Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”.
ER - TY - JOUR T1 - Toward vocabulary domain specifications for health level 7-coded data elements A1 - Bakken, S A1 - Campbell, K E A1 - Cimino, J J A1 - Huff, S M A1 - Hammond, W E Y1 - 2000/// KW - Health Status KW - Vocabulary KW - article KW - data base KW - health care KW - information science KW - linguistics KW - nomenclature KW - semantics JF - Journal of the American Medical Informatics Association VL - 7 IS - 4 SP - 333 EP - 342 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-0033940973&doi=10.1136%2Fjamia.2000.0070333&partnerID=40&md5=5009e2d47e71c39ace48a88dce3ff30d N1 - Cited By :36 Export Date: 10 September 2018 References: Campbell, K.E., Cohn, S.P., Chute, C.G., Shortliffe, E.H., Rennels, G., Scalable methodologies for distributed development of logic-based convergent medical terminology (1998) Methods Inf Med., 37 (4-5), pp. 426-439; Chute, C.G., Cohn, S.P., Campbell, J.R., A framework for comprehensive terminology systems in the united states: Development guidelines, criteria for selection, and public policy implications (1998) J Am Med Inform Assoc., 5 (6), pp. 503-510. , ANSI Health Care Informatics Standards Board Vocabulary Working Group and the Computer-based Patient Records Institute Working Group on Codes and Structures; Cimino, J.J., The concepts of language and the language of concepts (1998) Methods Inf Med., 37 (4-5), p. 311; Cimino, J.J., Desiderata for controlled medical vocabularies in the twenty-first century (1998) Methods Inf Med., 37 (4-5), pp. 394-403; Hammond, W.E., Call for a standard clinical vocabulary (1997) J Am Med Inform Assoc., 4 (3), pp. 254-255; Huff, S.M., Rocha, R.A., McDonald, C.J., Development of the LOINC (logical observations identifiers, names, and codes) vocabulary (1998) J Am Med Inform Assoc., 5 (3), pp. 276-292; Rector, A.L., Bechhofer, S., Goble, C.A., Horrocks, I., Nowlan, W.A., Solomon, W.D., The GRAIL concept modelling language for medical terminology (1997) Artif Intell Med., 9, pp. 139-171; Spackman, K.A., Campbell, K.E., Cote, R.A., SNOMED RT: A reference terminology for health care (1997) AMIA Annu Fall Symp., pp. 640-644. , Masys D (ed); Campbell, J., Carpenter, P., Sneiderman, C., Cohn, S., Chute, C., Warren, J., Phase II evaluation of clinical coding schemes: Completeness, taxonomy, mapping, definitions, and clarity (1997) J Am Med Inform Assoc., 4 (3), pp. 238-251; Chute, C.G., Cohn, S.P., Campbell, K.E., Oliver, D.E., Campbell, J.R., The content coverage of clinical classifications (1996) J Am Med Inform Assoc., 3 (3), pp. 224-233; Henry, S.B., Warren, J., Lange, L., Button, P., A review of the major nursing vocabularies and the extent to which they meet the characteristics required for implementation in computer-based systems (1998) J Am Med Inform Assoc., 5 (4), pp. 321-328; Henry, S.B., Mead, C.N., Nursing classification systems: Necessary but not sufficient for representing "what nurses do" for inclusion in computer-based patient record systems (1997) J Am Med Inform Assoc., 4 (3), pp. 222-232; (2000), http://www.h17.org, About HL7. Health Level 7 Web site. Accessed May 17; (1990) IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries, , New York: IEEE; Rossi-Mori, A., Consorti, F., Galeazzi, E., Standards to support development of terminological systems for health care telematics (1998) Methods Inf Med., 37 (4-5), pp. 551-563; Health level 7 (1999) Message Development Framework, , Ann Arbor, Mich: Health Level 7; Lindberg, D.A.B., Humphreys, B.L., McCray, A.T., The unified medical language system (1993) Methods Inf Med., 32, pp. 282-291; Rector, A.L., Glowinski, A.J., Nowlan, W.A., Rossi-Mori, A., Medical concept models and medical records: An approach based on GALEN and PEN & PAD (1995) J Am Med Inform Assoc., 2 (1), pp. 19-35; (1998) Code on Dental Procedures and Nomenclature, , Chicago, Ill: ADA; (1998) Systemized Nomenclature of Dentistry (SNODENT), , Chicago, Ill: ADA; (1993) Physician's Current Procedural Terminology, , Chicago, Ill: AMA; (1998) Alternate Billing Concepts. Version 983, , Las Cruces, NM: Alternate Link LLC; (1998) Centers for Disease Control Common Data Element Implementation Guide, , Atlanta, Ga: CDC; (1998) First Databank National Drug Data File, Master Drug Data Base, International Drug Data File, PIF, DDID, Multilex, Drug Knowledge Base, FDBDX, Medical Conditions, , San Bruno, Calif: First DataBank; (1998) Health Care Financing Administration Common Procedure Coding System (HCPCS): Level II Alpha-numeric Codes, , Baltimore, Md: HCFA; Saba, V.K., (1990) The Classification of Home Health Nursing Diagnoses and Interventions, , Washington, DC: Georgetown University; (1980) International Classification of Diseases: 9th Revision, , Clinical Modification (ICD-9-CM) Washington, DC: NCHS; (1998) International Statistical Classification of Diseases and Related Health Problems (ICD-10) Procedure Coding Systems (PCS), , Baltimore, Md: HCFA; (1998) International Classification of Primary Care, , Amsterdam, The Netherlands: WONCA; (1998) International Classification of Primary Care Drug Codes, , Amsterdam, The Netherlands: WONCA; (1998) Medicomp Systems I: MEDCIN, , Chantilly, Va: Medicomp Systems; (1998) Multum MediSource Lexicon, , Denver, Colo: Multum Information Services; O'Neil, M.J., Payne, C., Read, J.D., Read codes, version 3: A user led terminology (1995) Methods Inf Med., 34, pp. 187-192; (1999) Nursing Diagnoses: Definitions and Classification 1999-2000, , Philadelphia, Pa: NANDA; Grobe, S.J., The nursing intervention Lexicon and taxonomy: Implications for representing nursing care data in automated records (1996) Holistic Nurs Pract., 11 (1), pp. 48-63; McCloskey, J.C., Bulechek, G.M., (1996) Nursing Interventions Classification (NIC). 2nd Ed., , St Louis, Mo: Mosby; Johnson, M., Maas, M., (1997) Nursing Outcomes Classification (NOC), , St. Louis, Mo: Mosby; Martin, K.S., Scheet, N.J., (1992) The Omaha System: Applications for Community Health Nursing, , Philadelphia, Pa: Saunders; Ozbolt, J., Fruchtnicht, J.N., Hayden, J.R., Toward data standards for clinical nursing information (1994) J Am Med Inform Assoc., 1, pp. 175-185; Kleinbeck, S.V.M., In search of perioperative nursing data elements (1996) AORN J., 63 (5), pp. 926-931; (1998) Russian Translation of MeSH, , Moscow, Russia: State Central Scientific Medical Library; Henry, S.B., Holzemer, W.L., Reilly, C.A., Campbell, K.E., Terms used by nurses to describe patient problems: Can SNOMED III represent nursing concepts in the patient record? (1994) J Am Med Inform Assoc., 1, pp. 61-74; Humphreys, B.L., McCray, A.T., Cheh, M.L., Evaluating the coverage of controlled health data terminologies: Report on the results of the NLM/AHCPR large scale vocabulary test (1997) J Am Med Inform Assoc., 4 (6), pp. 484-500; Standards for medical identifiers, codes, and messages needed to create an efficient computer-stored medical record (1994) J Am Med Inform Assoc., 1, pp. 1-7; Rector, A.L., Thesauri and formal classifications: Terminologies for people and machines (1998) Methods Inf Med., 37 (4-5), pp. 501-509 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The 'vocabulary problem' has long plagued the developers, implementers, and users of computer-based systems. The authors review selected activities of the Health Level 7 (HL7) Vocabulary Technical Committee that are related to vocabulary domain specification for HL7 coded data elements. These activities include: 1) the development of two sets of principles to provide guidance to terminology stakeholders, including organizations seeking to deploy HL7-compliant systems, terminology developers, and terminology integrators; 2) the completion of a survey of terminology developers; 3) the development of a process for HL7 registration of terminologies; and 4) the maintenance of vocabulary domain specification tables. As background, vocabulary domain specification is defined and the relationship between the HL7 Reference Information Model and vocabulary domain specification is described. The activities of the Vocabulary Technical Committee complement the efforts of terminology developers and other stakeholders. These activities are aimed at realizing semantic interoperability in the context of the HL7 Message Development Framework, so that information exchange and use among disparate systems can occur for the delivery and management of direct clinical care as well as for purposes such as clinical research, outcome research, and population health management. ER - TY - BOOK T1 - Moving Towards a Blockchain-Based Healthcare Information System A1 - Balis, C A1 - Tagopoulos, I A1 - Dimola, K Y1 - 2019/// JF - Studies in Health Technology and Informatics VL - 262 SP - 168 EP - 171 SN - 9781614999867 DO - 10.3233/SHTI190044 N2 - ©2019 The authors and IOS Press. All rights reserved. One of the major problems that a national health system face is the lack of a unified clinical data management. In Greece, the critical and sensitive medical data generated during a patient lifetime are fragmented in one or more hospitals and healthcare services are not characterized by a 'continuity' factor. There is not the appropriate technological and administrative infrastructure for a unified patient medical history, prescriptions, laboratory tests or therapeutic plan. Technological, administrative and economic factors have led to this situation. We propose the integration and implementation of a blockchain network as a complementary technology to the existing information systems, so reliable and effective information management could be provided by a healthcare organization or the national healthcare system. Blockchain technology could be implemented as a bridge that can provide information systems interoperability within a hospital or between different hospitals. ER - TY - CONF T1 - Using the EC decision on case definitions for communicable diseases as a terminology source - Lessons learned A1 - Balkanyi, L A1 - Heja, G A1 - Nagy, A Y1 - 2014/// KW - Communicable Diseases KW - Data Mining KW - Databases, Factual KW - Dictionaries as Topic KW - Europe KW - Guidelines as Topic KW - Humans KW - Knowledge engineering KW - Ontology KW - Public health regulation KW - Terminology as Topic KW - Terminology extraction KW - Vocabulary, Controlled KW - book KW - classification KW - communicable disease KW - controlled vocabulary KW - data mining KW - factual database KW - human KW - nomenclature KW - practice guideline KW - standards VL - 197 SP - 3 EP - 7 N1 - Cited By :1 Export Date: 10 September 2018 References: (2012), p. 5538. , http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2012:262:0001: 0057:EN:PDF, COMMISSION IMPLEMENTING DECISION of 8 August 2012 amending Decision 2002/253/EC, laying down case definitions for reporting communicable diseases to the Community network under Decision No 2119/98/EC of the European Parliament and of the Council (notified under document C. EU Commission, 2012; Balkanyi, L., Terminology services-an example of knowledge management in public health (2007) Euro Surveill, 12 (22), p. 3211; Cimino, J.J., Desiderata for controlled medical vocabularies in the twenty-first century (1998) Methods Inf Med, 37, pp. 394-403. , http://www.eurosurveillance.org/ViewArticle.aspx?ArticleId=3211; http://www.cdc.gov/phin/tools/PHINvads/; Schulz, S., Boeker, M., Stenzhorn, H., Niggemann, J., Granularity issues in the alignment of upper ontologies (2009) Methods Inf Med, 48, pp. 184-189; http://www.w3.org/TR/owl-features/; http://www.w3.org/2004/02/skos/; http://www.w3.org/TR/soap/; http://www.w3.org/TR/sparql11-overview/UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903735879&doi=10.3233%2f978-1-61499-389-6-3&partnerID=40&md5=ec19c876fb1d31cedce5acad767bdfe3 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Extracting scientifically accurate terminology from an EU public health regulation is part of the knowledge engineering work at the European Centre for Disease Prevention and Control (ECDC). ECDC operates information systems at the crossroads of many areas-posing a challenge for transparency and consistency. Semantic interoperability is based on the Terminology Server (TS). TS value sets (structured vocabularies) describe shared domains as 'diseases', 'organisms', 'public health terms', 'geo-entities' 'organizations' and 'administrative terms' and others. We extracted information from the relevant EC Implementing Decision on case definitions for reporting communicable diseases, listing 53 notifiable infectious diseases, containing clinical, diagnostic, laboratory and epidemiological criteria. We performed a consistency check; a simplification-abstraction; we represented lab criteria in triplets: as 'y' procedural result /of 'x' organism-substance/on 'z' specimen and identified negations. The resulting new case definition value set represents the various formalized criteria, meanwhile the existing disease value set has been extended, new signs and symptoms were added. New organisms enriched the organism value set. Other new categories have been added to the public health value set, as transmission modes; substances; specimens and procedures. We identified problem areas, as (a) some classification error(s); (b) inconsistent granularity of conditions; (c) seemingly nonsense criteria, medical trivialities; (d) possible logical errors, (e) seemingly factual errors that might be phrasing errors. We think our hypothesis regarding room for possible improvements is valid: there are some open issues and a further improved legal text might lead to more precise epidemiologic data collection. It has to be noted that formal representation for automatic classification of cases was out of scope, such a task would require other formalism, as e.g. those used by rule-based decision support systems. ER - TY - JOUR T1 - Implementing standards for the interoperability among healthcare providers in the public regionalized Healthcare Information System of the Lombardy Region A1 - Barbarito, F A1 - Pinciroli, F A1 - Mason, J A1 - Marceglia, S A1 - Mazzola, L A1 - Bonacina, S Y1 - 2012/// KW - Electronic Health Records KW - HL7 KW - Health care KW - Health information systems KW - Health standards KW - Hospitals KW - Hospitals, Public KW - Humans KW - Industry KW - Information Systems KW - Information systems KW - Integrating the Healthcare Enterprise KW - Integrating the healthcare enterprise KW - Interoperability KW - Italy KW - Life-long personal health record KW - Medical Informatics KW - Personal health record KW - Quality of Health Care KW - Radiology KW - Specifications KW - Standards KW - Systems Integration KW - Workflow KW - access to information KW - article KW - conceptual framework KW - general practitioner KW - government KW - health care management KW - health care organization KW - health care personnel KW - health care system KW - hospital KW - human KW - information dissemination KW - interpersonal communication KW - medical information KW - medical information system KW - patient care KW - physician KW - priority journal KW - privacy KW - standardization KW - technology KW - workflow JF - Journal of Biomedical Informatics VL - 45 IS - 4 SP - 736 EP - 745 N1 - Cited By :32 Export Date: 10 September 2018 References: Peterson, H.E., From punched cards to computerized patient records: a personal journey (2006) Yearbook Med Inform, pp. 180-186; Ludwick, D.A., Doucette, J., Adopting electronic medical records in primary care: lessons learned from health information systems implementation experience in seven countries (2009) Int J Med Inform, 78 (1), pp. 22-31; Häyrinen, K., Saranto, K., Nykänen, P., Definition, structure, content, use and impacts of electronic health records: a review of the research literature (2008) Int J Med Inform, 77 (5), pp. 291-304; Nøhr, C., Evaluation of electronic health record systems (2006) Yearbook Med Inform, pp. 107-113; Ploem, C., Gevers, S., Introduction of a national electronic patient record in The Netherlands: some legal issues (2011) Eur J Health Law, 18 (2), pp. 191-204; Garg, A.X., Adhikari, N.K., McDonald, H., Rosas-Arellano, M.P., Devereaux, P.J., Beyene, J., Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review (2005) JAMA, 293 (10), pp. 1223-1238; Gryfe, C.I., Getting physicians to accept new information technology (2006) Can Med Assoc J, 174 (11), pp. 1573-1578; Doebbeling, B.N., Chou, A.F., Tierney, W.M., Priorities and strategies for the implementation of integrated informatics and communications technology to improve evidence-based practice (2006) J Gen Int Med, 21 (SUPPL. 2), pp. S50-S57; Ash, J.S., Berg, M., Coiera, E., Some unintended consequences of information technology in health care: the nature of patient care information system-related errors (2004) J Am Med Inform Assoc, 11 (2), pp. 104-112; Whittaker, A.A., Aufdenkamp, M., Tinley, S., Barriers and facilitators to electronic documentation in a rural hospital (2009) J Nurs Scholarsh, 41 (3), pp. 293-300; Terry, A.L., Giles, G., Brown, J.B., Thind, A., Stewart, M., Adoption of electronic medical records in family practice: the providers' perspective (2009) Fam Med, 41 (7), pp. 508-512; Kaushal, R., Bates, D.W., Jenter, C.A., Mills, S.A., Volk, L.A., Burdick, E., Imminent adopters of electronic health records in ambulatory care (2009) Inform Prim Care, 17 (1), pp. 7-15; Pinciroli, F., Corso, M., Fuggetta, A., Masseroli, M., Bonacina, S., Marceglia, S., Telemedicine and e-health (2011) IEEE Pulse, 2 (3), pp. 62-70; Goroll, A.H., Simon, S.R., Tripathi, M., Ascenzo, C., Bates, D.W., Community-wide implementation of health information technology: the Massachusetts eHealth collaborative experience (2009) J Am Med Inform Assoc, 16 (1), pp. 132-139; Namli, T., Dogac, A., Testing conformance and interoperability of eHealth applications (2010) Methods Inf Med, 49 (3), pp. 281-289; Daniel, C., GarcíaRojo, M., Bourquard, K., Henin, D., Schrader, T., Della Mea, V., Standards to support information systems integration in anatomic pathology (2009) Arch Pathol Lab Med, 133 (11), pp. 1841-1849; Ohmann, C., Kuchinke, W., Future developments of medical informatics from the viewpoint of networked clinical research. Interoperability and integration (2009) Methods Inf Med, 48 (1), pp. 45-54; Henderson, M.L., Dayhoff, R.E., Titton, C.P., Casertano, A., Using IHE and HL7 conformance to specify consistent PACS interoperability for a large multi-center enterprise (2006) J Healthcare Inf Manage, 20 (3), pp. 47-53; Yuksel, M., Dogac, A., Interoperability of medical device information and the clinical applications: an HL7 RMIM based on the ISO/IEEE 11073 DIM (2011) IEEE Trans Inf Technol Biomed, 15 (4), pp. 557-566; (2004), ISO/DTR 20514. Health informatics - electronic health record - definition, scope, and context; Kalra, D., Electronic health record standards (2006) Yearbook Med Inform, pp. 136-144; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., HL7 clinical document architecture, release 2 (2006) J Am Med Inform Assoc, 13 (1), pp. 30-39; http://www.astm.org/Standards/E2369.htm, ASTM Continuity of Care Record (CCR). [last access 18.07.11]; Ferranti, J.M., Musser, R.C., Kawamoto, K., Hammond, W.E., The clinical document architecture and the continuity of care record: a critical analysis (2006) J Am Med Inform Assoc, 13 (3), pp. 245-252; American College of Cardiology (2001) Healthcare Information and Management Systems Society and the Radiological Society of North America, , http://www.ihe.net/About/index.cfm, Integrating the Healthcare Enterprise, (online ). [last access 18.07.11]; Demiris, G., Afrin, L.B., Speedie, S., Courtney, K.L., Sondhi, M., Vimarlund, V., Patient-centered applications: use of information technology to promote disease management and wellness. A white paper by the AMIA knowledge in motion working group (2008) J Am Med Inform Assoc, 15 (1), pp. 8-13; Rothstein, M.A., The hippocratic bargain and health information technology (2010) J Law Med Ethics, 38 (1), pp. 7-13; Detmer, D., Bloomrosen, M., Raymond, B., Tang, P., Integrated personal health records: transformative tools for consumer-centric care (2008) BMC Med Inform Decis Mak, 8, p. 45; Bonacina, S., Marceglia, S., Pinciroli, F., Barriers against adoption of electronic health record in Italy (2011) J Healthcare Eng, 2 (4), pp. 509-526; Health Level Seven International. HL7 messaging standard version 2.5; Regione Lombardia http://www.siss.regione.lombardia.it/EdmaSissPortaleSitoWeb/documentoDiProgetto.do?TIP=15336033&CAT=15334979&DEST=null&TESTO=&ACT=3&sDir=1, Sistema Informativo Socio-Sanitario - SISS. Linee guida e specifiche generali di progetto. [last access 18.07.11]; IHE IT Infrastructure Technical Framework (2010), 1, pp. 112-24. , ITI TF-1: integration profiles, IHE International, Inc.;; IHE Radiology Technical Framework (2011), 1. , Integration profiles, IHE International, Inc.;; IHE Laboratory (LAB) Technical Framework (2011), 2. , Transactions, IHE International, Inc.;; Netlink Project. Presentation of netlink project; ) (2002), http://www.sesam-vitale.fr/netlink/netlk_pres.htm, [last access 18.07.11]UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863320896&doi=10.1016%2fj.jbi.2012.01.006&partnerID=40&md5=1a56da411090d016e56da2d9fe1b87ea RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Information technologies (ITs) have now entered the everyday workflow in a variety of healthcare providers with a certain degree of independence. This independence may be the cause of difficulty in interoperability between information systems and it can be overcome through the implementation and adoption of standards. Here we present the case of the Lombardy Region, in Italy, that has been able, in the last 10. years, to set up the Regional Social and Healthcare Information System, connecting all the healthcare providers within the region, and providing full access to clinical and health-related documents independently from the healthcare organization that generated the document itself. This goal, in a region with almost 10 millions citizens, was achieved through a twofold approach: first, the political and operative push towards the adoption of the Health Level 7 (HL7) standard within single hospitals and, second, providing a technological infrastructure for data sharing based on interoperability specifications recognized at the regional level for messages transmitted from healthcare providers to the central domain. The adoption of such regional interoperability specifications enabled the communication among heterogeneous systems placed in different hospitals in Lombardy. Integrating the Healthcare Enterprise (IHE) integration profiles which refer to HL7 standards are adopted within hospitals for message exchange and for the definition of integration scenarios. The IHE patient administration management (PAM) profile with its different workflows is adopted for patient management, whereas the Scheduled Workflow (SWF), the Laboratory Testing Workflow (LTW), and the Ambulatory Testing Workflow (ATW) are adopted for order management. At present, the system manages 4,700,000 pharmacological e-prescriptions, and 1,700,000 e-prescriptions for laboratory exams per month. It produces, monthly, 490,000 laboratory medical reports, 180,000 radiology medical reports, 180,000 first aid medical reports, and 58,000 discharge summaries. Hence, despite there being still work in progress, the Lombardy Region healthcare system is a fully interoperable social healthcare system connecting patients, healthcare providers, healthcare organizations, and healthcare professionals in a large and heterogeneous territory through the implementation of international health standards. © 2012 Elsevier Inc. ER - TY - CONF T1 - Supporting digital healthcare services using semantic web technologies A1 - Barisevičius, Gintaras A1 - Coste, Martin A1 - Geleta, David A1 - Juric, Damir A1 - Khodadadi, Mohammad A1 - Stoilos, Giorgos A1 - Zaihrayeu, Ilya Y1 - 2018/// PB - Springer Verlag JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) VL - 11137 LNCS SP - 291 EP - 306 SN - 9783030006679 DO - 10.1007/978-3-030-00668-6_18 N2 - We report on our efforts and faced challenges in using Semantic Web technologies for the purposes of supporting healthcare services provided by Babylon Health. First, we created a large medical Linked Data Graph (LDG) which integrates many publicly available (bio)medical data sources as well as several country specific ones for which we had to build custom RDF-converters. Even for data sources already distributed in RDF format a conversion process had to be applied in order to unify their schemata, simplify their structure and adapt them to the Babylon data model. Another important issue in maintaining and managing the LDG was versioning and updating with new releases of data sources. After creating the LDG, various services were built on top in order to provide an abstraction layer for non-expert end-users like doctors and software engineers which need to interact with it. Finally, we report on one of the key use cases built in Babylon, namely an AI-based chatbot which can be used by users to determine if they are in need of immediate medical treatment or they can follow a conservative treatment at home. To match user text to our internal AI-models an NLP-based knowledge extraction and logic-based reasoning approach was implemented and evaluation provided with encouraging results. ER - TY - JOUR T1 - HHS proposes steps toward health data interoperability: CMS and ONC proposals would implement cures act A1 - Barlas, S Y1 - 2019/// JF - P and T VL - 44 IS - 6 SP - 347 EP - 349 ER - TY - JOUR T1 - Big Data in the Era of Health Information Exchanges: Challenges and Opportunities for Public Health A1 - Baseman, Janet A1 - Revere, Debra A1 - Painter, Ian Y1 - 2017/// KW - big data KW - communicable diseases KW - data mining KW - data quality KW - epidemiology KW - health information exchange KW - infectious diseases KW - population surveillance KW - public health JF - Informatics VL - 4 IS - 4 SP - 39 EP - 39 UR - http://www.mdpi.com/2227-9709/4/4/39 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public health surveillance of communicable diseases depends on timely, complete, accurate, and useful data that are collected across a number of healthcare and public health systems. Health Information Exchanges (HIEs) which support electronic sharing of data and information between health care organizations are recognized as a source of ‘big data’ in healthcare and have the potential to provide public health with a single stream of data collated across disparate systems and sources. However, given these data are not collected specifically to meet public health objectives, it is unknown whether a public health agency’s (PHA’s) secondary use of the data is supportive of or presents additional barriers to meeting disease reporting and surveillance needs. To explore this issue, we conducted an assessment of big data that is available to a PHA—laboratory test results and clinician-generated notifiable condition report data—through its participation in a HIE. ER - TY - JOUR T1 - The Dementias Platform UK (DPUK) Data Portal A1 - Bauermeister, S A1 - Orton, C A1 - Thompson, S A1 - Barker, R A A1 - Bauermeister, J R A1 - Ben-Shlomo, Y A1 - Brayne, C A1 - Burn, D A1 - Campbell, A A1 - Calvin, C A1 - Wong, A A1 - Gallacher, J E J Y1 - 2020/// JF - European Journal of Epidemiology VL - 35 IS - 6 SP - 601 EP - 611 DO - 10.1007/s10654-020-00633-4 N2 - ©2020, The Author(s). The Dementias Platform UK Data Portal is a data repository facilitating access to data for 3 370 929 individuals in 42 cohorts. The Data Portal is an end-to-end data management solution providing a secure, fully auditable, remote access environment for the analysis of cohort data. All projects utilising the data are by default collaborations with the cohort research teams generating the data. The Data Portal uses UK Secure eResearch Platform infrastructure to provide three core utilities: data discovery, access, and analysis. These are delivered using a 7 layered architecture comprising: data ingestion, data curation, platform interoperability, data discovery, access brokerage, data analysis and knowledge preservation. Automated, streamlined, and standardised procedures reduce the administrative burden for all stakeholders, particularly for requests involving multiple independent datasets, where a single request may be forwarded to multiple data controllers. Researchers are provided with their own secure ‘lab' using VMware which is accessed using two factor authentication. Over the last 2 years, 160 project proposals involving 579 individual cohort data access requests were received. These were received from 268 applicants spanning 72 institutions (56 academic, 13 commercial, 3 government) in 16 countries with 84 requests involving multiple cohorts. Projects are varied including multi-modal, machine learning, and Mendelian randomisation analyses. Data access is usually free at point of use although a small number of cohorts require a data access fee. ER - TY - JOUR T1 - HL7 FHIR: An agile and RESTful approach to healthcare information exchange A1 - Bender, Duane A1 - Sartipi, Kamran Y1 - 2013/// KW - Agile KW - FHIR KW - HL7 v3 KW - Healthcare KW - Informatics KW - Interoperability KW - RESTful KW - Standards KW - eHealth JF - Proceedings of CBMS 2013 - 26th IEEE International Symposium on Computer-Based Medical Systems IS - March SP - 326 EP - 331 SN - 9781479910533 DO - 10.1109/CBMS.2013.6627810 L1 - file:///C:/Users/fernanda.dorea/Downloads/CBMS2013 (1).pdf N2 - This research examines the potential for new Health Level 7 (HL7) standard Fast Healthcare Interoperability Resources (FHIR, pronounced "fire") standard to help achieve healthcare systems interoperability. HL7 messaging standards are widely implemented by the healthcare industry and have been deployed internationally for decades. HL7 Version 2 ("v2") health information exchange standards are a popular choice of local hospital communities for the exchange of healthcare information, including electronic medical record information. In development for 15 years, HL7 Version 3 ("v3") was designed to be the successor to Version 2, addressing Version 2's shortcomings. HL7 v3 has been heavily criticized by the industry for being internally inconsistent even in it's own documentation, too complex and expensive to implement in real world systems and has been accused of contributing towards many failed and stalled systems implementations. HL7 is now experimenting with a new approach to the development of standards with FHIR. This research provides a chronicle of the evolution of the HL7 messaging standards, an introduction to HL7 FHIR and a comparative analysis between HL7 FHIR and previous HL7 messaging standards. © 2013 IEEE. ER - TY - JOUR T1 - A data infrastructure for the assessment of health care performance: Lessons from the BRIDGE-health project A1 - Bernal-Delgado, E A1 - Estupiñán-Romero, F Y1 - 2018/// KW - article KW - comparative effectiveness KW - controlled study KW - electronic health record KW - human KW - logic KW - major clinical study KW - monitoring KW - ontology KW - public health KW - quality control KW - travel JF - Archives of Public Health VL - 76 IS - 1 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041012151&doi=10.1186%2Fs13690-017-0245-1&partnerID=40&md5=d131cfa0a39fdde7fbe8876c87cedec6 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Bernal-Delgado, Estupiñán-Romero - 2018 - A data infrastructure for the assessment of health care performance Lessons from the BRIDGE-he.pdf N1 - Export Date: 10 September 2018 References: https://ec.europa.eu/health//sites/health/files/systems_performance:assessment/docs/com2014_215_final_en.pdf, Communication on effective, accessible and resilient health systems. COM (2014) 215 final, [Accessed 3 Aug 2017]; http://www.ices.on.ca/Publications/Atlases-and-Reports, [Accessed 3 Aug 2017]; (2010), http://www.qualityindicators.ahrq.gov, [Accessed 3 Aug 2017]; https://www.england.nhs.uk/rightcare/products/atlas/, [Accessed 3 Aug 2017]; https://www.volksgezondheidenzorg.info/onderwerp/atlas-vzinfo/inleidingand!node-kaarten, [Accessed 3 Aug 2017]; http://www.hqsc.govt.nz/our-programmes/health-quality-evaluation/projects/atlas-of-healthcare-variation/, [Accessed 3 Aug 2017]; (2016), http://dx.doi.org/10.1787/9789264265592-en, Health at a glance: Europe 2016: state of health in the EU cycle, OECD Publishing, Paris, [Accessed 3 Aug 2017]; http://www.oecd.org/els/health-systems/health-care-quality-reviews.htm, [Accessed 3 Aug 2017]; https://ec.europa.eu/health/systems_performance:assessment/policy/expert_group_en, [Accessed 3 Aug 2017]; Bernal-Delgado, E., on behalf of ECHO Consortium, T. Christiansen, on behalf of ECHO Consortium, K. Bloor, on behalf of ECHO Consortium, C. Mateus, on behalf of ECHO Consortium, A.M. Yazbeck, on behalf of ECHO Consortium, J. Munck, on behalf of ECHO Consortium, J. Bremner, on behalf of ECHO Consortium; ECHO: health care performance assessment in several European health systems Eur J Pub Health 2015, 25, pp. 3-7. , https://doi.org/10.1093/eurpub/cku219; Thygesen, C.T., Baixauli-Pérez, C., Librero-López, J., Martínez-Lizaga, N., Ridao-López, M., Bernal-Delgado, E., on behalf of the ECHO Consortium Eur J Pub Health, 25, pp. 8-14. , https://doi.org/10.1093/eurpub/cku229, Comparing variation across European countries: building geographical areas to provide sounder estimates; Bergdahl, M., Ehling, M., Elvers, E., Földesi, E., Körner, T., Kron, A., (2007) Handbook on data quality assessment methods and tools, , Wiesbaden: European Comission RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-EXCLUSION-REASONS: possibly useful methods? N2 - The integration of different administrative data sources from a number of European countries has been shown useful in the assessment of unwarranted variations in health care performance. This essay describes the procedures used to set up a data infrastructure (e.g., data access and exchange, definition of the minimum common wealth of data required, and the development of the relational logic data model) and, the methods to produce trustworthy healthcare performance measurements (e.g., ontologies standardisation and quality assurance analysis). The paper ends providing some hints on how to use these lessons in an eventual European infrastructure on public health research and monitoring. Although the relational data infrastructure developed has been proven accurate, effective to compare health system performance across different countries, and efficient enough to deal with hundred of millions of episodes, the logic data model might not be responsive if the European infrastructure aims at including electronic health records and carrying out multi-cohort multi-intervention comparative effectiveness research. The deployment of a distributed infrastructure based on semantic interoperability, where individual data remain in-country and open-access scripts for data management and analysis travel around the hubs composing the infrastructure, might be a sensible way forward. © 2018 The Author(s). ER - TY - CONF T1 - VacSeen: A linked data-based information architecture to track vaccines using barcode scan authentication A1 - Bhattacharjee, P S A1 - Solanki, M A1 - Bhattacharyya, R A1 - Ehrenberg, I A1 - Sarma, S Y1 - 2015/// KW - Abstracting KW - Authentication KW - Automatic identification and data capture KW - Automation KW - Bar codes KW - Barcode KW - Cellular telephone systems KW - Data handling KW - Data visualization KW - Developing Countries KW - Developing countries KW - EEM KW - EventModeling KW - Existing architectures KW - Health information systems KW - Information Systems KW - Information architectures KW - Information systems KW - Interoperability KW - LOD Cloud KW - Pharmaceutical company KW - Public health KW - Public-health agencies KW - RDBMS2RDF KW - Semantic Web KW - Supply Chain KW - Supply chains KW - Vaccination KW - Vaccine KW - Vaccines KW - World Wide Web VL - 1546 SP - 39 EP - 48 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964005669&partnerID=40&md5=a44c71c2af1e312712e8ba7b400e9a76 N1 - Cited By :1 Export Date: 10 September 2018 References: Andre, F., Booy, R., Bock, H., Clemens, J., Datta, S., John, T., Lee, B., Ruff, T., Vaccination greatly reduces disease, disability, death and inequity worldwide (2008) Bulletin of the World Health Organization, 86 (2), pp. 140-146; Au, L., Oster, A., Yeh, G., Magno, J., Paek, H., Utilizing an electronic health record system to improve vaccination coverage in children (2010) Appl Clin Inform, 1 (3), pp. 221-231; Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z., (2007) Dbpedia: A Nucleus for A Web of Open Data, , Springer; Barlas, S., Fda weighs updating its bar-code mandate: Hospital pharmacies worry about implementation (2012) Pharmacy and Therapeutics, 37 (3), p. 162; Katib, A., Rao, D., Rao, P., Williams, K., Grant, J., A prototype of a novel cell phone application for tracking the vaccination coverage of children in rural communities (2015) Computer Methods and Programs in Biomedicine; Michel, F., Montagnat, J., Faron-Zucker, C., (2014) A Survey of Rdb to Rdf Translation Approaches and Tools; Solanki, M., Brewster, C., Representing supply chain events on the web of data (2013) Workshop on Detection, Representation, and Exploitation of Events in the Semantic Web (DeRiVE) at ISWC, , CEUR-WS.org, proceedings; Solanki, M., Brewster, C., EPCIS event based traceability in pharmaceutical supply chains via automated generation of linked pedigrees (2014) Proceedings of the 13th International Semantic Web Conference (ISWC), , Peter Mika et al., editor, Springer-Verlag; Solanki, M., Brewster, C., Monitoring EPCIS Exceptions in linked traceability streams across supply chain business processes (2014) Proceedings of the 10th International Conference on Semantic Systems(SEMANTiCS), , ACM-ICPS; Thornton, D., Mwanyika, H., Meek, D., Kreysa, U., (2013) Tanzania Leading the Way with Barcodes on Vaccine Packaging, , OPTIMIZE; Zaffran, M., Vandelaer, J., Kristensen, D., Melgaard, B., Yadav, P., Antwi-Agyei, K., Lasher, H., The imperative for stronger vaccine supply and logistics systems (2013) Vaccine, 31, pp. B73-B80 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Renewed global efforts to deploy Automatic Identification and Data Capture (AIDC) technologies, such as barcodes, on vaccine packaging in developing countries are currently underway. An opportunity to evaluate Linked Data technologies for generating an ecosystem of data connectedness and interoperability in the vaccine supply chain presents itself. We discuss the VacSeen project, a Linked Data-based information system to track vaccines through visualization and authentication of barcode scans on vaccine packaging using mobile phones. The project is aimed at enabling endeavors such as logistical planning and integration with health information systems, demand forecasting, anticounterfeiting and diversion measures, and post-marketing surveillance by pharmaceutical companies, supply chain contractors, and public health agencies. By forming an abstraction layer over siloed data while necessitating minimal modification of existing architecture, VacSeen can help minimize the technical, operational, and political friction often associated with fostering data interoperability. We discuss VacSeen's software architecture and present sample data analytics that highlight VacSeen's ability to facilitate the interoperability of diverse and non-standardized data sources. Limitations of the current framework and areas of future exploration and expansion are also discussed. © Copyright 2015 for the individual papers by the papers' authors. ER - TY - JOUR T1 - Uses of Electronic Health Records for Public Health Surveillance to Advance Public Health A1 - Birkhead, Guthrie S A1 - Klompas, Michael A1 - Shah, Nirav R Y1 - 2015/// JF - Annual Review of Public Health VL - 36 IS - 1 SP - 345 EP - 359 UR - http://www.annualreviews.org/doi/abs/10.1146/annurev-publhealth-031914-122747 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} ER - TY - JOUR T1 - Ten recommendations for supporting open pathogen genomic analysis in public health A1 - Black, A A1 - MacCannell, D R A1 - Sibley, T R A1 - Bedford, T Y1 - 2020/// JF - Nature Medicine VL - 26 IS - 6 SP - 832 EP - 841 DO - 10.1038/s41591-020-0935-z N2 - ©2020, Springer Nature America, Inc. Increasingly, public-health agencies are using pathogen genomic sequence data to support surveillance and epidemiological investigations. As access to whole-genome sequencing has grown, greater amounts of molecular data have helped improve the ability to detect and track outbreaks of diseases such as COVID-19, investigate transmission chains and explore large-scale population dynamics, such as the spread of antibiotic resistance. However, the wide adoption of whole-genome sequencing also poses new challenges for public-health agencies that must adapt to support a new set of expertise, which means that the capacity to perform genomic data assembly and analysis has not expanded as widely as the adoption of sequencing itself. In this Perspective, we make recommendations for developing an accessible, unified informatic ecosystem to support pathogen genomic analysis in public-health agencies across income settings. We hope that the creation of this ecosystem will allow agencies to effectively and efficiently share data, workflows and analyses and thereby increase the reproducibility, accessibility and auditability of pathogen genomic analysis while also supporting agency autonomy. ER - TY - JOUR T1 - Data sharing for precision medicine: Policy lessons and future directions A1 - Blasimme, A A1 - Fadda, M A1 - Schneider, M A1 - Vayena, E Y1 - 2018/// KW - Information Dissemination KW - Privacy KW - article KW - ecosystem KW - landscape KW - organization KW - personalized medicine KW - practice guideline KW - privacy JF - Health Affairs VL - 37 IS - 5 SP - 702 EP - 709 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046742958&doi=10.1377%2Fhlthaff.2017.1558&partnerID=40&md5=feb9f0d418935cc19c5106f934edcfe4 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Blasimme et al. - 2018 - Data sharing for precision medicine Policy lessons and future directions.pdf N1 - Cited By :1 Export Date: 10 September 2018 References: Khoury, M.J., Bowen, M.S., Clyne, M., Dotson, W.D., Gwinn, M.L., Green, R.F., From public health genomics to precision public health: a 20-year journey Genet Med, , 2017 Dec 14. [Epub ahead of print]; (2011) Toward precision medicine: building a knowledge network for biomedical research and a new taxonomy of disease, , Washington (DC): National Academies Press; Collins, F.S., Varmus, H., A new initiative on precision medicine (2015) N Engl J Med, 372 (9), pp. 793-795; Marx, V., The DNA of a nation (2015) Nature, 524 (7566), pp. 503-505; Bahcall, O., Precision medicine (2015) Nature, 526 (7573), p. 335; Meier-Abt, P., Lawrence, A.K., Selter, L., Vayena, E., Schwede, T., The Swiss approach to precision medicine, , https://smw.ch/en/op-eds/post/the-swissapproach-to-precision-medicine/, Swiss Medical Weekly [serial on the Internet]. 2018 Jan 2 [cited 2018 Mar 16]; Kohane, I.S., Health care policy Ten things we have to do to achieve precision medicine (2015) Science, 349 (6243), pp. 37-38; Vayena, E., Dzenowagis, J., Brownstein, J.S., Sheikh, A., Policy implications of big data in the health sector (2018) Bull World Health Organ, 96 (1), pp. 66-68; Jain, S.H., Powers, B.W., Hawkins, J.B., Brownstein, J.S., The digital phenotype (2015) Nat Biotechnol, 33 (5), pp. 462-463; Vayena, E., Haeusermann, T., Adjekum, A., Blasimme, A., Digital health: meeting the ethical and policy challenges (2018) Swiss Med Wkly, 148; Elenko, E., Underwood, L., Zohar, D., Defining digital medicine (2015) Nat Biotechnol, 33 (5), pp. 456-461; Sansone, S.-A., Rocca-Serra, P., Field, D., Maguire, E., Taylor, C., Hofmann, O., Toward interoperable bioscience data (2012) Nat Genet, 44 (2), pp. 121-126; Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A.U., Wu, L., Read, E., Data sharing by scientists: practices and perceptions (2011) PLoS One, 6 (6); Wallis, J.C., Rolando, E., Borgman, C.L., If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology (2013) PLoS One, 8 (7); Van Panhuis, W.G., Paul, P., Emerson, C., Grefenstette, J., Wilder, R., Herbst, A.J., A systematic review of barriers to data sharing in public health (2014) BMC Public Health, 14 (1), p. 1144; Bauchner, H., Golub, R.M., Fontanarosa, P.B., Data sharing: an ethical and scientific imperative (2016) JAMA, 315 (12), pp. 1237-1239; Sejnowski, T.J., Churchland, P.S., Movshon, J.A., Putting big data to good use in neuroscience (2014) Nat Neurosci, 17 (11), pp. 1440-1441; To access the appendix, click on the Details tab of the article online; Rogers, R., (2013) Digital methods, , Cambridge (MA): MIT Press; Ackland, R., (2013) Web social science: concepts, data and tools for social scientists in the digital age, , London: Sage Publications; Scott, J., Carrington, P.J., (2011) The SAGE handbook of social network analysis, , London: SAGE Publications; Bastian, M., Heymann, S., Jacomy, M., Gephi: an open source software for exploring and manipulating networks Proceedings of the Third International Conference on Weblogs and Social Media [Internet], pp. 361-362. , https://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154/1009, In: Adar E, Hurst M, Finin T, Glance N, Nicolov N, Tseng B, eds. Menlo Park (CA): AAAI Press; 2009 [cited 2018 Mar 19]; Borgatti, S.P., Mehra, A., Brass, D.J., Labianca, G., Network analysis in the social sciences (2009) Science, 323 (5916), pp. 892-895; Faden, R.R., Beauchamp, T.L., (1986) A history and theory of informed consent, , New York (NY): Oxford University Press; Blasimme, A., Moret, C., Hurst, S.A., Vayena, E., Informed consent and the disclosure of clinical results to research participants (2017) Am J Bioeth, 17 (7), pp. 58-60; Koenig, B.A., Have we asked too much of consent? (2014) Hastings Cent Rep, 44 (4), pp. 33-34; Vayena, E., Blasimme, A., Biomedical big data: new models of control over access, use and governance (2017) J Bioeth Inq, 14 (4), pp. 501-513; Better science together, , http://sagebionetworks.org//, [home page on the Internet]. Seattle (WA): Sage Bionetworks; c 2018 [cited 2018 Mar 19]; Azaria, A., Ekblaw, A., Vieira, T., Lippman, A., Medrec: using blockchain for medical data access and permission management (2016) Proceedings: 2016 2nd International Conference on Open and Big Data, pp. 25-30. , In: Awan I, Younas M, eds. Washington (DC): Institute of Electrical and Electronics Engineers; Benchoufi, M., Ravaud, P., Blockchain technology for improving clinical research quality (2017) Trials, 18 (1), p. 335; Dubovitskaya, A., Xu, Z., Ryu, S., Schumacher, M., Wang, F., Secure and trustable electronic medical records sharing using blockchain, , https://arxiv.org/pdf/1709.06528.pdf, [Internet]. Ithaca (NY): Cornell University Library; 2017 Aug 2 [cited 2018 Mar 20]. (arXiv:1709.06528v1); Froelicher, D., Egger, P., Sousa, J.S., Raisaro, J.L., Huang, Z., Mouchet, C., UnLynx: a decentralized system for privacy-conscious data sharing (2017) Proceedings on Privacy Enhancing Technologies, 2017 (4), pp. 232-250; Nikolaenko, V., Weinsberg, U., Ioannidis, S., Joye, M., Boneh, D., Taft, N., Privacy-preserving ridge regression on hundreds of millions of records (2013) In: Security and Privacy (SP), pp. 334-348. , 2013 IEEE Symposium on. IEEE; Raisaro, J.L., Choi, G., Pradervand, S., Colsenet, R., Jacquemont, N., Rosat, N., Protecting privacy and security of genomic data in i2b2 IEEE/ACM Transactions on Computational Biology and Bioinformatics, , https://infoscience.epfl.ch/record/229262/files/main.pdf, [serial on the Internet]. [Cited 2018 Mar 19]; Ackerman Shrier, A., Chang, A., Diakun-thibault, N., Forni, L., Landa, F., Mayo, J., Blockchain and health IT: algorithms, privacy, and data, , https://www.healthit.gov/sites/default/files/1-78-blockchainandhealthitalgorithmsprivacydata_whitepaper.pdf, [Internet]. Washington (DC): Department of Health and Human Services, Office of the National Coordinator for Health Information Technology; 2016 Aug 8 [cited 2018 Mar 19]. (White Paper); Credit where credit is overdue (2009) Nat Biotechnol, 27 (7), p. 579; Thorisson, G.A., Accreditation and attribution in data sharing (2009) Nat Biotechnol, 27 (11), pp. 984-985; Kaye, J., Heeney, C., Hawkins, N., de Vries, J., Boddington, P., Data sharing in genomics-re-shaping scientific practice (2009) Nat Rev Genet, 10 (5), pp. 331-335; Washington, V., DeSalvo, K., Mostashari, F., Blumenthal, D., The HITECH era and the path forward (2017) N Engl J Med, 377 (10), pp. 904-906; Hunton, Williams, L.L.P., Accountability: a compendium for stakeholders, , http://informationaccountability.org/wp-content/uploads/Centre-Accountability-Compendium.pdf, [Internet]. Washington (DC): Centre for Information Policy Leadership; 2011 Mar [cited 2018 Mar 19]; Accountability on the ground: provisional guidance on documenting processing operations for EU institutions, bodies and agencies: summary [Internet], , https://edps.europa.eu/sites/edp/files/publication/18-02-06_accountability_on_the_ground_summary_en.pdf, Brussels: EDPS; 2018 Feb [cited 2018 Mar 19]; Conducting privacy impact assessments: code of practice: Data Protection Act [Internet], , https://ico.org.uk/media/for-organisations/documents/1595/pia-code-ofpractice.pdf, Wilmslow (UK): ICO; 2014 Feb [cited 2018 Mar 19]; Katz, J., The regulation of human research-reflections and proposals (1973) Clin Res, 21 (4), pp. 785-791; O'Doherty, K.C., Burgess, M.M., Edwards, K., Gallagher, R.P., Hawkins, A.K., Kaye, J., From consent to institutions: designing adaptive governance for genomic biobanks (2011) Soc Sci Med, 73 (3), pp. 367-374; Winickoff, D.E., Jamal, L., Anderson, N.R., New modes of engagement for big data research (2016) Journal of Responsible Innovation, 3 (2), pp. 169-177; Blasimme, A., Vayena, E., Becoming partners, retaining autonomy: ethical considerations on the development of precision medicine (2016) BMC Med Ethics, 17 (1), p. 67; Blasimme, A., Vayena, E., "Tailored-toyou": public engagement and the political legitimation of precision medicine (2016) Perspect Biol Med, 59 (2), pp. 172-188; Arzberger, P., Schroeder, P., Beaulieu, A., Bowker, G., Casey, K., Laaksonen, L., Science and government An international framework to promote access to data (2004) Science, 303 (5665), pp. 1777-1778; Vayena, E., Blasimme, A., Health research with big data: time for systemic oversight (2018) J Law Med Ethics, 41 (6), pp. 119-129 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Data sharing is a precondition of precision medicine. Numerous organizations have produced abundant guidance on data sharing. Despite such efforts, data are not being shared to a degree that can trigger the expected data-driven revolution in precision medicine. We set out to explore why. Here we report the results of a comprehensive analysis of data-sharing guidelines issued over the past two decades by multiple organizations. We found that the guidelines overlap on a restricted set of policy themes. However, we observed substantial fragmentation in the policy landscape across specific organizations and data types. This may have contributed to the current stalemate in data sharing. To move toward a more efficient data-sharing ecosystem for precision medicine, policy makers should explore innovative ways to cope with central policy themes such as privacy, consent, and data quality; focus guidance on interoperability, attribution, and public engagement; and promote data-sharing policies that can be adapted to multiple data types. © 2018 Project HOPE- The People-to-People Health Foundation, Inc. ER - TY - CONF T1 - Standards and solutions for architecture based, ontology driven and individualized pervasive health A1 - Blobel, B Y1 - 2012/// KW - Architectural framework KW - Database Management Systems KW - EHealth KW - Electronic Health Records KW - Germany KW - Health Records, Personal KW - Individualized Medicine KW - Information Storage and Retrieval KW - Interoperability KW - Monitoring, Ambulatory KW - Ontology KW - Pervasive health KW - Practice Guidelines as Topic KW - Standards KW - Taxonomy KW - ambulatory monitoring KW - article KW - data base KW - electronic medical record KW - information retrieval KW - medical record KW - personalized medicine KW - practice guideline KW - standard VL - 177 SP - 147 EP - 157 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866763368&doi=10.3233%2F978-1-61499-069-7-147&partnerID=40&md5=f1fe9b9dbaf2cfc6607e8d375ac7e2f4 N1 - Cited By :5 Export Date: 10 September 2018 References: Blobel, B., Analysis, design and implementation of secure and interoperable distributed health information systems (2002) Series Studies in Health Technology and Informatics, 89. , IOS Press, Amsterdam; Lankhorst, M., Enterprise architecture at work (2009) The Enterprise Engineering Series, , Springer-Verlag, Berlin Heidelberg; (2006) OASIS Reference Model for SOA, Version 1.0, , OASIS, OASIS Standard, October, docs.oasisopen.org/soa-rm/v1.0/soa-rm.pdf; (2008) Reference Architecture for SOA Foundation, Version 1.0, , OASIS, OASIS Public Review Draft 1, April, : docs.oasis-open.org/soa-rm/ soa-ra/ v1.0/soa-ra-pr-01.pdf; Blobel, B., Ontologies, knowledge representation, artificial intelligence - Hype or prerequisite for international pHealth interoperability? (2011) E-Health Across Borders Without Boundaries, 165, pp. 11-20. , L. Stoicu-Tivadar, B. Blobel, T. MarČun, A. Orel (Edrs.), Series Studies in Health Technology and Informatics. IOS Press, Amsterdam, Berlin, Oxford, Tokyo, Washington; Blobel, B., Architectural approach to eHealth for enabling paradigm changes in health (2010) Methods Inf Med, 49 (2), pp. 123-134; Blobel, B., Concept representation in health informatics for enabling intelligent architectures (2006) Ubiquity: Technology for Better Health in Aging Societies, 124, pp. 285-291. , A. Hasman, R. Haux, J. van der Lei, E. De Clercq, F. Roger-France (Edrs.), Series Studies in Health Technology and Informatics. IOS Press, Amsterdam; Rebstock, M., Fengel, J., Paulheim, H., (2008) Ontologies-Based Business Integration, , Springer-Verlag, Berlin; Russel, S., Norvig, P., (2003) Artificial Intelligence - A Modern Approach, , 3rd ed., Upper Saddle River, NJ: Pearson Education; García-Matos, M., Väänänen, J., Abstract model theory as a framework for universal logic (2007) Logica Universalis, pp. 19-33. , J-Y Beziau (edr), 2nd Edition, Birkhäuser Verlag AG, Basel; Weidenbach, C., First-order tableaux with sorts (1995) J of the IGPL, 3 (6), pp. 887-906; Bloe, R., Kamareddine, F., Nederpelt, R., The barendregt cube with definitions and generalized reduction (1996) Information and Computation, 126 (2), pp. 123-143; Kamareddine, F., Laan, T., Nederpelt, R., (2004) A Modern Perspective on Type Theory, , Kluwer Academic Publishers, New York; Blobel, B., Brochhausen, M., Gonzaléz, C., Lopez, D.M., Oemig, F., A system-theoretical, architecture-based approach to ontology management MIE 2012, , submitted to; Gonzaléz, C., Blobel, B., Lopez, D.M., Formal specification of an ontology-based service for EHR interoperability (2012) MIE, , submitted to; Blobel, B., Ontologies, knowledge representation, artificial intelligence - Hype or prerequisite for international pHealth interoperability? (2011) Series Studies in Health Technology and Informatics, 165, pp. 11-20. , L.Stoicu-Tivadar, B.Blobel, T.MarČun, A.Orel (Edrs.): e-Health Across Borders Without Boundaries, IOS Press, Amsterdam, Berlin, Oxford, Tokyo, Washington RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Based on the long-term work of scientific institutions and SDOs dedicated to system architectures, an interoperability framework is presented to help navigation through existing, emerging and even future standards for comprehensive interoperability of intelligent health and social care services. HL7 artifacts as well as work products of competing organizations are classified and semi-formally interrelated. The methodology is proven in many international standard development and health information systems implementation projects. © 2012 The authors and IOS Press. All rights reserved. ER - TY - JOUR T1 - Towards a sustainable EU health information system infrastructure: A consensus driven approach A1 - Bogaert, P A1 - van Oers, H A1 - Van Oyen, H Y1 - 2018/// JF - Health Policy VL - 122 IS - 12 SP - 1340 EP - 1347 DO - 10.1016/j.healthpol.2018.10.009 N2 - ©2018 Elsevier B.V. Background: Health information in the EU is characterised by diversity and fragmentation of health information infrastructures. A well-defined and sustainable EU health information system infrastructure is lacking. The potential of a European Research Infrastructure Consortium on Health Information for Research and Evidence-based Policy (HIREP-ERIC) to take up this role is investigated. Methods: Two working groups, a BRIDGE Health Steering Committee and the European Commission's Drafting Group of the Expert Group on Health Information, discussed the technical and scientific description of the HIREP-ERIC through a consensus-driven modified Delphi technique. Results: Consensus was reached on three aspects of the HIREP-ERIC. First, it was defined as an infrastructure that facilitates interaction of networks and experts in health information by providing central governance and a more permanent collaboration. Second, the infrastructure should be distributed, with a central hub coordinating the operation of distributed networks. Third, it should provide easy access to high quality and comparable data for purposes of research and policy making, and focus its activities around generating, managing, exchanging and translating health information. Conclusion: A momentum has been created where representatives from 16 European countries agreed on the HIREP-ERIC as a pragmatic bottom-up approach to strengthen the current EU health information landscape. A Member States' commitment is needed at senior political level to make this consensus operational. ER - TY - CONF T1 - Data set standardization and its reusability in e-government under an interoperability framework - A pilot project to enhance the reusability of the agreed data sets in seven government domains A1 - Boonmee, C A1 - Saekow, A Y1 - 2009/// KW - Agriculture KW - Building techniques KW - Business process modelling KW - CCTS KW - Change management KW - Data sets KW - Design rules KW - Different domains KW - Electronic data exchange KW - Electronic data interchange KW - Government Agencies KW - Government agencies KW - Government data processing KW - Humanism KW - Humanities KW - Humans KW - Interoperability KW - Interoperability framework KW - Management KW - Management systems KW - Modelling methodology KW - New projects KW - Pilot Projects KW - Pilot projects KW - Public services KW - Reusability KW - Standardization KW - Success factors KW - TH e-GIF KW - Technical standards KW - UN/CEFACT KW - XML KW - XML schemas KW - e-CMS KW - e-GIF KW - e-Government KW - e-government SP - 149 EP - 154 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84871856588&partnerID=40&md5=1f068376b1751f012177cb97a4dba4fa N1 - Cited By :2 Export Date: 10 September 2018 References: Benoit, O., Patrik, H., Fernand, F., Interoperability of E-Government Information Systems: Issues of Identification and Data Sharing (2007) Journal of Management Information Systems, 23 (4), pp. 29-51; Boonmee, S., Saekow, A., Boonmee, C., (2008) A Group Collaboration Support System to Assist; ICEG-08 Proceeding of conference, pp. 73-82. , Building and Managing National Core Component Dictionary and XMLSchema Standards; Charalabidis, Y., Lampathaki, F., Psarras, J., (2009) Combination of Interoperability Registries with Process and Data Management Tools for Governmental Services Transformation, , HICSS-42 Proceeding of conference; Saekow, A., Jirachiefpattana, A., Boonmee, C., (2008) Electronic Government Interoperability in Thailand: A Pilot Project on Official Electronic Correspondence Letters Exchange between Heterogeneous Software Products, pp. 463-473. , ECEG-08 Proceeding of conference; Saekow, A., Boonmee, C., (2008) E-Government Interoperability System Development: Issue of Labour Statistic Information Management in Thailand, pp. 51-362. , ICEG-08 Proceeding of conference; Saekow, A., Boonmee, C., (2009) Towards a Practical Approach for Electronic Government Interoperability Framework (e-GIF), pp. 1-9. , HICSS-42 Proceeding of conference; (2006) Ministry of Information and Communication Technology, , Thailand, Thailand e-Government Interoperability Framework Version 1.0; Techniques and Methodologies Group (2006) United Nations Centre for Trade Facilitation and Electronic Business, , UN/CEFACT, (UN/CEFACT), UN/CEFACT Modeling Methodology Version 1.0 Technical specification (UMM); Techniques and Methodologies Group (2003) United Nations Centre for Trade Facilitation and Electronic Business, , UN/CEFACT, (UN/CEFACT), Core Components Technical Specification (CCTS) - Part 8 of the ebXML Framework; Techniques and Methodologies Group (2006) United Nations Centre for Trade Facilitation and Electronic Business, , UN/CEFACT, (UN/CEFACT), XML Naming and Design Rules Version 2.0 (NDR) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - To enhance government public service efficiency, an information seamless flow across government agencies is required. The standardization and simplification of data set to be used in electronic data exchange is significant. The agreed guideline and framework is required in a real life application.Thai government created an e-government interoperability framework (e-GIF) to be used as a tool for data exchange implementation. It includes five main parts; business process modelling, data set standardization technique, XML schema building technique, a collection of agreed interoperable technical standards and change management. For the business process modelling, a technique based on UN/CEFACT Modelling Methodology has been used. For the data set standardization, a technique based on CCTS has been used. For XML schema building, a technique based on UN/CEFACT XML naming and design rules has been used. It is found that the reusability of the agreed data sets across various agencies is one of the significant success factors. In 2007 a project called electronic correspondent letter management system (e-CMS) began to standardize a data set in the domain of electronic official letters. In the project 30 ministerial departments involved to use and re-use the data set to achieve the seamless flow ofelectronic letter across those agencies. However in the project the data set is only in one domain ofinterest which is a letter. A new project had begun in 2008 to motivate more agencies to build further more standardized data sets from seven different domains. The finding is that the reusability of the data sets across various domain of interest is another significant success factor. In this project some data sets in the domains of education, labor, health, agriculture (livestock), research, governmental human resource and registrations had been built. Among the data sets from each domain, some data sets are very similar across different domain. To harmonize the similar data sets and reuse them ascommon data sets in different domain becomes significant. The common data sets are for examples; 'Person', 'Address', 'Education' and etc. The data set 'Person' appeared as 'Student' in education domain.It appeared as 'Labour' in labour domain and again appeared as 'Patient' in health domain. In this paper we illustrate that the reusability in those various domains increases the reusability across agencies which in turn enhances the seamless flow across government agencies. ER - TY - JOUR T1 - Interoperability Among Healthcare Organizations Acting as Certification Authorities A1 - Bourka, A A1 - Polemi, D A1 - Koutsouris, D Y1 - 2003/// KW - Algorithms KW - Automation KW - Cerebral Palsy KW - Certificate policies (CP) KW - Certificate policy (CP) KW - Certification KW - Computer Communication Networks KW - Computer Security KW - Confidentiality KW - Cross-certification KW - Database Management Systems KW - Decision Support Techniques KW - Decision making KW - Health Services Administration KW - Health care KW - Healthcare security KW - Information Management KW - Information analysis KW - Interinstitutional Relations KW - International Cooperation KW - Internet KW - Interoperability KW - Java programming language KW - Medical Records Systems, Computerized KW - Organizational Policy KW - Public key infrastructure (PKI) interoperability KW - Public policy KW - Regulatory compliance KW - Societies and institutions KW - Systems Integration KW - World Wide Web KW - article KW - certification KW - comparative study KW - computer network KW - computer security KW - confidentiality KW - data base KW - decision support system KW - evaluation KW - health service KW - information system KW - international cooperation KW - medical record KW - organization and management KW - policy KW - public relations KW - standard KW - system analysis JF - IEEE Transactions on Information Technology in Biomedicine VL - 7 IS - 4 SP - 364 EP - 377 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-1442264193&doi=10.1109%2FTITB.2003.823291&partnerID=40&md5=9e22d6d6c159855752eff8fa1c23f28e N1 - Cited By :6 Export Date: 10 September 2018 References: Arsenault, A., Turner, S., Internet X.509 public key infrastructure: Roadmap (2002) Internet Draft, , http://ieft.org/internet-drafts/drafts-ieft-pkix-roadmap-08.txt, KIX Working Group, IETF. [Online]; Housley, R., Ford, W., Polk, W., Solo, D., Internet X.509 public key infrastructure certificate and CRL profile (1999) IEFT RFC Standard, 2459. , http:www.ieft.org/rfc/rfc2459.txt, [Online]; (1994) Information Technology - Open Systems Interconnection - The Directory: Authentication Framework, , CCITT Rec. X.509/ISO/IEC Standard 9594-8; Harris, P., Hermans, J., Hilton, J., Hoeke, M., Hodgson, K., Koorn, R., (2002) Pki Usage Within User Organizations: An Examination of the Current and Future Use and Implementation of Pki Within the Ict User Community, , Eema, Security Interest Group. [online]; A Bridge CA for Europe's Public Administrations (2002) European Commission - Enterprise DG, Public Key Infrastructure for Closed User Groups Project (PKIUG), , http://europa.eu.int/ISPO/ida/, [Online]; X509 certificate policy for the healthcare PKI (2001) Federal Government, Tech. Rep. Version 0.3.1; National PKI Framework for Health, , http://secure.cihi.ca, Canadian Institute for Health Informatics (CIHI), CA. [Online]; (2000) PKI in Healthcare: Recommendations and Guidelines for Community Based Testing, , http://www.health.key.org, Healthkey [Online]; Bourka, A., Georgoulas, A., Polemi, D., Blobel, B., Pharow, P., Itkonen, P., Survey on current security practices and solutions in the field of regional healthcare information networks (2001) RESHAN Project, , Final Deliverable D.2.1; Information technology - Open systems interconnection - Security frameworks for open systems: Overview (1996) JTC1 ISO/IEC Standard 10181-1, , http://www.iso.org, [Online]; (1999) Data Encryption Standard (DES), , http://csrc.nist.gov/cryptval/cmvp.htm, FIPS PUB 46-3 standard. US Department of Commerce, NIST. [Online]; Rivest, R.L., Shamir, A., Adleman, L.M., On digital signatures and public key cryptosystems (1979) MIT Laboratory for Computer Science, USA, Tech. Rep., MIT-LCS-TR-212; Adams, C., Chain, P., Pinkas, D., Zuccherato, R., Internet X.509 public key infrastructure: Time stamp protocol (TSP) (2001) IETF RFC Standard, 3161. , http://www.ieft.org/rfc/rfc3161.txt, [Online]; Identification authentication in e-government (2002) White Paper, , eEurope smart Cards, Trailbrazer 2, European Commission; Blobel, B., (2002) Analysis, Design and Implementation of Secure and Interoperable Distributed Health Information Systems, , Amsterdam, The Netherlands: IOS Press; (2001) Cross Certification Guidelines, , http://secure.cihi.ca, Canadian institute for health informatics (CIHI), CA. [Online]; (2001) Cross Certification Methodology and Criteria, Tech. Document, , Treasury Board Secretariat of Canada, Government of Canada, Ottawa, Canada; Kardasiadou, Z., Blobel, B., Amberla, S., Legal and policy issues of pki adoption in health telematics applications in Greece (2001) RESHEN Project, , http://www.biomed.ntua.gr/reshen, Germany and Finland, Tech. Del. D.2.2, European Commission [Online]; Chokhani, S., Ford, W., Internet X.509 public key infrastructure certificate policy and certification practices framework (1999) IEFT RFC Standard, 2527. , http://www.ieft.org/rfc/rfc2527.txt, [Online]; (2000) Policy Requirements for Certification Authorities Issuing Qualified Certificates, , http://portal.etsi.org/sec/el-sign.asp, ETSI TS 101 456. [Online]; Louwerse, K., Allaert, F.A., Blobel, B., Barber, B., (2002) Security Standards for Healthcare, , Amsterdam, The Netherlands: IOS Press; Fraser, R., Healthcare PKI standards development 2001 Canadian Institute for Health Information Workshop, , Ottawa, Canada; (2001) Healthcare Informatics - Public Key Infrastructure, , ISO TS 17090 Parts 1-3; Healthcare certificate policy (2000) ASTM Standard E31.20, , http://www.cio.gov/fpkisc, [Online]; Bourka, A., Polemi, D., Koutsouris, D., An overview in healthcare information systems security 2001 MEDINFO Conference, , London, U.K; Directive 1999/93/EC of the european parliament and of the council of 13 December 1999 on a community framework for electronic signatures (2000) Official J., L 013, pp. 0012-0020. , Jan; Bourka, A., (2002) Advanced Public Key Infrastructure Services for Healthcare: Development of Secure Application for E-Healthcare Documents Communication - Implementation of Prototype Method for Automated Certificate Policies Compatibility Assessment, , Ph.D. dissertation, Dept. Elect. Comput. Eng., National Tech. Univ.Athens, Athens, Greece; (2000) Model Certificate Policy for a Healthcare PKI, , Tunitas Group; X.509 certificate policy for the federal bridge certification authority (FBCA) (2000) Federal PKI Task Force, USA, Tech. Rep. Version 1.9; EuroPKI certificate policy (2000) Tech. Report Version 1.1 (Draft 4), , http://www.europki.org, Computer and Network Security Group of Politecnico di Torino. [Online]; (2002) Network and Information Security: Proposal for a European Policy Approach, , European Commission, Communication of the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions; Asay, A., Brandt, C.S., Daniels, B., Greenwood, D., Larimer, J., Vincent III, W.T., (2000) Certification Authority of Rating and Trust (CARAT) Guidelines, , http://internet-council.nacha.org/Projects/default.html, National Automated Clearing House Association (NACHA), The Internet Council. [Online]; (2000) Health OCA Certificate Policy, , Baltimore Certificates Australia Pty Limited, Australia. [Online]; (2001) Healthcare OCA Gatekeeper Individual Accredited Healthcare Certificate Policy, , http://www.hesa.com.au, Heath Insurance Commission, Australia. [Online]; Model digital signature and confidentiality certificate policies for health PKI (2001) National PKI Framework for Health, , Canadian Institute for Health Informatics (CIHI), Canada. [Online]; Tiantaphyllou, E., (2002) Multi-criteria Decision-making Methods: A Comparative Study, , Dordrecht, The Netherlands: Kluwer; Bray, T., Paoli, J., Sperberg-Mcqueen, C.M., Maler, E., Extensible markup language (XML) 1.0 recommendation (Second Edition) (2000) XML Standard, , http://www.w3.org/TR/REC-xml, W3C. [Online]; Eastlake, D., Reagle, J., Solo, D., (2001) XML-signature Syntax and Processing IETF RFC Standard, 3075. , http://www.ietf.org/rfc/rfc3075.txt, [Online]; Imamura, T., Dillaway, B., (2002) XML Encryption Syntax and Processing W3C Candidate Recommendation, , http://www.w3.org/TR/xmlenc-core/, [Online]; (2001) Specification for XML DTD's in Healthcare, , http://www.openhealth.org/ASTM/, draft ASTM E31.25 standar [Online]; (1999) Health Level Seven XML Patient Record Architecture, HL7 SGML/XML SIG, , http://xml.cover-pages.prg/hl7PRA.html, [Online]; (2000) JBUILDER 5 Documentation, , BORLAND, Scotts Valley, CA; (2002) IBM XML SECURITY SUITE, , http://www.alphaworks.ibm.com, IBM, New York. [Online]; (2002) IAIK JCE 3.0., , http://jcewww.iaik.tu-graz.ac.at/products/jce, Graz Univ. Technol. Graz, Austria. [Online]; Improvement and modernization of the national health system, chapter a: Regional healthcare systems (2001) Official J. Govern. Greek Democ., 37 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - One of the main problems in public key infrastructures (PKI) is currently the lack of interoperability at international level, which is greatly dependent on the automation of the cross-certification procedure using certificate policies (CP). This paper addresses the aforementioned need by presenting a method for the automated development and comparison of CPs, with main emphasis on healthcare environments. The basic elements of this method include standardization of the CP content for healthcare, a prototype decision-making algorithm for CPs comparison, representation of CPs in extensible markup language, as well as a JAVA-based CP comparison tool. The final aim of the paper is to contribute toward the technical implementation of an on-line automated cross-certification service, yielding PKI interoperability and promoting information exchange between healthcare establishments. ER - TY - JOUR T1 - Data for Decision Making in Networked Health A1 - Bourret, C A1 - Salzano, G Y1 - 2006/// KW - Data reduction KW - Decision Making KW - Decision making KW - Developed Countries KW - Developing Countries KW - Health Care Costs KW - Health care KW - Health networked organizations KW - Information System KW - Information Systems KW - Information dissemination KW - Information sharing KW - Information system KW - Information technology KW - Interoperability KW - Societies and institutions KW - e-Health Information Systems JF - Data Science Journal VL - 5 SP - 64 EP - 78 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-33746650526&doi=10.2481%2Fdsj.5.64&partnerID=40&md5=dccdc32b338dfec506e4adc98c166c6c N1 - Cited By :2 Export Date: 10 September 2018 References: Homepage of American medical association AMA, , http://www.ama.org, n.d; Ammenwerth, E., Gräber, S., Hermann, G., Bürkle, T., König, J., Evaluation of health information systems - Problems and challenges (2003) International Journal of Medical Informatics, 71, pp. 125-135; Ammenwerth, E., Brender, J., Nykänen, P., Prokosch, H.A., Rigby, M., Talmon, J., Visions and strategies to improve evaluation of health information systems. Reflections and lessons based on the HIS-EVAL workshop in Innsbruck (2004) International Journal of Medical Informatics, 73, pp. 479-491; Benassi, A., Bravar, D., Carpeggiani, C., Macerata, A., Donato, L., SPERIGEST: An italian experience for telematic in-hospital health care (2002) Proceedings Telemedicine in Care Delivery, , TICD, Pise, Italy; Blendon, R.-J., DesRoches, C.M., Brodie, M., Benson, J.M., Rosen, A.B., Schneider, E., Altman, D.E., Steffenson, A.M., Patient safety. Views of practising physicians and the public on medical errors (2002) The New England Journal of Medicine, 347 (24), pp. 1933-1940; Boden, M., Braun, A., Cabrera, M., Constantelou, A., Da Costa, O., Karounou, V., Ligtvoet, A., Skulimowski, A.M., Aspects of eHealth (2004) The IPTS Report, , Special Issue, 81, Sevilla, Spain, Institute for Prospective Technological Studies; Bourret, C., Data concerns and challenges in health: Networks, information & communication systems and electronic records (2004) Data Science Journal, 3 (SEPTEMBER), pp. 96-113; Bourret, C., Salzano, G., Laurent, D., Data and cooperative work in Health Services: French specificities and comparisons with other countries (2003) Proceedings Systems Integration 2003, pp. 182-190. , Prague, Czech Republic; Bourret, C., La santé en réseaux (2003) Etudes: Revue de Culture Contemporaine, 3993, pp. 175-190. , Paris: Assas Editions; Burns, F., (1998) Information for Health. An Information Strategy for the Modern NHS 1998 - 2005. A National Strategy for Local Implementation, , London: NHS Executive; Homepage of commission d'accès à l'information du Québec CAI, , http://www.cai.gouv.qc.ca, n.d; Carré, D., Lacroix, J.-G., (2001) La Santé et les Autoroutes de l'Information. la Greffe Informatique, , Paris: L'Harmattan; Castells, M., (1996) The Rise of the Network Society, , Oxford, Blackwell Publishers; (2001) La Société en Réseaux (2nd Ed.), , Traduction française, Paris, France: Fayard; (2002) The Strategic Plan of CatSalut (Catalan Heath Service), , http://www10.gencat.net/catsalut/cat/coneix_quees_lin.htm, Retrieved September 15, 2005 from the CatSalut website; (1997) Healthcare Information System Architecture Part 1 (HISA) - Healthcare Middleware Layer, , http://www.tc251wgiv.nhs.uk/pages/pdf/cenp2967.pdf, CEN/TC251; Homepage of Canadian Health Network (CHN) - Réseau Canadien de la Santé (RCS) CHN, , http://www.canadian-health-network.ca, n.d; Homepage of Caisse Nationale d'Assurance Maladie des Travailleurs Salariés (CNAMTS) CNAMTS, , http://www.ameli.fr, n.d; Homepage of commission nationale de l'informatique et des libertés CNIL, , http://www.cnil.fr, n.d; Homepage of carte professionnelle de santé GIP CPS, , http://www.gip-cps.fr/uk/intro/index.html, n.d; Crisp, N., (2001) Shifting the Balance of Power Within the NHS. Securing Delivery, , London: Department of Health; Denning, P.J., The profession of Information Technology (IT) who are we ? (2001) Communications of the ACM, 44 (2), pp. 15-19; Homepage of DICOM DICOM, , http://medical.nema.org, n.d; Dranove, D., (2000) The Economic Evolution of American Health Care, , Princeton and Oxford: Princeton University Press; Homepage of electronic record development and implementation programme ERDIP, , http://www.nhsia.nhs.uk/erdip, (n.d.). Available from the NHS Information Authority website; Fieschi, M., (2003) Les Données du Patient Partagées: la Culture du Partage et de la Qualité des Informations pour Améliorer la Qualité des Soins, , http://www.sante.gouv.fr/htm/actu/fieschi/sommaire.htm, Paris. Retrieved September 15, 2005; Homepage of fédération nationale des observatoires régionaux de santé FNORS, , http://www.fnors.org, n.d; Gadrey, J., (2003) Socio-économie des Services, , Paris: Repères-La Découverte; Glouberman, S., Mintzberg, H., Managing the care of health and the cure of disease (2001) Health Care Management Review, pp. 56-84. , New York: Aspen Publishers; Homepage of groupement pour la modernisation du système d'information hospitalier GMSIH, , http://www.gmsih.fr/tiki-index.php, n.d; Government Reform Committee, , http://reform-house.gov/GovReform/Hearings/EventSingle.aspx?EventID=34864, Retrieved October 15, 2005; Grimson, J., Grimson, W., Hasselbring, W., The SI challenge in health care (2000) Communications of the ACM, 43 (6), pp. 49-55; Homepage of haute autorité de santé (high authority in health) Haute Autorité de Santé, , http://www.has-sante.fr, n.d; Homepage of health Scotland Health Scotland, , http://www.healthscotland.com/news/index.cfm, n.d; Hichney, A.M., Dean, D.L., Nunamaker, J.F., Establishing a foundation for collaborative scenario elicitation (1999) Database for Advances in Information Systems, 30 (3-4). , New York; Homepage of HL7 United States HL7, , http://www.hl7.org, n.d; Homepage of HL7 France - HPRIM HPRIM, , http://www.hprim.org, n.d; Home page of junta de andalucia Junta de Andalucia, , http://www.juntadeandalucia.es/salud/, n.d; Homepage of kaiser permanente Kaiser Permanente, , http://www.kaiserpermanente.org, n.d; Le Beux, P., Boullier, D., (2001) L'Information Médicale Numérique, , Paris, France: Ed. Hermes; Le Coadic, Y.F., (1999) La Science de l'Information, , Paris, France: PUF; Legifrance, , www.legifrance.gouv.fr/citoyen/jorf_nor.ow?numjo=MESX0100092L, Loi no 2002-303 du 4 mars 2002 relative aux Droits des malades et à la qualité du système de santé. Retrieved October 15, 2005 from the Legifrance web site; Legifrance, , http://www.legifrance.gouv.fr/WAspad/SardeUneRubriqueBase?num=41160000, Loi no 78-17 du 6 Janvier 1978 relative à l'Informatique, aux fichiers et aux libertés. Retrieved October 15, 2005 from the Legifrance web site; Lehalle, D., Réseaux de santé et dossier informatisé du patient: Ce qui va changer (2003) Le Quotidien du Médecin, , http://www.quotimed.com/specialites/index.cfm?fuseaction= viewarticle&DartIdx=144449, 25/04/2003, Retrieved September 15, 2005; (2005) Le Monde Informatique, 1056. , http://www.lemondeinformatique.fr, Paris, France, 13-19. Retrieved September 15, 2005; Lievre, P., (2002) Evaluer une Action Sociale, , Rennes, France: Ed. ENSP; Le salon de la médecine MEDEC 2005, , http://www.lemedec.com/presentation/index.asp, (n.d.), Paris, Retrieved October 15, 2005; Homepage of medline MEDLINE, , http://www.nlm.nih.gov/databases, (n.d.). Retrieved September 15, 2005 from United States National Library of Medicine National Institute of Health website; Miège, B., (2004) L'information-communication, Objet de Connaissance, , Brussels, Belgium: De Boeck; Homepage of ministère de la santé et de la protection sociale Ministère Santé, , http://www.sante.gouv.fr, (n.d.), France; Mintzberg, H., (2001) Le Management, Voyage au Cœur des Organisations, , Paris, France: Ed. d'Organisation; Morin, E., Le Moigne, J.-L., (2003) L'Intelligence de la Complexité, , Paris, France: L'Harmattan; Nakache, D., Decision for health service (2003) Proceedings ICYCS'2003 (7th International Conference for Young Computer Scientists), , Harbin, China; Homepage of national health service NHS, , http://www.nhs.uk, n.d; Homepage of NHS direct NHS Direct, , http://www.nhsdirect.nhs.uk/, n.d; Nunamaker Jr., J.-F., Briggs, R.O., De Vreede, G.-J., Sprague Jr., R.-H., Special issue: Enhancing organizations' intellectual bandwidth: The quest for fast and effective value creation (2001) Journal of Management Information Systems, 17 (3), pp. 3-8; (2004) Towards High-performing Health Systems, , http://www.oecd.org/document/58/0.2340.en_2649_201185_31786874_1_1_1_1, 00.html, Retrieved 15 October 2005 from OECD website; Health insurance portability and accountability act Office for Civil Liberties, , http://www.hhs.gov/ocr/hipaa, (n.d.). Retrieved October 15, 2005 from United States Department of Health & Human Resources website; Homepage of office of the national coordinator for health information technology ONC, , www.hhs.gov/healthit, n.d; Palier, B., (2005) La Réforme des Systèmes de Santé, , Paris: PUF; Salzano, G., Bourret, C., Healthcare networks services towards patients and large public: Methodological and engineering issues (2003) Proceedings Medical Informatics Europe, pp. 492-497. , France: Saint-Malo; Salzano, G., Integration methodology for heterogeneous databases (2002) Heterogeneous Information Exchange and Organizational Hubs, , Bestougeff, H., Dubois, J.E., Thurasingsham, B. (Eds.), Dordrecht, The Netherlands: Kluwer Academic Publishers; Salzano, G., Bourret, C., Interoperability among medical applications (2002) Proceedings Healthcom.2002, 4th International Workshop on Enterprise Networking and Computing in Healthcare Industry, , Nancy, France; Homepage of Scottish health on the net SHOW, , http://www.show.scot.nhs.uk/organisations/orgindex.htm, n.d; Sicotte, C., Moreault, M.-P., Lehoux, P., Farand, L., (2004) Réseaux en Convergence: Télécommunications de Données Cliniques et Réseaux Intégrés de Soins de la Région Socio-sanitaire de Laval, , http:/www.gris.umontreal.ca/publist.asp, Groupe de Recherche Interdisciplinaire en Santé (GRIS), Université de Montréal; Silber, D., (2003) The Case for EHealth, , The European Commission's conference on eHealth, Belgium: Brussels; Shortell, S.M., Gillies, R.R., Anderson, D.A., Morgan Erickson, K., Mitchell, G.B., (1996) Remaking Health Care in America. Building Organized Delivery Systems, , San Francisco: Jossey-Bass Publishers; Stefanacci, R.G., Reducing medical mistakes with technology (2001) Caring for the Ages, 2 (12), pp. 28-30. , American Medical Director Association; Stiglitz, J.E., (2003) The Roaring Nineties, , New York: W.W. Norton; Tsiknakis, M., Katehakis, D.G., Orphanoudakis, S.C., An open, component-based information infrastructure for integrated health information networks (2002) International Journal of Medical Informatics, 68, pp. 3-26; (2005) Summary of Nationwide Health Information Network (NHIN) Request for Information (RFI) Responses, , http://www.hhs.gov/healthit/rfisummaryreport.pdf, Retrieved October 15, 2005 from the U.S. Department of Health and Human Services, Office of the National Coordinator for Health Information Technology web site; Walker, J., Pan, E., Johnston, D., Adler-Milstein, J., Bates, D.W., Middleton, B., The value of health care information exchange and interoperability: There is a business case to be made for spending money on a fully standardized nationwide system (2005) Health Affairs: Web Exclusive, , http://www.content.healthaffairs.org/cgi/reprint/hlthaff.w5.10v1; Wang, R.Y., Total Data Quality Management (TDQM) (1998) Communications of the ACM, 41, pp. 58-65; Wennberg, J.E., Fisher, E.S., Skinner, J.S., Geography and the debate, over medicare reform (2002) Health Affairs: Web Exclusive, , http://www.kaiseredu.org/SyllabusLibrary/3707_1.pdf; Home page of the world wide web consortium World Wide Web Consortium, , http://www.w3c.org/, n.d RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Today's developed countries are networked societies, with strong specificities in the Health field. Health costs have strongly increased. Indeed, governments, local powers, public and private health or insurance organizations face difficult choices: they need the most specific and valuable data available. Data for Decision Making in Networked Health is necessary at 3 levels: between patients and physicians and within the organizations (micro), within the organizations (meso) and in regional powers or governments (macro) and with 3 major content dimensions: quality, ethics, economics (effectiveness). We point out some specific tools of e-Health Information Systems: EHR (Electronic Health Record), portals and call centers. Then we analyze the main issues about data for Decision Making in Networked Health: information sharing, coordination and evaluation. Lastly we use an Information System perspective to analyze ways of improving interoperability at the core of each context, and of advancing from one context to another. ER - TY - JOUR T1 - A Malaria Analytics Framework to Support Evolution and Interoperability of Global Health Surveillance Systems A1 - Brenas, J H A1 - Al-Manir, M S A1 - Baker, C J O A1 - Shaban-Nejad, A Y1 - 2017/// KW - Cause of Death KW - Change management KW - Decision Making KW - Decision making KW - Design and Development KW - Diseases KW - Dynamic changes KW - Electronic data interchange KW - Government Agencies KW - Government agencies KW - Graph Transformation KW - Informed decision KW - Interoperability KW - Knowledge sources KW - Malaria KW - Malaria control KW - Monitoring KW - Semantic interoperability KW - Semantics KW - Uganda KW - Web services KW - change management KW - graph transformation KW - malaria surveillance KW - semantics KW - web services JF - IEEE Access VL - 5 SP - 21605 EP - 21619 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031795111&doi=10.1109%2FACCESS.2017.2761232&partnerID=40&md5=efe9c1b8417a6c5b3beab8c316ce475b L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Brenas et al. - 2017 - A Malaria Analytics Framework to Support Evolution and Interoperability of Global Health Surveillance Systems(2).pdf N1 - Cited By :3 Export Date: 10 September 2018 References: (2015) The Top 10 Causes of Death, , www.who.int/mediacentre/factsheets/fs310/en/index1.html, World Health Organisation Accessed: Jun. 28, 2017; (2016) World Malaria Report, , WHO, Geneva, Switzerland, 2016; Awash, S., Spielman, B., Tozan, A., Schapira, Y., Teklehaimanot, A., Coming to grips with malaria in the new millennium: Un millennium project task force on HIV/AIDS (2005) Malaria, TB, and Access to Essen-tial Medicines Working Group on Malaria, , 1st ed. Geneva, Switzerland: Earthscan Publications, Ltd; Bass, C., Williamson, M.S., Wilding, C.S., Donnelly, M.J., Field, L.M., Identification of the main malaria vectors in the Anopheles gambiae species complex using a TaqMan real-time PCR assay (2007) Malaria J, 6, p. 155. , http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2213665/, Nov; McMichael, A.J., (2003) Climate Change and Human Health-Risks and Responses, , Geneva, Switzerland: WHO; Sachs, J., Malaney, P., The economic and social burden of malaria (2002) Nature, 415 (6872), pp. 680-685. , http://dx.doi.org/10.1038/415680a; IPCC third assessment report (2001) Intergovernmental Panel Climate Change, Tech. Rep; Notifiable Diseases Surveillance System (NNDSS), Data Collection and Reporting, , https://wwwn.cdc.gov/nndss/data-collection.html, Office of Public Health Scientific Services (OPHSS). National. Accessed: Aug. 2, 2017; Liu, J., Yang, B., Cheung, W.K., Yang, G., Malaria transmission modelling: A network perspective (2012) Infectious Diseases Poverty, 1 (1), p. 11. , http://dx.doi.org/10.1186/2049-9957-1-11, Nov; (2012) Disease Surveillance for Malaria Control: An Operational Manual, , https://apps.who.int/iris/bitstream/10665/44851/1/9789241503341_eng.pdf?ua=1, World Health Organization Accessed: Sep. 14, 2017; Zinszer, K., Integrated disease surveillance to reduce data fragmentation An application to malaria control (2015) Online J. Public Health Informat, 7 (1), p. e181. , http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4512354/; Africa Health Observatory and Real-time Strategic Information Sys-tem, , http://www.afro.who.int/en/ghana/country-programmes/4989-aho-a-rsis.html, Accessed: Jun. 27, 2017; Coconut Surveillance: Open-Source Mobile Tool Designed to Take on Malaria, Other Infectious Diseases, , https://www.rti.org/impact/coconutsurveillance, RTI International. Accessed: Sep. 14, 2017; Eeshan, K., Performance Evaluation of Zanzibar's Malaria Case Noti-fication (MCN) System: The Assessment of Timeliness and Stake-holder Interaction, , https://dukespace.lib.duke.edu/dspace/handle/10161/10026, Accessed: Sep. 14, 2017; Hsiang, M.S., Surveillance for malaria elimination in Swaziland: A national cross-sectional study using pooled PCR and serology (2012) PLoS ONE, 7 (1), p. e29550; Guintran, J.-O., Delacollette, C., Trigg, P., Systems for the early detection of malaria epidemics in Africa: An analysis of current practices and future priorities (2006) World Health Org., Geneva, Switzerland, Tech. Rep. WHO/HTM/MAL/, 1115, p. 2006; Ohrt, C., Roberts, K.W., Sturrock, H.J.W., Wegbreit, J., Lee, B.Y., Gosling, R.D., Information systems to support surveillance for malaria elimination (2015) Amer. J. Tropical Med. Hygiene, 93 (1), pp. 145-152. , Jul; Le Sueur, D., An atlas of malaria in Africa (1997) Africa Health, 19 (2), pp. 23-24. , Jan; Mapping MAlaria Risk in Africa, , http://www.mara-database.org//login.html, Accessed: Jul. 2, 2017; VecNet, , https://dw.vecnet.org/datawarehouse/lookuptables/, Accessed: Jul. 2, 2017; (2013) Global Malaria Mapper World Health Organisation, , www.who.int/malaria/publications/world_malaria_report/global_malaria_mapper/en/, Accessed: Jun. 27, 2017; Global Malaria Mapper, , http://www.worldmalariareport.org/, Accessed: Jul. 2, 2017; Hay, S.I., Snow, R.W., The malaria atlas project: Developing global maps of malaria risk (2006) PLoS Med, 3 (12), pp. 1-5. , https://doi.org/10.1371/journal.pmed.0030473; The Malaria Atlas Project, , http://www.map.ox.ac.uk/, Accessed: Jul. 2, 2017; The USAID Measure DHS Website, Data Downloads, , http://www.measuredhs.com/Data/, Accessed: Jun. 27, 2017; Lawson, D., VectorBase: A home for invertebrate vectors of human pathogens (2007) Nucl. Acids Res, 35, pp. D503-D505. , Jan; VectorBase, , https://www.vectorbase.org/, Accessed: Jun. 2, 2017; The DHIS 2 Web Site, , https://www.dhis2.org/, Accessed: Jun. 27, 2017; Lozano-Fuentes, S., Bandyopadhyay, A., Cowell, L.G., Goldfain, A., Eisen, L., Ontology for vector surveillance and management (2013) J. Med. Entomol, 50 (1), pp. 1-14. , Jan; Topalis, P., Mitraka, E., Dritsou, V., Dialynas, E., Louis, C., IDOMAL: The malaria ontology revisited (2013) J. Biomed. Semantics, 4 (1), p. 16. , http://dx.doi.org/10.1186/2041-1480-4-16, Sep; Malaria Ontology, , https://bioportal.bioontology.org/ontologies/IDOMAL, Accessed: Jul. 2, 2017; Dialynas, E., Topalis, P., Vontas, J., Louis, C., MIRO and IRbase: IT tools for the epidemiological monitoring of insecticide resistance in mosquito disease vectors (2009) PLoS Neglected Tropical Diseases, 3 (6), pp. 1-9. , https://doi.org/10.1371/journal.pntd.0000465; Mosquito Insecticide Resistance Ontology, , https://bioportal.bioontology.org/ontologies/MIRO, Accessed: Jul. 2, 2017; Freifeld, C.C., Mandl, K.D., Reis, B.Y., Brownstein, J.S., HealthMap: Global infectious disease monitoring through automated classification and visualization of Internet media reports (2008) J. Amer. Med. Inf. Assoc, 15 (2), pp. 150-157. , Mar./Apr; HealthMap, , https://www.healthmap.org/, Accessed: Jul. 2, 2017; The World Wide Web Consortium (W3C), , https://www.w3.org, Accessed: Jul. 2, 2017 World Wide Web Consortium; HyperText Transfer Protocol, , https://www.w3.org/Protocols/, Accessed: Jul. 2, 2017; Ressource Description Framework, , https://www.w3.org/2001/sw/wiki/RDF, Accessed: Jul. 2, 2017; Web Ontology Language, , https://www.w3.org/2001/sw/wiki/OWL, Accessed: Jul. 2, 2017; SPARQL Query Language for RDF, , https://www.w3.org/TR/rdf-sparql-query/, Accessed: Jul. 2, 2017; Wilkinson, M.D., Vandervalk, B., McCarthy, L., The semantic automated discovery and integration (SADI) Web service design-pattern, API and reference implementation (2011) J. Biomed. Semantics, 2 (1), p. 8. , http://dx.doi.org/10.1186/2041-1480-2-8; Vandervalk, B.P., McCarthy, E.L., Wilkinson, D.M., (2009) SHARE: A Seman-tic Web Query Engine for Bioinformatics, pp. 367-369. , https://doi.org/10.1007/978-3-642-10871-6-27, Berlin, Germany: Springer; HYDRA, , http://ipsnp.com/hydra/, Accessed:Oct.1,2017; Riazanov, A., Semantic querying of relational data for clinical intelligence: A semanticWeb services-based approach (2013) J. Biomed. Semantics, 4 (1), p. 9. , Mar; Wolstencroft, K., The myGrid ontology: Bioinformatics service discovery (2007) Int. J. Bioinf. Res. Appl, 3 (3), pp. 303-325. , https://doi.org/10.1504/IJBRA.2007.015005; Boley, H., Kifer, M., RIF Basic Logic Dialect (Second Edi-tion), , https://www.w3.org/TR/2013/REC-rif-bld-20130205/, Accessed: Jul. 2, 2017; Boley, H., (2011) A RIF-Style Semantics for RuleML-Integrated Positional-Slotted, Object-Applicative Rules, pp. 194-211. , http://dx.doi.org/10.1007/978-3-642-22546-8-16, Berlin, Germany: Springer; Haarslev, V., Hidde, K., Möller, R., Wessel, M., The RacerPro knowledge representation and reasoning system (2012) Semantic Web J, 3 (3), pp. 267-277; Musen, M.A., The Protégé project: A look back and a look forward (2015) AI Matters, 1 (4), pp. 4-12. , http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883684/; Al Manir, M.S., Riazanov, A., Boley, H., Klein, A., Baker, C.J.O., Valet SADI: Provisioning SADI Web services for semantic querying of relational databases (2016) Proc. 20th Int. Database Eng. Appl. Symp, pp. 248-255. , http://doi.acm.org/10.1145/2938503.2938543, New York, NY, USA; Heckel, R., Graph transformation in a nutshell (2006) Electron. Notes Theor. Comput. Sci, 148 (1), pp. 187-198. , http://www.sciencedirect.com/science/article/pii/S157106610600048X; Minas, M., Schneider, H.J., (2010) Graph Transformation by Computational Category Theory, pp. 33-58. , http://dx.doi.org/10.1007/978-3-642-17322-6-3, Berlin, Germany: Springer; Echahed, R., Inductively sequential term-graph rewrite systems (2008) Proc. 4th Int. Conf. Graph Transf. (ICGT 5214, pp. 84-98; Brenas, J.H., Echahed, R., Strecker, M., Proving correctness of logically decorated graph rewriting systems (2016) Proc. 1st Int. Conf. Formal Struct. Comput. Deduction (FSCD), 15, pp. 14-18. , http://dx.doi.org/10.4230/LIPIcs.FSCD.2016.14, Jun; De Virgilio, R., Maccioni, A., Torlone, R., Converting relational to graph databases (2013) Proc. 1st Int. Workshop Graph Data Manage, p. 1. , http://doi.acm.org/10.1145/2484425.2484426, 1 1 6; Brenas, J.H., Echahed, R., Strecker, M., C2PDLS: A combination of combinatory and converse PDL with substitutions (2017) Proc. SCSS, Gammarth, Tunisia, pp. 29-41. , http://www.easychair.org/publications/paper/C2PDLS_A_Combination_of_Combinatory_and_Converse_PDL_with-Substitutions; Areces, C., Ten Cate, B., Hybrid logics (2007) Studies in Logic and Practical Reasoning, 3, pp. 821-868. , Amsterdam, The Netherlands: Elsevier; Courcelle, B., The monadic second-order logic of graphs. I. Recognizable sets of finite graphs (1990) Inf. Comput, 85 (1), pp. 12-75. , http://dx.doi.org/10.1016/0890-5401(90)90043-H; Balbiani, P., Echahed, R., Herzig, A., A dynamic logic for termgraph rewriting (2010) Proc. 5th Int. Conf. Graph Transf. (ICGT 6372, pp. 59-74; Brenas, J.H., Echahed, R., Strecker, M., Ensuring correctness of model transformations while remaining decidable (2016) Proc. 13th Int. Colloquium Theor. Aspects Comput. (ICTAC, pp. 315-332. , http://dx.doi.org/10.1007/978-3-319-46750-4-18; VectorBase CV, , www.vectorbase.org/downloadinfo/ontologyvbcv0162017-06obogz, Accessed: Jul. 2, 2017; ENVironment Ontology, , https://bioportal.bioontology.org/ontologies/ENVO, Accessed: Jul. 2, 2017; Brenas, J.H., Al-Manir, M.S., Baker, C.J.O., Shaban-Nejad, A., Change management dashboard for the SIEMA global surveillance infrastructure (2017) Proc. Int. Semantic Web Conf, pp. 1-4; Bienvenu, M., Bourgaux, C., Goasdoué, F., Query-driven repairing of inconsistent DL-lite knowledge bases (extended abstract) (2016) Proc. 29th Int.Workshop Description Logics, pp. 1-4. , http://ceur-ws.org/Vol-1577/paper_5.pdf, Apr; Holsti, K.J., (1998) The Problem of Change in International Relations Theory, , Vancouver, BC, Canada: Univ. British Columbia; Shaban-Nejad, A., Haarslev, V., (2009) Bio-Medical Ontologies Maintenance and Change Management, pp. 143-168. , https://doi.org/10.1007/978-3-642-02193-0-6, Berlin, Germany: Springer RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Malaria is a leading cause of death in Africa. Many organizations, NGO's, and government agencies are collaborating to prevent, control, and eliminate malaria. In order to succeed in these shared goals, an integrated, consistent knowledge source to empower informed decision-making is required. Malaria surveillance is currently performed using dynamic, interconnected, systems which require rapid data exchange between different platforms. An important challenge these systems must overcome is the occurrence of dynamic changes in one or more interacting components, which can lead to inconsistencies and mismatches between components of the infrastructure. In this paper, we present our efforts toward the design and development of the semantic interoperability and evolution for malaria analytics platform, with the goal of improving data and semantic interoperability for dynamic malaria surveillance and to support the integration of data across multiple scales. The long term target is to deliver transparent and scalable tools for decision making for malaria elimination. Our analysis is focused on sentinel sites in selected African countries, including Uganda and Gabon. © 2017 IEEE. ER - TY - CONF T1 - A change management dashboard for the SIEMA malaria surveillance infrastructure A1 - Brenas, J H A1 - Al-Manir, M S A1 - Baker, C J O A1 - Shaban-Nejad, A Y1 - 2017/// KW - Cause of Death KW - Change management KW - Data access KW - Data-sources KW - Developing Countries KW - Developing countries KW - Diseases KW - Infectious disease KW - Low incomes KW - Semantic Web KW - Semantic metadata KW - Web services KW - World Health Organization VL - 1963 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033493474&partnerID=40&md5=b7e9a5ab0d1bf9d5f8cfbf892620f7c4 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Brenas et al. - 2017 - A change management dashboard for the SIEMA malaria surveillance infrastructure.pdf N1 - Export Date: 10 September 2018 References: (2015) The Top 10 Causes of Death, , WHO; (2016) World Malaria Report 2016. Technical Report, , World Health Organization; Wilkinson, M.D., Vanderwalk, B., McCarthy, L., The semantic automated discovery and integration (SADI) web service design-pattern, api and reference implementation (2011) Journal of Biomedical Semantics, 2 (1), p. 8; Topalis, P., Mitraka, E., Dritsou, V., Dialynas, E., Louis, C., IDOMAL: The malaria ontology revisited (2013) Journal of Biomedical Semantics, pp. 4-16; Shaban-Nejad, A., Haarslev, V., Managing changes in distributed biomedical ontologies using hierarchical distributed graph transformation (2015) International Journal of Data Mining and Bioinformatics, 11 (1), pp. 53-83; Vanderwalk, B.P., McCarthy, E.L., Wilkinson, M.D., (2009) SHARE: A Semantic Web Query Engine for Bioinformatics, pp. 367-369. , Springer Berlin Heidelberg, Berlin, Heidelberg; Al Manir, M.S., Riazanov, A., Boley, H., Klein, A., Baker, C.J., Valet sadi: Provisioning sadi web services for semantic querying of relational databases (2016) Proc. of IDEAS'16, pp. 248-255. , New York, NY, USA, ACM; Gonçalves, R., Parsia, P., Sattler, U., Ecco: A hybrid diff tool for OWL 2 ontologies (2012) Proc. of OWLED; Liquibase: Source Control for Your Database, , http://www.liquibase.org RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Malaria is an infectious disease that remains a major cause of death in low-income developing countries. The World Health Organization (WHO) has set a target for its eradication by 2030. Among the issues that will have to be solved to achieve this goal is interoperability between the various malaria data sources. This can be achieved through the adoption of semantic web service infrastructure to provide access to the data while abstracting its structure. Given that data sources, semantic metadata descriptions and ontologies evolve over time, it remains a challenge to propagate changes, ensuring services continue to be discoverable, while at the same time keep the services operational. We propose a dashboard to detect, identify, and classify changes based on their likely functional impact on data access, and propose steps to maintain infrastructure, either rebuilding or retiring services from a registry. ER - TY - JOUR T1 - Exploring semantic data federation to enable malaria surveillance queries A1 - Brenas, Jon Haël A1 - Al Manir, Mohammad Sadnan A1 - Zinszer, Kate A1 - Baker, Christopher J.O. A1 - Shaban-Nejad, Arash Y1 - 2018/// KW - Distributed data KW - Interoperability KW - Malaria analytics KW - Malaria surveillance KW - Web services JF - Studies in Health Technology and Informatics VL - 247 SP - 6 EP - 10 SN - 9781614998518 DO - 10.3233/978-1-61499-852-5-6 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Brenas et al. - 2018 - Exploring semantic data federation to enable malaria surveillance queries.pdf N2 - Malaria is an infectious disease affecting people across tropical countries. In order to devise efficient interventions, surveillance experts need to be able to answer increasingly complex queries integrating information coming from repositories distributed all over the globe. This, in turn, requires extraordinary coding abilities that cannot be expected from non-technical surveillance experts. In this paper, we present a deployment of Semantic Automated Discovery and Integration (SADI) Web services for the federation and querying of malaria data. More than 10 services were created to answer an example query requiring data coming from various sources. Our method assists surveillance experts in formulating their queries and gaining access to the answers they need. ER - TY - JOUR T1 - Advancing patient-centered Pediatric care through health information exchange: update from the American health information community personalized health care workgroup A1 - Brinner, K A A1 - Downing, G J Y1 - 2009/// KW - Child KW - Child Health Services KW - Clinical decision support KW - Community Health Services KW - Consumer Health Information KW - Cooperative Behavior KW - Electronic health record KW - Electronics, Medical KW - Family health history KW - Genetic testing KW - Health information technology KW - Humans KW - Interprofessional Relations KW - Newborn screening KW - Patient-Centered Care KW - Pediatrics KW - Personalized health care KW - United States KW - Use case KW - article KW - child KW - child health care KW - community care KW - consumer health information KW - cooperation KW - electronic medical record KW - electronics KW - genome analysis KW - health care organization KW - health care planning KW - health care quality KW - human KW - information dissemination KW - information processing KW - information service KW - instrumentation KW - legal aspect KW - medical information system KW - newborn screening KW - organization and management KW - patient care KW - pediatrics KW - practice guideline KW - priority journal KW - public relations JF - Pediatrics VL - 123 SP - S122 EP - S124 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-58849133425&doi=10.1542%2Fpeds.2008-1755N&partnerID=40&md5=d4dd87f65e981bc1e73932ffd819a396 N1 - Cited By :6 Export Date: 10 September 2018 References: McDonald, C.J., The barriers to electronic medical record systems and how to overcome them (1997) J Am Med Inform Assoc, 4 (3), pp. 213-221; Deverka, P.A., Doksum, T., Carlson, R.J., Integrating molecular medicine into the US health-care system: Opportunities, barriers, and policy challenges (2007) Clin Pharmacol Ther, 82 (4), pp. 427-434; Personalized health care, , www.hhs.gov/myhealthcare, Available at:, Accessed November 5, 2007; Personalized health care: Opportunities, pathways, , www.hhs.gov/myhealthcare/news/presonalized-healthcare-9-2007.html, resources. Available at:, Accessed November 4, 2007; www.medicalhomeinfo.org/Joint%20Statement.pdf, American Academy of Family Physicians; American Academy of Pediatrics; American College of Physicians; American Osteopathic Association. Joint principles of the patient-centered medical home. Available at:, Accessed December 5, 2007; American Health Information Community, , www.hhs.gov/healthit/community/background, Available at:, Accessed November 5, 2007; Personalized Health Care Workgroup: Genetic/genomic test priority area, , www.hhs.gov/healthit/ahic/materials/06-07/phc/matrix.html, Available at:, Accessed November 30, 2007; Osheroff, J., Teich, J., Middleton, B., Steen, E., Wright, A., Detmer, D., A roadmap for national action on clinical decision support (2007) J Am Med Inform Assoc, 14 (2), pp. 141-145 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Personalized Health Care Workgroup of the American Health Information Community was formed to foster a broad, community-based approach to facilitate the incorporation of interoperable, clinically useful, genetic/genomic information and analytical tools into electronic health records, to support clinical decision-making. The Personalized Health Care Workgroup has developed a series of use cases that outline the informational needs of multiple stakeholders (eg, patients, clinicians, organizations, and systems) and describe the information systems necessary to connect these stakeholders at multiple levels. These use case scenarios offer a guide for standardized data elements and architecture that enable interoperability (content sharing) among different formats of patient electronic health records. Copyright © 2009 by the American Academy of Pediatrics. ER - TY - JOUR T1 - Public Health Information Network--improving early detection by using a standards-based approach to connecting public health and clinical medicine. A1 - Broome, C V A1 - Loonsk, J Y1 - 2004/// KW - Bioterrorism KW - Clinical Medicine KW - Communicable Diseases, Emerging KW - Disease Outbreaks KW - Humans KW - Population Surveillance KW - Public Health Administration KW - Public Health Informatics KW - article KW - biological warfare KW - clinical medicine KW - communicable disease KW - epidemic KW - health survey KW - human KW - medical informatics KW - methodology KW - public health service JF - MMWR. Morbidity and mortality weekly report VL - 53 SP - 199 EP - 202 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-13844256836&partnerID=40&md5=6deac5cbac9ce4673f2d350ec5b19013 N1 - Cited By :9 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public health departments and their clinical partners are moving ahead rapidly to implement systems for early detection of disease outbreaks. In the urgency to develop useful early detection systems, information systems must adhere to certain standards to facilitate sustainable, real-time delivery of important data and to make data available to the public health partners who verify, investigate, and respond to outbreaks. To ensure this crucial interoperability, all information systems supported by federal funding for state and local preparedness capacity are required to adhere to the Public Health Information Network standards. ER - TY - JOUR T1 - Information Sharing Performance Management - A Semantic Interoperability Assessment in the Maritime Surveillance Domain A1 - Bryton, Fernando Sérgio A1 - Marín, Jesús E Martínez A1 - Ortega, Olga Delgado Y1 - 2015/// JF - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management IS - Ise SP - 382 EP - 393 DO - 10.5220/0005712003820393 UR - http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0005712003820393 ER - TY - JOUR T1 - Data federation in the Biomedical Informatics Research Network: tools for semantic annotation and query of distributed multiscale brain data. A1 - Bug, William A1 - Astahkov, Vadim A1 - Boline, Jyl A1 - Fennema-Notestine, Christine A1 - Grethe, Jeffrey S A1 - Gupta, Amarnath A1 - Kennedy, David N A1 - Rubin, Daniel L A1 - Sanders, Brian A1 - Turner, Jessica A A1 - Martone, Maryann E Y1 - 2008/11// JF - AMIA ... Annual Symposium proceedings. AMIA Symposium SP - 1220 EP - 1220 UR - http://www.ncbi.nlm.nih.gov/pubmed/18999211 N2 - The broadly defined mission of the Biomedical Informatics Research Network (BIRN, www.nbirn.net) is to better understand the causes human disease and the specific ways in which animal models inform that understanding. To construct the community-wide infrastructure for gathering, organizing and managing this knowledge, BIRN is developing a federated architecture for linking multiple databases across sites contributing data and knowledge. Navigating across these distributed data sources requires a shared semantic scheme and supporting software framework to actively link the disparate repositories. At the core of this knowledge organization is BIRNLex, a formally-represented ontology facilitating data exchange. Source curators enable database interoperability by mapping their schema and data to BIRNLex semantic classes thereby providing a means to cast BIRNLex-based queries against specific data sources in the federation. We will illustrate use of the source registration, term mapping, and query tools. ER - TY - CONF T1 - Semantic interoperation and electronic health records: Context sensitive mapping from SNOMED CT to ICD-10 A1 - Campbell, J R A1 - Brear, H A1 - Scichilone, R A1 - White, S A1 - Giannangelo, K A1 - Carlsen, B A1 - Solbrig, H A1 - Fung, K W Y1 - 2013/// KW - Artificial Intelligence KW - Electronic Health Records KW - ICD-10 KW - ICD-10-CM KW - International Classification of Diseases KW - Interoperation KW - Medical Record Linkage KW - Natural Language Processing KW - Pattern Recognition, Automated KW - SNOMED CT KW - Semantics KW - Systematized Nomenclature of Medicine KW - Terminology as Topic KW - Translating KW - artificial intelligence KW - automated pattern recognition KW - classification KW - data translation KW - electronic medical record KW - knowledge representation KW - mapping terminology KW - medical record KW - natural language processing KW - nomenclature KW - procedures KW - semantics KW - translating (language) VL - 192 IS - 1 SP - 603 EP - 607 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894309346&doi=10.3233%2F978-1-61499-289-9-603&partnerID=40&md5=fb8e7599d4de2834a3fc0a8cbe4c1402 N1 - Cited By :6 Export Date: 10 September 2018 References: Cimino, J.J., Review paper: Coding systems in health care (1996) Methods Inf Medicine, 35 (4-5), pp. 273-284; Campbell, J.R., Carpenter, P., Sneiderman, C., Cohn, S., Chute, C.J., Warren, J., Phase ii evaluation of coding schemes: Completeness, taxonomy, mapping, definitions and clarity (1997) JAMIA, 4 (3), pp. 238-251; Giannangelo, K., Millar, J., Mapping snomed ct to icd-10 (2012) Stud Health Technol Inform, 180, pp. 83-87; (2012) Mapping SNOMED CT to ICD-10: Technical Specifications, , http://www.ihtsdo.org/develop/mapping/icd10/, Copenhagen Denmark; http://www.nlm.nih.gov/research/umls/Snomed/core_subset.html; Fung, K.W., McDonald, C., Srinivasan, S., The umls-core project: A study of the problem list terminologies used in large healthcare institutions (2010) J Am Med Inform Assoc, 17 (6), pp. 675-680. , Nov 1; http://www.connectingforhealth.nhs.uk/systemsandservices/data/ clinicalcoding/crossmap; Crossmap: SNOMED CT to ICD-10 Release Notes, , http://www.ihtsdo.org/develop/mapping/icd10/; https://www.ihtsdoregistration.nss.cfh.nhs.uk/salsa/user/guest/group/0/ pack/4/subpack/56/releases; Mapping SNOMED CT to ICD-10-CM: Technical Specifications, , http://www.nlm.nih.gov/research/umls/mapping_projects/ snomedct_to_icd10cm_tech_spec_20120614.pdf; Fung, K.W., Xu, J., Synergism between the mapping projects from snomed ct to icd-10 and icd-10-cm (2012) AMIA Annu Symp Proc, pp. 218-227; http://www.nlm.nih.gov/research/umls/mapping_projects/ snomedct_to_icd10cm.html; I-MAGIC Browser, , http://imagic.nlm.nih.gov/imagic/code/map RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - An important case for successful deployment of a lifetime electronic health record is reuse of clinical data from the electronic health record (EHR) for epidemiology, reimbursement, and research. We report a collaboration between the IHTSDO and the WHO to develop knowledge-based tools supporting translation of data from SNOMED CT to the ICD-10 classification. These tools have been vetted by an international community and are available for system vendors to enhance the interoperability of their products. The maps we created are also informing the development of the next generation of classifications which will employ a common ontology base between SNOMED CT and ICD-11 to promote interoperability. © 2013 IMIA and IOS Press. ER - TY - JOUR T1 - A computable pathology report for precision medicine: Extending an observables ontology unifying SNOMED CT and LOINC A1 - Campbell, W S A1 - Karlsson, D A1 - Vreeman, D J A1 - Lazenby, A J A1 - Talmon, G A A1 - Campbell, J R Y1 - 2018/// KW - Breast Neoplasms KW - Cancer synoptic reports KW - Interoperability KW - LOINC KW - Logical Observation Identifiers Names and Codes KW - Medical Informatics KW - Ontology KW - SNOMED CT KW - Systematized Nomenclature of Medicine JF - Journal of the American Medical Informatics Association VL - 25 IS - 3 SP - 259 EP - 266 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043326578&doi=10.1093%2Fjamia%2Focx097&partnerID=40&md5=d89d1f0a0434f0f29f4daad0fa79c317 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Campbell et al. - 2018 - A computable pathology report for precision medicine Extending an observables ontology unifying SNOMED CT and L.pdf N1 - Export Date: 10 September 2018 References: Srigley, J.R., McGowan, T., Maclean, A., Standardized synoptic cancer pathology reporting: A population-based approach (2009) J Surg Oncol, 99 (8), pp. 517-524; Markel, S.F., Hirsch, S.D., Synoptic surgical pathology reporting (1991) Hum Pathol, 22 (8), pp. 807-810; (2009) An Overview of the College of American Pathologists Cancer Checklist, , www.cap.org/apps/docs/committees/cancer/cancer_protocols/Overview_CAP_Cancer_Checlkists_090115.pdf, Updated, Accessed July 10, 2017; (2016) Cancer Datasets and Tissue Pathways, , www.rcpath.org/resource-library-homepage/publications/cancer-datasets.html, Updated, Accessed July 10, 2017; (2013) RCPA Cancer Protocols, , www.rcpa.edu.au/Library/Practising-Pathology/Structured-Pathology-Reporting-of-Cancer/Cancer-Protocols, Updated, Accessed July 10, 2017; (2016) International Collaborative on Cancer Reporting/Datasets, , www.iccr-cancer.org/datasets, Updated, Accessed July 10, 2017; (2015) ACS Commission on Cancer Releases Updated Standards Manual, , www.facs.org/publications/newsscope/121815/cocmanual1218, Updated, Accessed July 10, 2017; (2012) The Partnership Launches Electronic Synoptic Pathology Reporting Initiative (ESPRI) to Advance Pan-Canadian Standardized Cancer Pathology Reporting, , www.partnershipagainstcancer.ca/the-partnership-launches-electronic-synoptic-pathology-reporting-initiative-espri-to-advance-pan-canadian-standardized-cancer-pathology-reporting/, Updated, Accessed July 10, 2017; (2016) Cancer Protocols Frequently Asked Questions, , www.cap.org/web/home/resources/cancer-reporting-tools/cancer-protocol-frequently-asked-questions?_afrLoop=262923013927738#!%40%40%3F_afrLoop3D262923013927738%26_adf.ctrl-state%3Dvq1atfacv_98, Updated, Accessed July 10, 2017; Williams, C.L., Bjugn, R., Hassell, A.L., Current status of discrete data capture in synoptic surgical pathology and cancer reporting (2015) PLMI, 7, pp. 11-22; Cimino, J.J., Desiderata for controlled medical vocabularies in the twenty-first century (1998) Methods Inf Med, 37 (4-5), pp. 394-403; (2009) Report on the Reporting Pathology Protocols for Breast and Prostate Cancers, and Melanomas, , RPP2; (2005) Report on the Reporting Pathology Protocols for Colon and Rectum Cancers Project, , RPP1; (2009) Report on the Reporting Pathology Protocols Project for Breast and Prostate Cancers and Melanomas - Executive Summary; Cimino, J.J., Coding systems in health care (1995) Yearb Med Inform, 1 (1), pp. 71-85; Chute, C.G., Cohn, S.P., Campbell, K.E., Oliver, D.E., Campbell, J.R., The content coverage of clinical classifications. For the Computer-Based Patient Record Institute's Work Group on Codes & Structures (1996) J Am Med Inform Assoc, 3 (3), pp. 224-233; Campbell, J.R., Carpenter, P., Sneiderman, C., Cohn, S., Chute, C.G., Warren, J., Phase II evaluation of clinical coding schemes: Completeness, taxonomy, mapping, definitions, and clarity. CPRI Work Group on Codes and Structures (1997) J Am Med Inform Assoc, 4 (3), pp. 238-251; (2002) Scope and Criteria for Selection of PMRI Terminologies, pp. 1-98; Schulz, S., Balkanyi, L., Cornet, R., Bodenreider, O., From concept representations to ontologies: A paradigm shift in health informatics? (2013) Healthc Inform Res, 19 (4), pp. 235-242; Rector, A.L., Rogers, J., Taweel, A., Models and inference methods for clinical systems: A principled approach (2004) Stud Health Technol Inform, 107, pp. 79-83; (2014) Template for Reporting Results of Biomarker Testing of Specimens from Patients with Carcinoma of the Colon and Rectum, , www.cap.org/ShowProperty?nodePath=/UCMCon/Contribution%20Folders/WebContent/pdf/cp-colorectalbiomarker-14.pdf, Updated, Accessed July 10, 2017; Simpson, R.W., Berman, M.A., Foulis, P.R., Cancer biomarkers: The role of structured data reporting (2015) Arch Pathol Lab Med, 139 (5), pp. 587-593; (2017) LOINC, , www.loinc.org, Updated, Accessed February 3, 2017; (2017) SNOMED CT worldwide, , www.snomed.org/snomed-ct/snomed-ct-worldwide, Updated, Accessed February 3, 2017; Health information technology: Initial set of standards, implementation specifications, and certification criteria for electronic health record technology (2010) Interim final rule. Fed Regist, 75 (8), pp. 2013-2047. , Department of Health and Human Services; (2016) 2016 interoperability standards advisory, , www.healthit.gov/sites/default/files/2016-interoperability-standards-advisory-final-508.pdf, Updated, Accessed April 10, 2017; (2013) Cooperation agreement between international health standards terminology organization and Regenstrief Institute, Inc, , http://loinc.org/collaboration/ihtsdo/agreement.pdf, Updated, Accessed February 7, 2017; Case, J., (2017) SNOMED CT Editorial Guide, , January, London: SNOMED International; 2017; (2016) IHTSDO Observable and Investigation Model Project, , https://confluence.ihtsdotools.org/display/OBSERVABLE, Updated; Washington, M.K., Berlin, J., Branton, P., Protocol for the examination of specimens from patients with primary carcinoma of the colon and rectum (2009) Arch Pathol Lab Med, 133 (10), pp. 1539-1551; Lester, S.C., Bose, S., Chen, Y.Y., Protocol for the examination of specimens from patients with invasive carcinoma of the breast (2009) Arch Pathol Lab Med, 133 (10), pp. 1515-1538; Bartley, A.N., Hamilton, S.R., Alsabeh, R., Template for reporting results of biomarker testing of specimens from patients with carcinoma of the colon and rectum (2014) Arch Pathol Lab Med, 138 (2), pp. 166-170; Fitzgibbons, P.L., Dillon, D.A., Alsabeh, R., Template for reporting results of biomarker testing of specimens from patients with carcinoma of the breast (2014) Arch Pathol Lab Med, 138 (5), pp. 595-601; (2012) SNOMED-CT Technical Implementation Guide, , July 2012 International Release (US English) ed. Copenhagen: International Health Terminology Standards Development Organization; (2014), https://confluence.ihtsdotools.org/display/REFSET/Requirements?preview=%2F6160816%2F6160916%2FSNOMED_CT_Namespace:Registry-OFFICIAL20141021.pdf, Updated, Accessed July 10, 2017; http://owl.man.ac.uk/factplusplus/, FaCT++, Updated 2007, Accessed July 10, 2017; Sithanandam, G., Druck, T., Cannizzaro, L.A., Leuzzi, G., Huebner, K., Rapp, U.R., B-raf and a B-raf pseudogene are located on 7q in man (1992) Oncogene, 7 (4), pp. 795-799; www.genenames.org, HUGO Gene Nomenclature Committee, Updated 2015, Accessed July 10, 2017; den Dunnen, J.T., Dalgleish, R., Maglott, D.R., HGVS recommendations for the description of sequence variants: 2016 update (2016) Hum Mutat, 37 (6), pp. 564-569; den Dunnen, J.T., Sequence variant nomenclature, , www.hgvs.org/varnomen, Accessed February 3, 2017; Deckard, J., McDonald, C.J., Vreeman, D.J., Supporting interoperability of genetic data with LOINC (2015) J Am Med Inform Assoc, 22 (3), pp. 621-627; Campbell, J.R., Talmon, G., Cushman-vokoun, A., Karlsson, D., Scott Campbell, W., An extended SNOMED CT concept model for observations in molecular genetics (2017) AMIA Annu Symp Proc, 2016, pp. 352-360; Obama, B., (2015) The Precision Medicine Initiative, , www.whitehouse.gov/precision-medicine, Updated, Accessed July 10, 2017; Hoffman, M., Arnoldi, C., Chuang, I., The clinical bioinformatics ontology: A curated semantic network utilizing RefSeq information (2005) Pac Symp Biocomput, pp. 139-150; Hoffman, M.A., The genome-enabled electronic medical record (2007) J Biomed Inform, 40 (1), pp. 44-46; Jing, X., Kay, S., Marley, T., Hardiker, N.R., Cimino, J.J., Incorporating personalized gene sequence variants, molecular genetics knowledge, and health knowledge into an EHR prototype based on the continuity of care record standard (2012) J Biomed Inform, 45 (1), pp. 82-92; Sax, U., Schmidt, S., Integration of genomic data in electronic health records: Opportunities and dilemmas (2005) Methods Inf Med, 44 (4), pp. 546-550; Deckard, J., McDonald, C.J., Vreeman, D.J., Supporting interoperability of genetic data with LOINC (2015) J Am Med Inform Assoc, 22 (3), pp. 621-627; (2017) HL7 version 2 Implementation Guide: Clinical Genomics; Fully LOINC-qualified Cytogenetic Model, release 1 (US Realm), , www.hl7.org/implement/standards/product_brief.cfm?product_id=364, Updated, Accessed February 3, 2017; (2017) HL7 Version 2 Implementation Guide: Clinical Genomics; Fully LOINC-qualified Genetic Variation Model (US realm), , www.hl7.org/implement/standards/product_brief.cfm?product_id=23, Updated, Accessed February 3, 2017; (2017) FHIR Release 3 (STU) - Genomics Implementation Guidance, , www.hl7.org/FHIR/genomics.html#diagnosticreport-genetics, Updated, Accessed July 10, 2017; Masys, D.R., Jarvik, G.P., Abernethy, N.F., Technical desiderata for the integration of genomic data into electronic health records (2012) J Biomed Inform, 45 (3), pp. 419-422; (2007) The Learning Healthcare System, , Washington, DC: National Academies Press RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: The College of American Pathologists (CAP) introduced the first cancer synoptic reporting protocols in 1998. However, the objective of a fully computable and machine-readable cancer synoptic report remains elusive due to insufficient definitional content in Systematized Nomenclature of Medicine - Clinical Terms (SNOMED CT) and Logical Observation Identifiers Names and Codes (LOINC). To address this terminology gap, investigators at the University of Nebraska Medical Center (UNMC) are developing, authoring, and testing a SNOMED CT observable ontology to represent the data elements identified by the synoptic worksheets of CAP. Methods: Investigators along with collaborators from the US National Library of Medicine, CAP, the International Health Terminology Standards Development Organization, and the UK Health and Social Care Information Centre analyzed and assessed required data elements for colorectal cancer and invasive breast cancer synoptic reporting. SNOMED CT concept expressions were developed at UNMC in the Nebraska LexiconVC SNOMED CT namespace. LOINC codes for each SNOMED CT expression were issued by the Regenstrief Institute. SNOMED CT concepts represented observation answer value sets. Results: UNMC investigators created a total of 194 SNOMED CT observable entity concept definitions to represent required data elements for CAP colorectal and breast cancer synoptic worksheets, including biomarkers. Concepts were bound to colorectal and invasive breast cancer reports in the UNMC pathology system and successfully used to populate a UNMC biobank. Discussion: The absence of a robust observables ontology represents a barrier to data capture and reuse in clinical areas founded upon observational information. Terminology developed in this project establishes the model to characterize pathology data for information exchange, public health, and research analytics. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. ER - TY - JOUR T1 - The next generation of interoperability agents in healthcare A1 - Cardoso, Luciana A1 - Marins, Fernando A1 - Portela, Filipe A1 - Santos, Manuel A1 - Abelha, António A1 - Machado, José Y1 - 2014/// KW - Agency for integration KW - Agent monitoring KW - Diffusion and archive of medical information(AIDA) KW - Healthcare interoperability KW - Multi-agent systems JF - International Journal of Environmental Research and Public Health DO - 10.3390/ijerph110505349 N2 - Interoperability in health information systems is increasingly a requirement rather than an option. Standards and technologies, such as multi-agent systems, have proven to be powerful tools in interoperability issues. In the last few years, the authors have worked on developing the Agency for Integration, Diffusion and Archive of Medical Information (AIDA), which is an intelligent, agent-based platform to ensure interoperability in healthcare units. It is increasingly important to ensure the high availability and reliability of systems. The functions provided by the systems that treat interoperability cannot fail. This paper shows the importance of monitoring and controlling intelligent agents as a tool to anticipate problems in health information systems. The interaction between humans and agents through an interface that allows the user to create new agents easily and to monitor their activities in real time is also an important feature, as health systems evolve by adopting more features and solving new problems. A module was installed in Centro Hospitalar do Porto, increasing the functionality and the overall usability of AIDA. ER - TY - CONF T1 - A big data approach for querying data in EHR systems A1 - Cassavia, N A1 - Ciampi, M A1 - De Pietro, G A1 - Masciari, E Y1 - 2016/// KW - Big data KW - Data access KW - Database systems KW - EHR systems KW - Federal governments KW - Health care KW - Health-care system KW - Healthcare KW - Information management KW - Interoperability KW - Medical data KW - Private organizations KW - Query processing KW - Reduce costs VL - 11 SP - 212 EP - 217 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989237536&doi=10.1145%2F2938503.2938539&partnerID=40&md5=64e5a57bd0794d7ffa77170a8ac751f6 N1 - Cited By :2 Export Date: 10 September 2018 References: (1999) Synapses/SynEx Goes XML. Studies in Health Technology and Informatics, , IOS press; (2001), http://healthcare.omg.org/Roadmap/corbamedroadmap.htm; Big data (2008) Nature, , Sep; Data, data everywhere (2010) The Economist, , Feb; Drowning in numbers - Digital data will flood the planet - And help us understand it better (2011) The Economist, , Nov; Agrawal, D., (2012) D.: Challenges and Opportunities with Big Data. A Community White Paper Developed by Leading Researchers Across the United States, , Mar; Appari, A., Johnson, M.E., Information security and privacy in healthcare: Current state of research (2010) International Journal of Internet and Enterprise Management, 6 (4), p. 279; Bittner, T., Donnelly, M., Winter, S., Ontology and semantic interoperability (2005) Large-Scale 3D Data Integration, pp. 139-161. , CRC Press, London; Blobel, B., Oemig, F., What is needed to finally achieve semantic interoperability? (2009) IFMBE Proceedings, 25 (12), pp. 411-414; Blobel, B., Kalra, D., Koehn, M., Lunn, K., Pharow, P., Ruotsalainen, P., Schulz, S., Smith, B., The role of ontologies for sustainable, semantically interoperable and trustworthy ehr solutions (2009) Medical Informatics in A United and Healthy Europe - Proceedings of MIE 2009, the XXIInd International Congress of the European Federation for Medical Informatics, Sarajevo, Bosnia and Herzegovina, pp. 953-957. , http://dx.doi.org/10.3233/978-1-60750-044-5-953, August 30 -September 2, 2009; Borst, F., Appel, R., Baud, R., Ligier, Y., Scherrer, J., Happy birthday DIOGENE: A hospital information system born 20 years ago (1999) International Journal of Medical Informatics, 54 (3), pp. 157-167; Bouhaddou, O., Warnekar, P., Parrish, F., Do, N., Mandel, J., Kilbourne, J., Lincoln, M.J., Exchange of computable patient data between the department of veterans affairs (va) and the department of defense (dod): Terminology mediation strategy (2008) Journal of the American Medical Informatics Association, 15 (2), pp. 174-183; Dogac, A., Laleci, G.B., Aden, T., Eichelberg, M., Enhancing ihe xds for federated clinical affinity domain support (2007) IEEE Transactions on Information Technology in Biomedicine, 11 (2), pp. 213-221. , http://dx.doi.org/10.1109/TITB.2006.874928, Mar; Dogac, A., Laleci, G.B., Kabak, Y., Unal, S., Heard, S., Beale, T., Elkin, P.L., Kernberg, M., Exploiting ebxml registry semantic constructs for handling archetype metadata in healthcare informatics (2006) International Journal of Metadata, Semantics and Ontologies, 1 (1), pp. 21-36. , http://dx.doi.org/10.1504/IJMSO.2006.008767, Jan; Esposito, C., Ciampi, M., De Pietro, G., Donzelli, P., Notifying medical data in health information systems (2012) Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems, pp. 373-374. , http://doi.acm.org/10.1145/2335484.2335528, DEBS '12, ACM, New York, NY, USA; Haux, R., Health information systems aas past, present, future (2006) International Journal of Medical Informatics, 75 (3-4), pp. 268-281; Huang, H.K., (2004) PACS and Imaging Informatics, , Wiley-Liss; Nixon, L.J.B., Cerizza, D., Valle, E.D., Simperl, E., Krummenacher, R., Enabling collaborative ehealth through triplespace computing (2007) Proceedings of the 16th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, pp. 80-85. , http://dx.doi.org/10.1109/WETICE.2007.140, WETICE '07, IEEE Computer Society, Washington, DC, USA; Nordbotten, N.A., Xml and web services security standards (2009) IEEE Communications Surveys & Tutorials, 11 (3), pp. 4-21. , http://dx.doi.org/10.1109/SURV.2009.090302, Jul; Schloeffel, P., Beale, T., Hayworth, G., Heard, S., Leslie, H., (2006) The Relationship between Cen 13606, hl7, and Openehr; Sittig, D., Kuperman, G., Teich, J., Www-based interfaces to clinical information systems: The state of the art (1996) Proceedings of the AMIA Annual Fall Symposium, pp. 694-698. , CRC Press, London RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Information management in healthcare is nowadays experiencing a great revolution. After the impressive progress in digitizing medical data by private organizations, also the federal government and other public stakeholders have also started to make use of healthcare data for data analysis purposes in order to extract actionable knowledge. In this paper, we propose an architecture for supporting interoperability in healthcare systems by exploiting Big Data techniques. In particular, we describe a proposal based on big data techniques to implement a nationwide system able to improve EHR data access efficiency and reduce costs. © ACM 2016. ER - TY - CHAP T1 - Use and reuse of electronic health records: Building information systems for improvement of health services A1 - Ceruti, M A1 - Geninatti, S A1 - Siliquini, R Y1 - 2015/// KW - Building information system KW - Electronic health record KW - Electronic medical record KW - Electronic records KW - Health KW - Health care KW - Health related informations KW - Healthcare services KW - Information Systems KW - Medical computing KW - Personal health record KW - Population statistics KW - Public health issues KW - Records management JF - E-Health and Telemedicine: Concepts, Methodologies, Tools, and Applications VL - 2 SP - 961 EP - 975 SN - 9781466687578 (ISBN); 1466687568 (ISBN); 9781466687561 (ISBN) UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958679023&doi=10.4018%2F978-1-4666-8756-1.ch049&partnerID=40&md5=1c56929c09fb0baaa1b948603a0bb3f0 N1 - Cited By :1 Export Date: 10 September 2018 References: Albu, J., Sohler, N., Matti-Orozco, B., Sill, J., Baxter, D., Burke, G., Young, E., Expansion of electronic health record-based screening, prevention, and management of diabetes in New York City (2013) Preventing Chronic Disease, 10, p. E13. , PMID:23369766; Almond, H., Cummings, E., Turner, P., Australia's personally controlled electronic health record and primary healthcare: Generating a framework for implementation and evaluation (2013) Studies in Health Technology and Informatics, 188, pp. 1-6. , PMID:23823280; Ash, J., Kilo, C.M., Shapiro, M., Wasserman, J., McMullen, C., Hersh, W., (2011) Roadmap for Provision of Safer Healthcare Information Systems: Preventing e-Iatrogenesis, , Institute of Medicine; (2010) Electronic Health Record Interoperability., , http://www.e-health.standards.org.au/IT014SubjectAreas/EHRInteroperability.aspx; Bernat, J.L., Ethical and quality pitfalls in electronic health records (2013) Neurology, 80 (11), pp. 1057-1061; Blobel, B., Advances in secure and architectural EHR approaches (2005) International Journal of Medical Informatics, 75 (3-4), pp. 185-190. , Epub 2005 Aug 19, PMID:16112891; Burnum, J.F., The misinformation era:The fall of the Medical Record (1989) Annals of Internal Medicine, 110, pp. 482-484. , PMID:2919852; ISO 13606 standard. The EN 13606 Association, , www.en13606.org, (2009-2011). Retrieved September 29, 2013 from; De Clerq, E., Problem-oriented patient record model as a conceptual foundation for a multi-professional electronic patient record (2008) International Journal of Medical Informatics, 77 (9), pp. 565-575. , PMID:18248847; Garets, D., Davis, M., (2006) Electronic medical records vs. electronic health records: yes, there is a difference, , http://www.himssanalytics.org/docs/wp_emr_ehr.pdf, January 26, HIMSS Analytics. Retrieved 2013, September 28, from; Garrett, P., Seidman, J., US Department of Health & Human Services (2011) EMR vs EHR - What is the Difference?, , http://www.healthit.gov/buzz-blog/electronic-health-and-medical-records/emr-vsehr-difference/, Retrieved 2013, September 28, from:; Gibbons, P., Health Level Seven EHR Interoperability Work Group (2007) Coming to terms:Scoping Interoperability for Health Care, , http://www.hln.com/assets/pdf/Coming-to-Terms-February-2007.pdf, Retrieved 2013, October 2, from:; Goldwater, J.C., Kwon, N.J., Nathanson, A., Muckle, A.E., Brown, A., Cornejo, K., Open source electronic health records and chronic disease management (2013) Journal of American Medical Informatics Association, , doi: 11367amiajnl-2013-001672; Habib, J.L., EHRs, meaningful use, and a model EMR (2010) Drug Benefit Trends, 22 (4), pp. 99-101; Hayrinen, K., Saranto, K., Nykanen, P., Definition, structure, content, use and impacts of electronic health records: A review of the research literature (2008) International Journal of Medical Informatics, 77, pp. 291-304. , PMID:17951106; Hersh, W.R., Cimino, J., Payne, P.R.O., Embi, P., Logan, J., Weiner, M., Bernstam, E.V., Saltz, J., Recommendations for the use of operational Electronic Health Record data in comparative effectiveness research (2013) eGEMs, 1 (1). , Article 14; Hripcsak, G., Albers, D.J., Nextgeneration phenotyping of electronic health records (2012) Journal of the American Medical Informatics Association, pp. 1-5. , PMID:22955496; (2010) International Classification of ICD, , http://www.who.int/classifications/icd/en/; (2011) International Classification of Diseases, Ninth Revision, Clinical Modification, , http://www.cdc.gov/nchs/icd/icd9cm.htm#ftp; (2012) Health IT and Patient Safety: Building Safer Systems for Better Care, , Washington, DC: The National Academies Press; OpenEHR Foundation, , http://www.openehr.org, (n.d.), Retrieved September 29, 2013 from; Joellenbeck, L.M., Russell, P.K., Guze, S.B., Strategies to Protect the Health of Deployed US Forces, pp. 79-82. , Washington, DC: National Academy Press; Kahn, M.G., Raebel, M.A., Glanz, J.M., Riedlinger, K., Steiner, J.F., A pragmatic framework for single-site and multisite data quality assessment in electronic health record-based clinical research (2012) Medical Care, 50, pp. S21-S29. , PMID:22692254; Kalra, D., Electronic Health Standards (2006) IMIA Yearbook of Medical Informatics, 45, pp. S136-S144; Kudyakov, R., Bowen, J., Ewen, E., West, S.l., Daoud, Y., Fleming, N., Masica, A., Electronic health record use to classify patients with newly diagnosed versus preexisting type 2 diabetes: infrastructure for comparative effectiveness research and population health management (2012) Population Health Management, 15 (1), pp. 3-11. , PMID:21877923; Los, R.K., van Ginneken, A.M., Roukema, J., Moll, H.A., van der Lei, J., (2005) Medical Informatics and the Internet in Medicine, 30 (4), pp. 267-276. , PMID:16531353; Maylahn, C., Fleming, D., Birkhead, G., Health departments in a brave new world (2013) Preventing Chronic Disease, 10, p. E41. , PMID:23517584; (2013) Medicare and Medicaid EHR Incentive Programs, , http://www.healthit.gov/providers-professionals/ehr-incentive-programs; Najaftorkaman, M., Ghapanchi, A.H., Talaei-Khoei, A., Ray, P., Recent research areas and grand challenges in Electronic Health Record:A Literature survey approach (2013) The International Technology Management Review, 3 (1), pp. 12-21; (2013) Health IT Policy Committee: Recommendations to the National Coordinator for Health IT., , http://www.healthit.gov/policy-researchers-implementers/health-itpolicy-committee-recommendations-nationalcoordinator-heal, Retrieved September 12, 2013 from; Ruch, P., Section Editor for the IMIA Yearbook Section on Decision Support Systems. Findings from the yearbook 2010 section on decision support systems (2010) IMIA Yearbook of Medical Information, 2010, pp. 55-57; Siliquini, R., Surfing the internet for health information: an italian survey on use and population choices (2011) BMC Medical Informatics and Decision Making, (11), p. 21. , PMID:21470435; Sinha, P.K., Sunder, G., Bendale, P., Mantri, M.D., Dande, A.C., (2013) Electronic Health Record. Standards, Coding Systems, Frameworks, and Infrastructure. Wiley, , IEEE Press; Steers, W.D., The Electronic Medical Record: How Not to Communicate (2013) The Journal of Urology, 190 (5), pp. 1636-1637. , PMID:23933460; (2008) Report to the Office of the National Coordinator for Health Information Technology on Defining Key Health Information Technology Terms., , http://hitechanswers.wpengine.netdnacdn.com/wp-content/uploads/2013/05/NAHITDefinitions2008.pdf, Retrieved September 12, 2013 at; US eMERGE network The Electronic Medical Records and Genomics (eMERGE) Network., , http://emerge.mc.vanderbilt.edu/; Weiner, J.P., Fowles, J., Chan, K.S., New paradigms for measuring clinical performance using electronic health records (2012) International Journal for Quality in Health Care, 24 (3), pp. 200-205. , PMID:22490301; Weiskopf, N.G., Hripcsak, G., Swaminathan, S., Weng, C., Defining and measuring completeness of electronic health records for secondary use (2013) Journal of Biomedical Informatics, 46, pp. 830-836. , PMID:23820016; Weiskopf, N.G., Weng, C., Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research (2013) Journal of the American Medical Informatics Association, 20 (1), pp. 144-151. , PMID:22733976; (2012) Legal frameworks for e-health, 5. , Global observatory for ehealth series; Zuehlke, P., Li, J.H., Talaei-Khoei, A., Ray, P., A functional specification for mobile eHealth (mHealth) systems (2009) Proceedings of E-Health Networking, Applications and Services, , IEEE RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Electronic Health Record (EHR) is a term with several meanings, even if its very definition allows distinguishing it from other electronic records of healthcare interest, such as Electronic Medical Records (EMR) and Personal Health Records (PHR). EMR is the electronic evolution of paper-based medical records, while PHR is mainly the collection of health-related information of a single individual. All of these have many points in common, but the interchangeable use of the terms leads to several misunderstandings and may threaten the validity and reliability of EHR applications. EHRs are more structured and conform to interoperability standards, and include a huge quantity of data of very large populations. Thus, they have proven to be useful for both theoretical and practical purposes, especially for Public Health issues. In this chapter, the authors argue that the appropriate use of EHR requires a realistic comprehensive concept of e-health by all the involved professions. They also show that a change in the "thinking" of e-health is necessary in order to achieve tangible results of improvement in healthcare services through the use of EHR. © 2016 by IGI Global. All rights reserved. ER - TY - JOUR T1 - OMDP: An ontology-based model for diagnosis and treatment of diabetes patients in remote healthcare systems A1 - Chen, L A1 - Lu, D A1 - Zhu, M A1 - Muzammal, M A1 - Samuel, O W A1 - Huang, G A1 - Li, W A1 - Wu, H Y1 - 2019/// JF - International Journal of Distributed Sensor Networks VL - 15 IS - 5 DO - 10.1177/1550147719847112 N2 - ©The Author(s) 2019. Millions of adults have diabetes across the globe and the overall cost for managing diabetic patients has reached up to approximately 250 million. A major constraint in existing ontology-based systems for diagnosing and treating diabetes is the presence of semantic inconsistencies and lack of a comprehensive clinical approach primarily due to consideration of a limited number of classes in the model. In this research, we are focused on building an ontology-based model for diabetic patients by collecting detailed diabetic knowledge of subjects for further diagnosis and treatment. The concept of semantic resources to electronic health record standards is an essential factor for semantic interoperability in remote health monitoring. This study applies semantic web ontology language for developing ontology-based model for diabetic patients to aid doctors in reaching an efficient diagnostic decision about the status of diabetes by applying Semantic Web Rule Language. A total of 766 medical records from clinical environment were selected in this study, and 269 of them were known for developing diabetes. The experimental results suggest that the proposed solution is more accurate in managing diabetes compared to other medical applications. The performance analysis of the ontology-based model for diabetic patients regarding the accuracy of disease prediction, diagnosing diabetes, and recommending medicine is 95%, 98%, and 85%, respectively. ER - TY - JOUR T1 - Semantic Web integration of Cheminformatics resources with the SADI framework. A1 - Chepelev, Leonid L A1 - Dumontier, Michel Y1 - 2011/// KW - Humanism KW - Humanities KW - Humans KW - Semantics KW - Software PB - Springer JF - Journal of cheminformatics VL - 3 SP - 16 EP - 16 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND The diversity and the largely independent nature of chemical research efforts over the past half century are, most likely, the major contributors to the current poor state of chemical computational resource and database interoperability. While open software for chemical format interconversion and database entry cross-linking have partially addressed database interoperability, computational resource integration is hindered by the great diversity of software interfaces, languages, access methods, and platforms, among others. This has, in turn, translated into limited reproducibility of computational experiments and the need for application-specific computational workflow construction and semi-automated enactment by human experts, especially where emerging interdisciplinary fields, such as systems chemistry, are pursued. Fortunately, the advent of the Semantic Web, and the very recent introduction of RESTful Semantic Web Services (SWS) may present an opportunity to integrate all of the existing computational and database resources in chemistry into a machine-understandable, unified system that draws on the entirety of the Semantic Web. RESULTS We have created a prototype framework of Semantic Automated Discovery and Integration (SADI) framework SWS that exposes the QSAR descriptor functionality of the Chemistry Development Kit. Since each of these services has formal ontology-defined input and output classes, and each service consumes and produces RDF graphs, clients can automatically reason about the services and available reference information necessary to complete a given overall computational task specified through a simple SPARQL query. We demonstrate this capability by carrying out QSAR analysis backed by a simple formal ontology to determine whether a given molecule is drug-like. Further, we discuss parameter-based control over the execution of SADI SWS. Finally, we demonstrate the value of computational resource envelopment as SADI services through service reuse and ease of integration of computational functionality into formal ontologies. CONCLUSIONS The work we present here may trigger a major paradigm shift in the distribution of computational resources in chemistry. We conclude that envelopment of chemical computational resources as SADI SWS facilitates interdisciplinary research by enabling the definition of computational problems in terms of ontologies and formal logical statements instead of cumbersome and application-specific tasks and workflows. ER - TY - JOUR T1 - A journey to Semantic Web query federation in the life sciences. A1 - Cheung, Kei-Hoi A1 - Frost, H Robert A1 - Marshall, M Scott A1 - Prud'hommeaux, Eric A1 - Samwald, Matthias A1 - Zhao, Jun A1 - Paschke, Adrian Y1 - 2009/// KW - Biological Science Disciplines KW - Semantics KW - Vocabulary PB - BioMed Central JF - BMC bioinformatics VL - 10 SP - S10 EP - S10 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND As interest in adopting the Semantic Web in the biomedical domain continues to grow, Semantic Web technology has been evolving and maturing. A variety of technological approaches including triplestore technologies, SPARQL endpoints, Linked Data, and Vocabulary of Interlinked Datasets have emerged in recent years. In addition to the data warehouse construction, these technological approaches can be used to support dynamic query federation. As a community effort, the BioRDF task force, within the Semantic Web for Health Care and Life Sciences Interest Group, is exploring how these emerging approaches can be utilized to execute distributed queries across different neuroscience data sources. METHODS AND RESULTS We have created two health care and life science knowledge bases. We have explored a variety of Semantic Web approaches to describe, map, and dynamically query multiple datasets. We have demonstrated several federation approaches that integrate diverse types of information about neurons and receptors that play an important role in basic, clinical, and translational neuroscience research. Particularly, we have created a prototype receptor explorer which uses OWL mappings to provide an integrated list of receptors and executes individual queries against different SPARQL endpoints. We have also employed the AIDA Toolkit, which is directed at groups of knowledge workers who cooperatively search, annotate, interpret, and enrich large collections of heterogeneous documents from diverse locations. We have explored a tool called "FeDeRate", which enables a global SPARQL query to be decomposed into subqueries against the remote databases offering either SPARQL or SQL query interfaces. Finally, we have explored how to use the vocabulary of interlinked Datasets (voiD) to create metadata for describing datasets exposed as Linked Data URIs or SPARQL endpoints. CONCLUSION We have demonstrated the use of a set of novel and state-of-the-art Semantic Web technologies in support of a neuroscience query federation scenario. We have identified both the strengths and weaknesses of these technologies. While Semantic Web offers a global data model including the use of Uniform Resource Identifiers (URI's), the proliferation of semantically-equivalent URI's hinders large scale data integration. Our work helps direct research and tool development, which will be of benefit to this community. ER - TY - JOUR T1 - Semantic interoperability for antimicrobial resistance surveillance solutions in Europe A1 - Choquet, R A1 - Assélé-Kama, A A1 - Charlet, J A1 - Jaulent, M.-C. Y1 - 2013/// KW - Alignment KW - Data integration KW - Data quality KW - Data warehouse KW - Data warehouses KW - Europe KW - Information Dissemination KW - Information analysis KW - Information models KW - Interoperability KW - Medical informatics KW - Ontologies KW - Ontology KW - Query rewriting KW - Query rewritings KW - Semantic Web KW - Semantic interoperability KW - Semantic mediation KW - Semantic web KW - Semantics KW - Standards KW - Vocabulary JF - Ingenierie des Systemes d'Information VL - 18 IS - 6 SP - 59 EP - 82 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903276530&doi=10.3166%2Fisi.18.6.59-82&partnerID=40&md5=a78a899053bb3d0e538efe49d697c114 N1 - Export Date: 10 September 2018 References: Beale, T., Archetypes: Constraint-based domain models for future-proof information systems (2002) OOPSLA 2002 Workshop On Behavioural Semantics; Beuscart, R., PSIP: An overview of the results and clinical impli- cations (2011) Studies In Health Technology and Informatics, 166, pp. 3-12; Bizer, C., Cyganiak, R., D2RQ-Lessons Learned (2007) Proceedings of the W3CWorkshop On, p. 35; Broekstra, J., Kampman, A., van Harmelen, F., Se- same: A Generic Architecture for Storing and Querying RDF and RDF Schema (2002) The Semantic Web - ISWC 2002. First International Semantic Web Conference, 2342, pp. 54-68. , Ian Horrocks et James Hendler, editeurs, Sardinia, Italy, June 9-12, Proceedings; Chawathe, S., Garcia-Molina, H., Hammer, J., Ireland, K., Papakonstantinou, Y., Ullman, J., Widom, J., The TSIMMIS project: Integration of heterogeneous information sources (1994) Proceedings of the 10th Meeting of the Information Processing Society of Japan, pp. 7-18. , Tokyo, Japan; Choquet, R., Qouiyd, S., Ouagne, D., Pasche, E., Daniel, C., Boussaïd, O., Jaulent, M.C., The Information Quality Triangle: A methodology to assess clinical information quality (2010) Stud Health Technol Inform, 160 (PART 1), pp. 699-703; Choquet, R., (2011) Partage De Données Biomédicales: Modèles, Sémantique Et Qualité, , PhD thesis, Universite Pierre et Marie Curie; Coloma, P., Schuemie, M., Triro, G., Combining electronic healthcare databases in Europe to allow for largescale drug safety monitoring: The EUADR Project (2011) Pharmacoepidemiology and Drug Safety, 20 (1), pp. 1-11. , Jan; Levy, A.Y., Rajaraman, A., Ordille, J.J., Querying heterogeneous information sources using source descriptions (1996) Proceedings of the Twenty-second International Conference On Very Large Data Bases (VLDB'96), pp. 251-262; Lovis, C., Colaert, D., Stroetmann, V., DebugIT for patient safety - improving the treatment with antibiotics through multimedia data mining of heterogeneous clinical data (2008) Stud Health Technol Inform, 136, pp. 641-646; O'Connor, M., Das, A., Semantic reasoning with XML- based biomedical information models (2010) Studies In Health Technology and Informatics, 160 (PART 2), pp. 986-990; Pasche, E., Gobeill, J., Teodoro, D., Gaudinat, A., Vishnykova, D., Lovis, C., Ruch, P., An advanced search engine for patent analytics in medicinal chemistry (2012) Stud Health Technol Inform, 180, pp. 204-209; Schober, D., Boeker, M., Cools, H., Teodoro, D., Bullenkamp, J., Nadah, N., Choquet, R., Schulz, S., The DebugIT core ontology: Semantic integration of antibiotics resistance patterns (2010) Stud Health Technol Inform, 160 (PART 2), pp. 1060-1064; Schulz, S., Suntisrivaraporn, B., Baader, F., SNOMED CT's problem list: Ontologists' and logicians' therapy suggestions (2007) Studies In Health Technology and Informatics, 129 (PART 1), pp. 802-806; Spackman, K.A., (2004) Examining SNOMED From the Perspective of Formal Ontological Principles: Some Preliminary Analysis and Observations, , Whistler; Teodoro, D., Lovis, C., Empirical mode decomposition and k-nearest embedding vectors for timely analyses of antibiotic resistance trends (2013) PloS One, 8 (4), pp. e61180. , doi:10.1371/journal.pone.0061180; Traver, V., Faubel, R., Personal Health: The New Paradigm to Make Sustainable the Health Care System (2011) Biomedical Engineering Systems and Technologies: Third International Joint Conference, BIOSTEC 2010; Vicente, M., Hodgson, J., Massidda, O., Tonjum, T., Henriques-Normark, B., Ron, E., The fallacies of hope: Will we discover new antibiotics to combat pathogenic bacteria in time? (2006) FEMS Microbiology Reviews, 30 (6), pp. 841-852; Wang, R., A product perspective on total data quality management (1998) Communications of the ACM, 41 (2), pp. 57-65; Xu, L., Embley, D.W., Combining the Best of Global-as-View and Local-as- View for Data Integration (2004) In ISTA, 48, pp. 123-136 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This article deals with the problematic of biomedical information sharing in the study of antibioresistance growth in Europe. Our general working hypothesis is: how can we share biomedical information in Europe in a non ambiguous way, in a fast way, and on demand? Many issues are raised by this working hypothesis: the issue of the quality of the data, the issue of the representation of data through structure, vocabulary, and semantics. We also address the problem of alignment of data with domain ontologies and the problem of data mediation using domain ontologies. We then present a system of semantic interoperability based on rules addressing the problem of semantic alignment of heterogeneous systems applied to our domain. Finally we discuss how semantics can contribute to the improvement of information sharing and we also discuss the limits of the current tools and methods. © 2013 Lavoisier. ER - TY - CONF T1 - OpenECG: Promoting interoperability through the consistent implementation of the SCP-ECG standard in electrocardiography A1 - Chronaki, C A1 - Chiarugi, F A1 - Fischer, R Y1 - 2007/// KW - Electrocardiography KW - eHealth services KW - electrocardiography KW - interoperability KW - medical devices KW - standards KW - telemedicine VL - 129 SP - 1484 EP - 1484 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887914251&partnerID=40&md5=696af8f61cbc82828dba57429af75178 N1 - Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The OpenECG Network (www.openecg.net) has been created to promote interoperability in electrocardiography with tutorials, specifications, open source tools, data sets, converters, and interoperability testing. ECG vendors, members of professional organizations, researchers, and other stakeholders participate in the OpenECG network to exchange views and receive assistance in implementation. In 2006, members are more than 700 individuals from 58 countries. A specific focus area for OpenECG that concerns diagnostic quality resting electrocardiograms (ECGs) is SCP-ECG, the European standard (EN1064:2005). An online interoperability testing service assists members in consistently implementing SCP-ECG and effortlessly integrating electrocardiographs with eHealth systems. OpenECG is a case of best practice in interoperability that should be followed by medical devices and sensors for effective personalized health monitoring. © 2007 The authors. All rights reserved. ER - TY - JOUR T1 - SNOMED CT concept hierarchies for computable clinical phenotypes from electronic health record data: Comparison of intensional versus extensional value sets A1 - Chu, L A1 - Kannan, V A1 - Basit, M A A1 - Schaeflein, D J A1 - Ortuzar, A R A1 - Glorioso, J F A1 - Buchanan, J R A1 - Willett, D L Y1 - 2019/// JF - Journal of Medical Internet Research VL - 21 IS - 1 DO - 10.2196/11487 N2 - ©Ling Chu, Vaishnavi Kannan, Mujeeb A Basit, Diane J Schaeflein, Adolfo R Ortuzar, Jimmie F Glorioso, Joel R Buchanan, Duwayne L Willett. Background: Defining clinical phenotypes from electronic health record (EHR)–derived data proves crucial for clinical decision support, population health endeavors, and translational research. EHR diagnoses now commonly draw from a finely grained clinical terminology—either native SNOMED CT or a vendor-supplied terminology mapped to SNOMED CT concepts as the standard for EHR interoperability. Accordingly, electronic clinical quality measures (eCQMs) increasingly define clinical phenotypes with SNOMED CT value sets. The work of creating and maintaining list-based value sets proves daunting, as does insuring that their contents accurately represent the clinically intended condition. Objective: The goal of the research was to compare an intensional (concept hierarchy-based) versus extensional (list-based) value set approach to defining clinical phenotypes using SNOMED CT–encoded data from EHRs by evaluating value set conciseness, time to create, and completeness. Methods: Starting from published Centers for Medicare and Medicaid Services (CMS) high-priority eCQMs, we selected 10 clinical conditions referenced by those eCQMs. For each, the published SNOMED CT list-based (extensional) value set was downloaded from the Value Set Authority Center (VSAC). Ten corresponding SNOMED CT hierarchy-based intensional value sets for the same conditions were identified within our EHR. From each hierarchy-based intensional value set, an exactly equivalent full extensional value set was derived enumerating all included descendant SNOMED CT concepts. Comparisons were then made between (1) VSAC-downloaded list-based (extensional) value sets, (2) corresponding hierarchy-based intensional value sets for the same conditions, and (3) derived list-based (extensional) value sets exactly equivalent to the hierarchy-based intensional value sets. Value set conciseness was assessed by the number of SNOMED CT concepts needed for definition. Time to construct the value sets for local use was measured. Value set completeness was assessed by comparing contents of the downloaded extensional versus intensional value sets. Two measures of content completeness were made: for individual SNOMED CT concepts and for the mapped diagnosis clinical terms available for selection within the EHR by clinicians. Results: The 10 hierarchy-based intensional value sets proved far simpler and faster to construct than exactly equivalent derived extensional value set lists, requiring a median 3 versus 78 concepts to define and 5 versus 37 minutes to build. The hierarchy-based intensional value sets also proved more complete: in comparison, the 10 downloaded 2018 extensional value sets contained a median of just 35% of the intensional value sets' SNOMED CT concepts and 65% of mapped EHR clinical terms. Conclusions: In the EHR era, defining conditions preferentially should employ SNOMED CT concept hierarchy-based (intensional) value sets rather than extensional lists. By doing so, clinical guideline and eCQM authors can more readily engage specialists in vetting condition subtypes to include and exclude, and streamline broad EHR implementation of condition-specific decision support promoting guideline adherence for patient benefit. ER - TY - JOUR T1 - An interoperable data architecture for data exchange in a biomedical research network A1 - Crichton, D A1 - Downing, G J A1 - Hughes, J S A1 - Kincaid, H A1 - Srivastava, S Y1 - 2001/// KW - Biological Markers KW - Biomedical engineering KW - Computational Biology KW - Data architecture KW - Data handling KW - Data structures KW - Database systems KW - Electronic commerce KW - Interoperability KW - Knowledge based systems KW - Mathematical models KW - Medical applications KW - Security of data KW - Software prototyping JF - Proceedings of the IEEE Symposium on Computer-Based Medical Systems SP - 65 EP - 72 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-0034869653&doi=10.1109%2FCBMS.2001.941699&partnerID=40&md5=58aa1b85868d582dea5e39d93c71e2c2 N1 - Cited By :9 Export Date: 10 September 2018 References: Crichton, D.J., Hughes, J.S., Hyon, J.J., Kelly, S.C., A distributed component framework for science data product interoperability (2001) The 17th International Conference on Scientific and Technical Data, , http://oodt.jpl.nasa.gov/doc/papers/italy_codata/italy_paper.pdf, October; Crichton, D.J., Hughes, J.S., Hyon, J.J., Kelly, S.C., Science Search and retrieval using XML (2000) The Second National Conference on Scientific and Technical Data, , http://oodt.jpl.nasa.gov/doc/papers/codata/paper.pdf, U.S. National Committee for CODATA, National Research Council, March 13-14; http://wwwl.od.nih.gov/osp/ospp/biomarkers/Biomarkers_Knowledge_System.pdf, Biomarkers Knowledge System; http:/edrn.nci.nih.gov/; Hughes, J.S., Crichton, D.J., Hyon, J.J., Kelly, S.C., (2000) A Multi-Discipline Metadata Registry for Science Interoperability, , http://www.sdct.itl.nist.gov/˜ftp/18/sc32wg2/2000/events/openforum /index.htm, Open Forum on Metadata Registries, ISO/IEC JTC1/SC32, Data Management and Interchange, January; (1999) CORBA/IIOP 2.3.1 Specification, , October; Extensible Markup Language (XML), Version 1.0, , http://www.w3.org/TR/REC-xml; Data entity dictionary specification language (DEDSL) - Abstract syntax (1999) CCSDS 647.0-R-2.0, Draft Recommendation for Space Data System, , Standards, Consultative Committee on Space Data Systems, November; Special issue: Planetary data system (1996) Planetary and Space Science, 44 (1). , Pergamon, January; http://www.iso.ch/infoe/text.htm, ISO/IEC11179-1,6; Common Data Elements Dictionary, , http://cii-server5.nci.nih.gov:8080/pls/cde_public/cde_java.show RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Knowledge discovery, and data correlation require a unified approach to basic data management. However, achieving such an approach is nearly impossible with hundreds of disparate data sources, legacy systems, and data formats. This problem is pervasive in the biomedical research community where data models, taxonomies, and data management systems are locally implemented. These local implementations create an environment where interoperability and collaboration between researchers and research institutions are limited. Investigators from this paper demonstrate how technology developed by NASA's Jet Propulsion Laboratory (JPL) for space science can be used to build an interoperable data architecture for bioinformatics. JPL has taken a novel approach towards solving this problem by exploiting web technologies usually dedicated to e-commerce, combined with a rich, metadata-based environment. This paper discusses the approach taken to develop a prototype data architecture for the discovery and validation of d isease biomarkers within a biomedical research network. Biomarkers are measured parameters of normal biologic processes. pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers are of growing importance in the biomedical research for therapeutic discovery, disease prevention, and detection. A bioinformatics infrastructure is crucial to support the integration and analysis of large, complex biological and epidemiologic datasets. ER - TY - JOUR T1 - Implementing interoperable provenance in biomedical research A1 - Curcin, V A1 - Miles, S A1 - Danger, R A1 - Chen, Y A1 - Bache, R A1 - Taweel, A Y1 - 2014/// KW - Biomedical domain KW - Biomedical informatics KW - Biomedical research KW - Computer software KW - Digital storage KW - Electronic health record KW - Epidemiological studies KW - Heterogeneous software systems KW - Industrial research KW - Interoperability KW - Provenance KW - Translational Research JF - Future Generation Computer Systems VL - 34 SP - 1 EP - 16 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891593304&doi=10.1016%2Fj.future.2013.12.001&partnerID=40&md5=a39753f21070d07d4a36964d03e12512 N1 - Cited By :10 Export Date: 10 September 2018 References: Moreau, L., The foundations for provenance on the web (2010) Found. Trends Web Sci., 2, pp. 99-241; Hull, D., Wolstencroft, K., Stevens, R., Goble, C., Pocock, M.R., Li, P., Oinn, T., Taverna: A tool for building and running workflows of services (2006) Nucleic Acids Res., 34, pp. 729-732; (2002) ICH Topic E6(R1) Guideline for Good Clinical Practice, Technical Report, European Medicines Agency, , http://www.ema.europa.eu/docs/enGB/document_library/Scientific_guideline/ 2009/09/WC500002874.pdf, European Medicines Agency, URL; Schulz, K.F., Altman, D.G., Moher, D., CONSORT 2010 statement: Updated guidelines for reporting parallel group randomised trials (2010) BMJ, 340. , c332; Von Elm, E., Egger, M., Altman, D.G., Pocock, S.J., Gotzsche, P.C., Vandenbroucke, J.P., Strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies (2007) British Medical Journal, 335 (7624), pp. 806-808; (2012) Clinical Data Interchange Standards Consortium, CDISC Analysis DAta Model v1.2; http://www.opendatainitiative.org/home/about, Space Time Research (Institution/Organization), The Open Data Initiative, 2011; Groves, T., Godlee, F., Open science and reproducible research (2012) BMJ, 344. , e4383; Miles, S., Groth, P., Branco, M., Moreau, L., The requirements of using provenance in e-science experiments (2007) Journal of Grid Computing, 5 (1), pp. 1-25. , DOI 10.1007/s10723-006-9055-3; Groth, P., Gil, Y., Cheney, J., Miles, S., Requirements for provenance on the web (2012) Int. J. Digit. Curation, 7, pp. 39-56; Buneman, P., Khanna, S., Tan, W.-C., Why and Where: A Characterization of Data Provenance (2001) Lecture notes in computer science, (1973), pp. 316-330; Foster, I., Vockler, J., Wilde, M., Zhao, Y., Chimera: A virtual data system for representing, querying, and automating data derivation (2002) International Conference on Scientific and Statistical Database Management, p. 37; Simmhan, Y.L., Plale, B., Gannon, D., A survey of data provenance in e-science (2005) SIGMOD Record, 34 (3), pp. 31-36. , http://www.sigmod.org/sigmod/record/issues/0509/p31-special-sw-section-5. pdf, DOI 10.1145/1084805.1084812; (2012) Dublin Core Metadata Initiative, DCMI Metadata Terms, , http://dublincore.org/documents/dcmi-terms/; Brazma, A., Minimum information about a microarray experiment (MIAME) - Successes, failures, challenges (2009) Sci. World J., 9, pp. 420-423; Moreau, L., Clifford, B., Freire, J., Futrelle, J., Gil, Y., Groth, P., Kwasnikowska, N., Van Den Bussche, J., The open provenance model core specification (v1.1) (2011) Future Gener. Comput. Syst., 27, pp. 743-756; http://www.w3.org/2011/prov/wiki/Main_Page, Provenance Working Group W3C, Provenance Working Group W3C, 2011; Freire, J., Koop, D., Santos, E., Silva, C.T., Provenance for computational tasks: A survey (2008) Computing in Science and Engineering, 10 (3), pp. 11-21. , DOI 10.1109/MCSE.2008.79, 4488060; Lim, C., Lu, S., Chebotko, A., Fotouhi, F., Prospective and retrospective provenance collection in scientific workflow environments (2010) IEEE SCC, pp. 449-456. , http://dblp.uni-trier.de/db/conf/IEEEscc/scc2010.html#LimLCF10, IEEE Computer Society URL; Wood, P.T., Query languages for graph databases (2012) ACM SIGMOD Rec., 41, p. 50; Cruz, I.F., Mendelzon, A.O., Wood, P.T., A graphical query language supporting recursion (1987) Proceedings of the 1987 ACM SIGMOD International Conference on Management of Data, pp. 323-330. , SIGMOD '87 ACM New York, NY, USA 10.1145/38713.38749; Consens, M.P., Mendelzon, A.O., Expressing structural hypertext queries in graphlog (1989) Proceedings of the Second Annual ACM Conference on Hypertext, pp. 269-292. , HYPERTEXT'89 ACM New York, NY, USA 10.1145/74224.74247; Güting, R.H., GraphDB: Modeling and querying graphs in databases (1994) Proceedings of the 20th International Conference on Very Large Data Bases, pp. 297-308. , http://dl.acm.org/citation.cfm?id%3D645920.672980, VLDB'94 Morgan Kaufmann Publishers Inc. San Francisco, CA, USA URL; Gyssens, M., Paredaens, J., Den Bussche, J.V., Gucht, D.V., A graph-oriented object database model (1994) IEEE Trans. Knowl. Data Eng., 6, pp. 572-586; Abiteboul, S., Quass, D., McHugh, J., Widom, J., Wiener, J., The Lorel query language for semistructured data (1996) J. Digit. Lib., 1; Fernández, M., Fiorescu, D., Levi, A., Sucin, D., Declarative specification of web sites with STRUDEL (2000) VLDB J., 9, pp. 38-55; Buneman, P., Fernandez, M., Suciu, D., UnQL: A query language and algebra for semistructured data based on structural recursion (2000) VLDB J., 9, pp. 76-110; Weikum, G., Kasneci, G., Ramanath, M., Suchanek, F., Database and information-retrieval methods for knowledge discovery (2009) Commun. ACM, 52, pp. 56-64; Harris, S., Seaborne, A., (2010) {SPARQL} 1.1 Query Language, Working Draft, W3C; Kifor, T., Varga, L.Z., Vazquez-Salceda, J., Alvarez, S., Willmott, S., Miles, S., Moreau, L., Provenance in agent-mediated healthcare systems (2006) IEEE Intelligent Systems, 21 (6), pp. 38-46. , DOI 9D04F813-E31E-416F-99B7-DBC4D177ACA7; Benabdelkader, A., Santcroos, M., Madougou, S., Van Kampen, A.H.C., Olabarriaga, S.D., A provenance approach to trace scientific experiments on a grid infrastructure (2011) EScience, pp. 134-141. , IEEE Computer Society; Anjum, A., Bloodsworth, P., Branson, A., Habib, I., McClatchey, R., Solomonides, T., (2012) Research Traceability Using Provenance Services for Biomedical Analysis, , CoRR abs/1202.5; Hasan, R., Sion, R., Winslett, M., Introducing secure provenance: Problems and challenges (2007) Proceedings of the 2007 ACM Workshop on Storage Security and Survivability, pp. 13-18. , StorageSS'07 ACM New York, NY, USA 10.1145/1314313.1314318; (2010) TRANSFoRm, Translational Medicine and Patient Safety in Europe, , http://www.transformproject.eu; (2011) EHR4CR, Electronic Health Records for Clinical Research, , http://www.ehr4cr.eu; Friedman, C.P., Wong, A.K., Blumenthal, D., Achieving a nationwide learning health system (2010) Sci. Transl. Med., 2. , 57cm29; Iavindrasana, J., Design of a decentralized reusable research database architecture to support data acquisition in large research projects (2007) MedInfo, pp. 325-329; Curcin, V., Danger, R., Kuchinke, W., Miles, S., Taweel, A., Ohmann, C., Provenance model for randomized clinical trials (2012) Data Provenance and Data Management for EScience, 426 VOL.. , Q. Liu, Q. Bai, S. Giugni, D. Williamson, J. Taylor, Studies in Computational Intelligence Springer; Missier, P., Dey, S., Belhajjame, K., Cuevas-Vicenttín, V., Ludäscher, B., D-PROV: Extending the PROV provenance model with workflow structure (2013) Proceedings of the 5th USENIX Workshop on the Theory and Practice of Provenance, pp. 91-97. , http://dl.acm.org/citation.cfm?id%3D2482949.2482961, TaPP'13 USENIX Association Berkeley, CA, USA URL; Bizer, C., D2RQ - Treating non-RDF databases as virtual RDF graphs (2004) Proceedings of the 3rd International Semantic Web Conference, ISWC2004; (2005) Organization for the Advancement of Structured Information Standards, Security Assertion Markup Language, SAML v2.0, , http://www.oasis-open.org/standards#samlv2.0; (2011) The Open Provenance Model, , http://openprovenance.org, OPM; http://www.w3.org/2011/prov/wiki/ProvImplementations, W3C Working Group, Prov implementations, 2013; Ethier, J.F., Dameron, O., Curcin, V., A unified structural/terminological interoperability framework based on LexEVS: Application to TRANSFoRm (2013) Am. Med. Inform. Assoc., 20, pp. 986-994; Keung, S.N.L.C., Zhao, L., Tyler, E., Arvanitis, T.N., Integrated vocabulary service for health data interoperability (2012) The Fourth International Conference on EHealth, Telemedicine, and Social Medicine, pp. 124-127. , http://www.sarahlck.co.uk/files/etelemed2012.pdf, eTELEMED 2012 IARIA Valencia, Spain URL; Miles, S., Groth, P., Munroe, S., Moreau, L., PrIMe: A methodology for developing provenance-aware applications (2011) ACM Trans. Softw. Eng. Methodol., 20, pp. 1-42; Groth, P., Miles, S., Fang, W., Wong, S.C., Zauner, K.-P., Moreau, L., Recording and using provenance in a protein compressibility experiment (2005) Proceedings of the IEEE International Symposium on High Performance Distributed Computing, pp. 201-208. , Proceedings - 14th IEEE Interntional Symposium on High Performance Distributed Computing, HPD-14; Russell, J., Cohn, R., (2012) Neo4j, Book on Demand, , http://books.google.co.uk/books?id%3DEb_GMQEACAAJ; A.P. Chapman, H.V. Jagadish, P. Ramanan, Efficient provenance storage, in: Proceedings of the ACM International Conference on Management of Data, SIGMOD, 2008, pp. 993-1006; Bertino, E., Sandhu, R., Database security - Concepts, approaches, and challenges (2005) IEEE Trans. Dependable Secure Comput., 2, pp. 2-19; Kaushik, S., Wijesekera, D., Ammann, P., Policy-based dissemination of partial web-ontologies (2005) Proceedings of the 2005 Workshop on Secure Web Services, pp. 43-52. , SWS'05 ACM New York, NY, USA 10.1145/1103022.1103030; Carminati, B., Ferrari, E., Heatherly, R., Kantarcioglu, M., Thuraisingham, B., A semantic web based framework for social network access control (2009) Proceedings of the 14th ACM Symposium on Access Control Models and Technologies, pp. 177-186. , SACMAT'09 ACM New York, NY, USA 10.1145/1542207.1542237; Delia, A., Honkola, J., Manzaroli, D., Cinotti, T., Access control at triple level: Specification and enforcement of a simple rdf model to support concurrent applications in smart environments (2011) Smart Spaces and Next Generation Wired/Wireless Networking, 6869 VOL., pp. 63-74. , http://dx.doi.org/10.1007/978-3-642-22875-9_6, S. Balandin, Y. Koucheryavy, H. Hu, Lecture Notes in Computer Science Springer Berlin, Heidelberg URL; Ni, Q., Xu, S., Bertino, E., Sandhu, R., Han, W., An access control language for a general provenance model (2009) Proceedings of the 6th VLDB Workshop on Secure Data Management, pp. 68-88. , http://www.springerlink.com/index/4V1X2374932725G3.pdf, Springer Verlag 10.1007/978-3-642-04219-5-5 URL; Cadenhead, T., Khadilkar, V., Kantarcioglu, M., Thuraisingham, B., A language for provenance access control (2011) Proceedings of the First ACM Conference on Data and Application Security and Privacy, pp. 133-144. , http://doi.acm.org/10.1145/1943513.1943532, CODASPY'11 ACM New York, NY, USA; Tyrone Cadenhead, M.K., Thuraisingham, B., A framework for policies over provenance (2011) 3rd USENIX Workshop on the Theory and Practice of Provenance; Braun, U., Shinnar, A., Seltzer, M., Securing provenance (2008) The 3rd USENIX Workshop on Hot Topics in Security, USENIX HotSec, pp. 1-5. , USENIX Association Berkeley, CA, USA; Sacco, O., Passant, A., Decker, S., An access control framework for the web of data (2011) 2011 IEEE 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 456-463. , http://dx.doi.org/10.1109/TrustCom.2011.59; Stepien, B., Matwin, S., Felty, A.P., Advantages of a non-technical XACML notation in role-based models (2011) PST, pp. 193-200; Helil, N., Rahman, K., Extending XACML profile for RBAC with semantic concepts (2010) 2010 International Conference on Computer Application and System Modeling, ICCASM, 10, pp. V1069-V1074. , http://dx.doi.org/10.1109/ICCASM.2010.5622888; Kounga, G., Mont, M.C., Bramhall, P., Extending XACML access control architecture for allowing preference-based authorisation (2010) Proceedings of the 7th International Conference on Trust, Privacy and Security in Digital Business, pp. 153-164. , http://dl.acm.org/citation.cfm?id%3D1894888.1894907, TrustBus'10 Springer-Verlag Berlin, Heidelberg URL; Dey, S., Zinn, D., Ludaescher, B., Publishing privacy-aware provenance by inventing anonymous nodes (2011) Proceedings of the Fourth International Workshop on REsource Discovery, RED 2011; Dey, S., Zinn, D., Ludäscher, B., ProPub: Towards a declarative approach for publishing customized, policy-aware provenance (2011) Scientific and Statistical Database Management, 6809 VOL., pp. 225-243. , http://dx.doi.org/10.1007/978-3-642-22351-8_13, J. Bayard Cushing, J. French, S. Bowers, Lecture Notes in Computer Science Springer Berlin, Heidelberg URL; Danger, R., Joy, R., Darlington, J., Curcin, V., (2012) Provenance and Annotation of Data and Processes, 7525 VOL., pp. 233-235. , P. Groth, J. Frew, Lecture Notes in Computer Science: Provenance and Annotation of Data and Processes Springer Berlin, Heidelberg RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The provenance of a piece of data refers to knowledge about its origin, in terms of the entities and actors involved in its creation, e.g. data sources used, operations carried out on them, and users enacting those operations. Provenance is used to better understand the data and the context of its production, and to assess its reliability, by asserting whether correct procedures were followed. Providing evidence for validating research is of particular importance in the biomedical domain, where the strength of the results depends on the data sources and processes used. In recent times, previously manual processes have become fully or semi-automated, e.g. clinical trial recruitment, epidemiological studies, diagnosis making. The latter is typically achieved through interactions of heterogeneous software systems in multiple settings (hospitals, clinics, academic and industrial research organisations). Provenance traces of these software need to be integrated in a consistent and meaningful manner, but since these software systems rarely share a common platform, the provenance interoperability between them has to be achieved on the level of conceptual models. It is a non-trivial matter to determine where to start in making a biomedical software system provenance-aware. In this paper, we specify recommendations to developers on how to approach provenance modelling, capture, security, storage and querying, based on our experiences with two large-scale biomedical research projects: Translational Research and Patient Safety in Europe (TRANSFoRm) and Electronic Health Records for Clinical Research (EHR4CR). While illustrated with concrete issues encountered, the recommendations are of a sufficiently high level so as to be reusable across the biomedical domain. © 2013 Elsevier B.V. All rights reserved. ER - TY - JOUR T1 - Utilization profile of the Canadian-led coalition Role 2 Medical Treatment Facility in Iraq: The growing requirement for multinational interoperability A1 - DaCambra, M P A1 - Kao, R L A1 - Berger, C A1 - McAlister, V C Y1 - 2018/// JF - Canadian Journal of Surgery VL - 61 IS - 6 SP - S195 EP - -S202 DO - 10.1503/cjs.015218 N2 - ©2018 Joule Inc. Background: The Canadian Armed Forces deployed a Role 2 Medical Treatment Facility (R2MTF) to Iraq in November 2016 as part of Operation IMPACT. We compared the multinational interoperability required of this R2MTF with that of similar facilities previously deployed by Canada or other nations. Methods: We reviewed data (Nov. 4, 2016, to Oct. 3, 2017) from the electronic Disease and Injury Surveillance Report and the Daily Medical Situation Report. Clinical activity was stratified by Global Burden of Diseases category, ICD-10 code, mechanism of injury, services used, encounter type, nationality and blood product usage. We reviewed the literature to identify utilization profiles for other MTFs over the last 20 years. Results: In total, 1487 patients were assessed. Of these, 5.0% had battle injuries requiring damage-control resuscitation and/or damage-control surgery, with 55 casualties requiring medical evacuation after stabilization. Trauma and disease non-battle injuries accounted for 44% and 51% of patient encounters, respectively. Other than dental conditions, musculoskeletal disorders accounted for most presentations. Fifty-seven units of fresh frozen plasma and 64 units of packed red blood cells were used, and the walking blood bank was activated 7 times. Mass casualty activations involved coordination of health care and logistical resources from more than 12 countries. In addition to host nation military and civilian casualties, patients from 15 different countries were treated with similar frequency. Conclusion: The experience of the Canadian R2MTF in Iraq demonstrates the importance of multinational interoperability in providing cohesive medical care in coalition surgical facilities. Multinational interoperability derives from a unique relationship between higher medical command collaboration, international training and adherence to common standards for equipment and clinical practice. ER - TY - JOUR T1 - How the Continuity of Care Document can advance medical research and public health A1 - D'Amore, J D A1 - Sittig, D F A1 - Ness, R B Y1 - 2012/// KW - Continuity of Patient Care KW - Data Collection KW - Death Certificates KW - Humans KW - Information Systems KW - Medical Informatics KW - Medical Records Systems, Computerized KW - Sentinel Surveillance KW - United States KW - article KW - death certificate KW - electronic medical record KW - human KW - information processing KW - information system KW - methodology KW - organization and management KW - patient care KW - sentinel surveillance JF - American Journal of Public Health VL - 102 IS - 5 SP - E1 EP - E4 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861958557&doi=10.2105%2FAJPH.2011.300640&partnerID=40&md5=07345d906b2522951652d0a11cab4354 N1 - Cited By :13 Export Date: 10 September 2018 References: Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans, , http://www.whitehouse.gov/administration/eop/ostp/pcast, Report to the President. Washington, DC. Accessed December 4, 2011; Grossman, C., Powers, B., McGinnis, J.M., (2011) Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care, , Institute of Medicine. Washington, DC: National Academies Press; Grannis, S.J., Biondich, P.G., Mamlin, B.W., How disease surveillance systems can serve as practical building blocks for a health information infrastructure: The Indiana experience (2005) AMIA Annu Symp Proc., pp. 286-290; (2009) American Recovery and Reinvestment Act of 2009, , Washington, DC: 111th Congress of the United States of America; Blumenthal, D., Tavenner, M., The "meaningful use" regulation for electronic health records (2010) N Engl J Med., 363 (6), pp. 501-504; Ferranti, J.M., Musser, R.C., Kawamoto, K., Hammond, W.E., The clinical document architecture and the continuity of care record: A critical analysis (2006) J Am Med Inform Assoc., 13 (3), pp. 245-252; Certified Health Information Technology Product List, , http://onc-chpl.force.com/ehrcert, Accessed December 4, 2011; Health information technology: Initial set of standards Implementation Specifications, and Certification Criteria for Electronic Health Record Technology, , US Department of Health and Human Services. Washington DC: Office of the National Coordinator for Health Information Technology. Regulation Identification No. 0991-AB58; Harris, C.D., Pan Lmukhtar, Q., Changes in receiving preventive care services among US adults with diabetes, 1997-2007 (2010) Prev Chronic Dis., 7 (3), pp. A56; Steinbrook, R., Facing the diabetes epidemic - Mandatory reporting of glycosylated hemoglobin values in New York City (2006) New England Journal of Medicine, 354 (6), pp. 545-548. , http://content.nejm.org/cgi/reprint/354/6/545.pdf, DOI 10.1056/NEJMp068008; Cebul, R.D., Love, T.E., Jain, A.K., Hebert, C.J., Electronic health records and quality of diabetes care (2011) N Engl J Med., 365 (9), pp. 825-833; Graham, D.J., Campen, D., Hui, R., Spence, M., Cheetham, C., Levy, G., Shoor, S., Ray, W.A., Risk of acute myocardial infarction and sudden cardiac death in patients treated with cyclo-oxygenase 2 selective and non-selective non-steroidal anti-inflammatory drugs: Nested case-control study (2005) Lancet, 365 (9458), pp. 475-481. , DOI 10.1016/S0140-6736(05)17864-7; Lenzer, J., FDA is incapable of protecting US "against another Vioxx." (2004) BMJ, 329 (7477), p. 1253; Woodcock, J., Behrman, R.E., Dal Pan, G.J., Role of postmarketing surveillance in contemporary medicine (2011) Annu Rev Med., 62, pp. 1-10; http://www.health.state.ny.us/diseases/communicable/influenza/ surveillance/ilinet_program, New York State Department of Health. Accessed December 4, 2011; Schirmer, P., Lucero, C., Oda, G., Lopez, J., Holodniy, M., Effective detection of the 2009 H1N1 influenza pandemic in U.S. Veterans Affairs medical centers using a national electronic biosurveillance system (2010) PLoS One, 5 (3), pp. e9533; Nass, S., (2009) Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research, , Institute of Medicine. Washington, DC: National Academies Press; An Open Source Population Health Reporting Prototype, , http://projectpophealth.org/index.html, Accessed December 4, 2011; Adler-Milstein, J., Bates, D.W., Jha, A.K., A survey of health information exchange organizations in the United States: Implications for meaningful use (2011) Ann InternMed., 154 (10), pp. 666-671; Brown, J.S., Holmes, J.H., Shah, K., Hall, K., Lazarus, R., Platt, R., Distributed health data networks: A practical and preferred approach to multi-institutional evaluations of comparative effectiveness, safety, and quality of care (2010) Med Care., 48 (6 SUPPL.), pp. S45-S51; Sittig, D.F., Joe, J.C., Toward a statewide health information technology center (abbreviated version) (2010) South Med J., 103 (11), pp. 1111-1114; Elmendorf, D.W., (2009) Letter to the Honorable Charles B. Rangel, , http://www.cbo.gov/ftpdocs/99xx/doc9966/HITECHRangelLtr.pdf, January 21. Accessed December 4, 2011; D'amore, J.D., Sittig, D.F., Wright, A., Iyengar, M.S., Ness, R.B., The Promise of the CCD: Challenges and opportunity for quality improvement and population health (2011) AMIA Annu Symp Proc., pp. 285-294; Blumenthal, D., Launching HITECH (2010) N Engl J Med., 362 (5), pp. 382-385 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Electronic health records in the United States currently isolate digital information in proprietary, institutional databases. Experts have identified inadequate data exchange as a leading challenge to advancements in care quality and efficiency. Recent federal health information technology incentives adopt an extensible standard, called the Continuity of Care Document (CCD), as a new basis for digital interoperability. Although this instrument was designed for individual provider communications, the CCD can be effectively reused for population- based research and public health. Three examples in this commentary demonstrate the potential of CCD aggregation and highlight required changes to existing public health and research practices. Transitioning to the use of this new interoperability standard should be a priority for public health investment, research, and development. ER - TY - JOUR T1 - Standards and specifications in pathology: Image management, report management and terminology A1 - Daniel, C A1 - Booker, D A1 - Beckwith, B A1 - Mea, V D A1 - García-Rojo, M A1 - Havener, L A1 - Kennedy, M A1 - Klossa, J A1 - Laurinavicius, A A1 - Macary, F A1 - Punys, V A1 - Scharber, W A1 - Schrader, T Y1 - 2012/// KW - Anatomic pathology KW - Clinical Document Architecture (CDA) KW - DICOM KW - Decision Making, Computer-Assisted KW - Diagnostic Imaging KW - France KW - HL7 KW - Hospital Information System KW - Hospital Information Systems KW - Humans KW - IHE KW - Image Processing, Computer-Assisted KW - Laboratory Information System KW - Medical Informatics KW - North America KW - PACS KW - Spain KW - Systems Integration KW - Telepathology KW - Terminology as Topic KW - Vocabulary, Controlled KW - article KW - decision support system KW - diagnostic imaging KW - hospital information system KW - human KW - image processing KW - interoperability KW - linguistics KW - medical informatics KW - methodology KW - nomenclature KW - semantic interoperability KW - standard KW - standards KW - system analysis KW - telepathology KW - terminology KW - whole slide image JF - Studies in Health Technology and Informatics VL - 179 SP - 105 EP - 122 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84872113933&doi=10.3233%2F978-1-61499-086-4-105&partnerID=40&md5=6f861bb678fdc13f053776673a83f1de N1 - Cited By :8 Export Date: 10 September 2018 References: Integrating the Healthcare Enterprise (IHE), , http://www.ihe.net; Daniel, C., Macary, F., García-Rojo, M., Klossa, J., Laurinavičius, A., Beckwith, B.A., Della Mea, V., Recent advances in standards for collaborative digital anatomic pathology (2011) Diagn Pathol, 6 SUPPL 1, pp. S17. , 30 March 2011; Daniel, C., García-Rojo, M., Schrader, T., Della Mea, V., Gilbertson, J., Beckwith, B.A., Standards to support information systems integration in anatomic pathology (2009) Arch Pathol Lab Med, 133 (11), pp. 1841-1849; IHE Anatomic Pathology Technical Framework, 1, pp. 11-24. , http://www.ihe.net/Technical_Framework#pathology, IHE. (PAT TF-1): Profiles -2008; IHE Anatomic Pathology Technical Framework, 2, pp. 11-24. , http://www.ihe.net/Technical_Framework#pathology, IHE. (PAT TF-2) : Transactions -2008; Della Mea, V., 25 years of telepathology research: A bibliometric analysis (2011) Diagn Pathol, 6 SUPPL 1, pp. S26. , 30 March 2011; García-Rojo, M., Daniel, C., Digital pathology and virtual microscopy integration in e-health records (2010) Ubiquitous Health and Medical Informatics: The Ubiquity 2.0 Trend and beyond, pp. 457-484. , S. Mohammed, J. Fiaidhi J (edrs.) , IGI Global, PA, USA; García-Rojo, M., Rolón, E., Calahorra, L., García, F.O., Sánchez, R.P., Ruiz, F., Ballester, N., Espartero, R.M., Implementation of the business process modelling notation (BPMN) in the modelling of anatomic pathology processes (2008) Diagn Pathol, 3 SUPPL 1, pp. S22. , 15 July 2008; Nakhleh, R.E., Patient safety and error reduction in surgical pathology (2008) Arch Pathol Lab Med, 132 (2), pp. 181-185. , February 2008; Goldsmith, J.D., Siegal, G.P., Suster, S., Wheeler, T.M., Brown, R.W., Reporting guidelines for clinical laboratory reports in surgical pathology (2008) Arch Pathol Lab Med, 132 (10), pp. 1608-1616. , October 2008; Leslie, K.O., Rosai, J., Standardization of the surgical pathology report: Formats, templates, and synoptic reports (1994) Semin Diagn Pathol, 11 (4), pp. 253-257; http://www.cap.org, CAP Cancer Protocols and Checklists; http://sfpathol.org, INCa SFP items minimaux; http://www.rcpa.edu.au/Publications/StructuredReporting/, RCPA Cancer protocols; SNOMED Clinical Terms Technical Implementation Guide, , http://www.ihtsdo.org/fileadmin/user_upload/Docs_01/ SNOMED_CT_Publications/SNOMED_CT_Technical_Implementation_Guide_20090131.pdf, IHTSDO; Brown, P.J., Sönksen, P., Evaluation of the quality of information retrieval of clinical findings from a computerized patient database using a semantic terminological model (2000) J Am Med Inform Assoc, 7 (4), pp. 392-403. , Jul-Aug 2000; European Network of Telepathology, , http://www.conganat.org/eurotelepath/, COST Action IC0604EURO-TELEPATH; http://medical.nema.org/, NEMA. DICOM (Digital Communications in Medicine); http://www.hl7.org/, HL7 Organization HL7 (Health Level 7); Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P., Hl7 clinical document architecture, release 2 (2006) J Am Med Inform Assoc, 13 (1), pp. 30-39; hftp://medical.nema.org/medical/dicom/final/sup122_ft2.pdf, DICOM Supplement 122: Specimen Module and Revised Pathology SOP Classes; hftp://medical.nema.org/medical/dicom/supps/sup145_09.pdf, DICOM Supplement 145: Whole Slide Microscopic Image IOD and SOP Classes; Peces, C., García-Rojo, M., Sacristán, J., Gallardo, A.J., Rodríguez, A., Serendipia: Castilla-la mancha telepathology network (2008) Diagn Pathol, 3 SUPPL 1, pp. S5. , 15 July 2009; García-Rojo, M., Castro, A.M., Gonçalves, L., COST Action "euroTelepath": Digital pathology integration in electronic health record, including primary care centres (2011) Diagn Pathol, 6 SUPPL 1, pp. S6. , 30 March 2011; International Health Terminology Standards Development Organisation, , http://www.ihtsdo.org/snomed-ct/, SNOMED CT (Systematized Nomenclature of Medicine-Clinical Terms); Rosenbloom, S.T., Miller, R.A., Johnson, K.B., Interface terminologies: Facilitating direct entry of clinical data into electronic health record systems (2006) J Am Med In-form Assoc, 13 (3), pp. 277-288. , May-June 2006; Rosenbloom, S.T., Brown, S.H., Froehling, D., Bauer, B.A., Wahner-Roedler, D.L., Gregg, W.M., Elkin, P.L., Using SNOMED CT to represent two interface terminologies (2009) J Am Med Inform Assoc, 16 (1), pp. 81-88. , Jan-Feb 2009; Rector, A.L., Clinical terminology: Why is it so hard? (1999) Methods Inf Med, 38 (4-5), pp. 239-252. , Dec 1999; Benson, T., (2009) Principles of Health Interoperability HL7 and SNOMED, , SpringerVerlag, London, Dordrecht, Heidelberg, New York; Daniel, C., Buemi, A., Mazuel, L., Ouagne, D., Charlet, J., Functional requirements of terminology services for coupling interface terminologies to reference terminologies (2009) Medical Informatics in A United and Healthy Europe -Proceedings of MIE, 150, pp. 205-209. , K.-P. Adlassnig, B. Blobel, J. Mantas, I. Masic (Edrs.) , Series Studies in Health Technology and Informatics. IOS Press, Amsterdam, Berlin, Oxford, Tokyo, Washington 2009 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - For making medical decisions, healthcare professionals require that all necessary information is both correct and easily available. Collaborative Digital Anatomic Pathology refers to the use of information technology that supports the creation and sharing or exchange of information, including data and images, during the complex workflow performed in an Anatomic Pathology department from specimen reception to report transmission and exploitation. Collaborative Digital Anatomic Pathology is supported by standardization efforts toward knowledge representation for sharable and computable clinical information. The goal of the international integrating the Healthcare Enterprise (IHE) initiative is precisely specifying how medical informatics standards should be implemented to meet specific health care needs and making systems integration more efficient and less expensive. The IHE Anatomic Pathology initiative was launched to implement the best use of medical informatics standards in order to produce, share and exchange machine-readable structured reports and their evidences (including whole slide images) within hospitals and across healthcare facilities. DICOM supplements 122 and 145 provide flexible object information definitions dedicated respectively to specimen description and WSI acquisition, storage and display. The profiles 'Anatomic Pathology Reporting for Public Health' (ARPH) and 'Anatomic Pathology Structured Report' (APSR) provide standard templates and transactions for sharing or exchanging structured reports in which textual observations - encoded using PathLex, an international controlled vocabulary currently being mapped to SNOMED CT concepts - may be bound to digital images or regions of interest in images. Current implementations of IHE Anatomic Pathology profiles in North America, France and Spain demonstrate the applicability of recent advances in standards for Collaborative Digital Anatomic Pathology. The use of machine-readable format of Anatomic Pathology information supports the development of computer-based decision support as well as secondary use of Anatomic Pathology information for research or public health.© 2012 The authors and IOS Press. All rights reserved. ER - TY - JOUR T1 - Information technology for clinical, translational and comparative effectiveness research. Findings from the section clinical research informatics A1 - Daniel, C A1 - Choquet, R Y1 - 2014/// KW - Biomedical Research KW - Clinical research KW - Comparative Effectiveness Research KW - Electronic Health Records KW - Humans KW - Informatics KW - International Medical Informatics Association KW - Medical Informatics KW - Medical informatics KW - Nursing Research KW - Patient Selection KW - Pharmacovigilance KW - Phenotype KW - Phenotyping KW - Translational Medical Research KW - comparative effectiveness KW - electronic health record KW - human KW - medical informatics KW - medical research KW - translational research KW - yearbook JF - Yearbook of medical informatics VL - 9 SP - 224 EP - 227 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017318536&doi=10.15265%2FIY-2014-0040&partnerID=40&md5=6e80680d26e73764fb4982ed5bef93a0 N1 - Cited By :1 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - OBJECTIVE: To select and summarize key contributions to current research in the field of Clinical Research Informatics (CRI). METHOD: A bibliographic search using a combination of MeSH and free terms search over PubMed was performed followed by a blinded review. RESULTS: The review process resulted in the selection of four papers illustrating various aspects of current research efforts in the area of CRI. The first paper tackles the challenge of extracting accurate phenotypes from Electronic Healthcare Records (EHRs). Privacy protection within shared de-identified, patient-level research databases is the focus of the second selected paper. Two other papers exemplify the growing role of formal representation of clinical data - in metadata repositories - and knowledge - in ontologies - for supporting the process of reusing data for clinical research. CONCLUSIONS: The selected articles demonstrate how concrete platforms are currently achieving interoperability across clinical research and care domains and have reached the evaluation phase. When EHRs linked to genetic data have the potential to shift the research focus from research driven patient recruitment to phenotyping in large population, a key issue is to lower patient re-identification risks for biomedical research databases. Current research illustrates the potential of knowledge engineering to support, in the coming years, the scientific lifecycle of clinical research. ER - TY - JOUR T1 - Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services. A1 - Daniel, Christel A1 - Ouagne, David A1 - Sadou, Eric A1 - Forsberg, Kerstin A1 - Gilchrist, Mark Mc A1 - Zapletal, Eric A1 - Paris, Nicolas A1 - Hussain, Sajjad A1 - Jaulent, Marie-Christine A1 - Md, Dipka Kalra Y1 - 2016/// KW - Biomedical Research KW - Data Integration and Standardization KW - Electronic Health Records KW - Emigration and Immigration KW - Interoperability KW - Knowledge representation KW - Semantics KW - Terminology as Topic PB - American Medical Informatics Association JF - AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science VL - 2016 SP - 51 EP - 59 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data. ER - TY - JOUR T1 - The DM-scope registry: A rare disease innovative framework bridging the gap between research and medical care A1 - De Antonio, M A1 - Dogan, C A1 - Daidj, F A1 - Eymard, B A1 - Puymirat, J A1 - Mathieu, J A1 - Gagnon, C A1 - Katsahian, S A1 - Arne Bes, M C A1 - Attarian, S A1 - Hamroun, D A1 - Bassez, G Y1 - 2019/// JF - Orphanet Journal of Rare Diseases VL - 14 IS - 1 DO - 10.1186/s13023-019-1088-3 N2 - ©2019 The Author(s). Background: The relevance of registries as a key component for developing clinical research for rare diseases (RD) and improving patient care has been acknowledged by most stakeholders. As recent studies pointed to several limitations of RD registries our challenge was (1) to improve standardization and data comparability; (2) to facilitate interoperability between existing RD registries; (3) to limit the amount of incomplete data; (4) to improve data quality. This report describes the innovative concept of the DM-Scope Registry that was developed to achieve these objectives for Myotonic Dystrophy (DM), a prototypical example of highly heterogeneous RD. By the setting up of an integrated platform attractive for practitioners use, we aimed to promote DM epidemiology, clinical research and patients care management simultaneously. Results: The DM-Scope Registry is a result of the collaboration within the French excellence network established by the National plan for RDs. Inclusion criteria is all genetically confirmed DM individuals, independently of disease age of onset. The dataset includes social-demographic data, clinical features, genotype, and biomaterial data, and is adjustable for clinical trial data collection. To date, the registry has a nationwide coverage, composed of 55 neuromuscular centres, encompassing the whole disease clinical and genetic spectrum. This widely used platform gathers almost 3000 DM patients (DM1 n = 2828, DM2 n = 142), both children (n = 322) and adults (n = 2648), which accounts for >20% of overall registered DM patients internationally. The registry supported 10 research studies of various type i.e. observational, basic science studies and patient recruitment for clinical trials. Conclusion: The DM-Scope registry represents the largest collection of standardized data for the DM population. Our concept improved collaboration among health care professionals by providing annual follow-up of quality longitudinal data collection. The combination of clinical features and biomolecular materials provides a comprehensive view of the disease in a given population. DM-Scope registry proves to be a powerful device for promoting both research and medical care that is suitable to other countries. In the context of emerging therapies, such integrated platform contributes to the standardisation of international DM research and for the design of multicentre clinical trials. Finally, this valuable model is applicable to other RDs. ER - TY - CONF T1 - Public electronic health record platform compliant with the ISO EN13606 standard as support to research groups A1 - de Madariaga, R S A1 - Tello, J C A1 - Carrero, A M A1 - Gil, O M A1 - Aza, I V A1 - Serrano, A C A1 - Cristóbal, R S Y1 - 2014/// KW - Artificial intelligence KW - Biochemical engineering KW - Clinical care KW - Clinical care continuity KW - Clinical decision support systems KW - Clinical information KW - Decision support systems KW - Design and implementations KW - Electronic health record KW - Hospitals KW - ISO EN13606 standard KW - Interoperability KW - Medical computing KW - Medical data mining KW - Records management KW - Research KW - Secondary research development KW - Secondary researches KW - Semantic interoperability KW - Semantics VL - 41 SP - 1254 EP - 1257 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891309103&doi=10.1007%2F978-3-319-00846-2_310&partnerID=40&md5=01b446ab94d4f804c3fd9662b66e040b N1 - Export Date: 10 September 2018 References: 356: E-Health - Making Health Care Better For European Citizens: An Action Plan For a European E-Health Area, , Commission of the European Communities - COM, European Union, Publications Office. Brussels, 2004-04-30 2004; (2004) Development and Adoption of a National Health Information Network (NHIN); Request For Information, 9, p. 2. , US Department of Health and Human Services, Nov; Sim, I., Gorman, P., Greenes, R.A., Haynes, R.B., Kaplan, B., Lehmann, H., Tang, P.C., Clinical decision support systems for the practice of evidence-based medicine (2001) J Am Med Inform Assoc, 8, pp. 527-534; Giannopoulo, E.G., (2008) Data Mining In Medical and Biological Research, , In-Teh; Muñoz, A., Somolinos, R., Pascual, M., Fragua, J.A., González, M.A., Monteagudo, J.L., Proof-of-concept design and development of an EN13606-based electronic health care record service (2007) J.Am.Med.Inform.Assoc, 14 (1), pp. 118-129; Muñoz, A., (2007) Interoperabilidad Semántica Entre Los Modelos De Historia Clínica Electrónica De CEN Y HL Propuesta De Un Modelo De Armonización, , Tesis Doctoral. Universidad Politécnica de Madrid; Carrero, M.A., del Pozo Guerrero, F., Salvador, H.C., Llull, T.F., Monserrat, F.P., (2006) Diseño de una pasarela HL7/EN 13606 para el intercambio de información de Telemonitorización domiciliaria de pacientes, , XXIV Congreso Anual De La Sociedad Española De Ingeniería Biomédica; Schloeffel, P., Beale, T., Hayworth, G., Heard, S., Leslie, H., The relationship between CEN 13606 (2006) HL7 and OpenEHR, , HIC 2006, Sydney, Australia; Tello, C.J., Carrero, M.A., de Madariaga, S.R., Serrano, C.A.L., Aza, V.I., Cristóbal, S.R., Plataforma de Visualización de Extractos conforme a la norma UNE-EN ISO 13606. Caso práctico (2011) OpenHealth Spain; Rector, A., Qamar, R., Marley, T., Binding ontologies and coding systems to Electronic Health Records and messages (2006) Proceedings KR-MED, pp. 11-19; Beale, T., (2002) Archetypes: Constraints-based Domain Models For Futureproof Information Systems, , http://www.openehr.org/files/publications/archetypes/archetypes_beale_oopsla_2002.pdf, (accessed April 2013); http://amaltea.telemedicina.isciii.es/interServer/; Cristóbal, R.S., Carrero, M.A., Carrasco, P.M., Rodríguez, M.C., Méndez, J.A., de Mingo, M.A.G., Tello, J.C., Pérez, M.E.H., Sistema anonimizador conforme a la norma UNE-EN ISO 13606 (2012) CASEIB; Witten, I.H., Frank, E., Mark, A.H., (2011) Data Mining Practical Machine Learning Tools and Techniques, , Third Edition, Elsevier; Health Informatics Privilege Management and Access Contro Implementations, , ISO/DIS 22600-3; (2013) eXtensible Access Control Markup Language (XACML), , https://www.oasis-open.org/committees/tc_home.php?wg_abbrev=xacml, (accessed April; Chomsiri, T., HTTPS Hacking Protection (2007) 21st International Conference on Advanced Infromation Networking and Applications Workshops, pp. 590-594. , AINAW'07; Lin, T.-P., The Analysis of Advantages and Disadvantages of the Network Sniffer Behavior Journal of Sanming University 2008-02; de Madariaga, S.R., Muñoz, A., Cáceres, J., Somolinos, R., Pascual, M., Martínez, I., Salvador, C.H., Monteagudo, J.L., ccML, a new markup language to improve ISO/EN 13606-based Electronic Health Record extracts practical edition (2013) J Am Med Inform Assoc (JAMIA), 20, pp. 298-304. , 10.1136/amiajnl-2011-000722; de Madariaga, S.R., Cáceres, J., Somolinos, R., Castro, A., Merino, L.M., Velázquez, I., Muñoz, A., miML, un nuevo lenguaje de marcado diseñado para la edición práctica de Historia Clínica Electrónica según la norma UNE-EN ISO 13606 (2012) XV Congreso Nacional De Informática De La Salud, , Inforsalud 2012. Madrid, 20-22 de marzo de 2012 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This paper presents the design and implementation of a new platform compliant with the ISO EN- 13606 standard which facilitates semantic interoperability between clinical platforms. The presented work forms a point of convergence of clinical information originating in distinct institutions such as hospitals, primary attention centers, etc. It enables clinical care continuity, Electronic Health Record (EHR) realistic and practical edition, clinical decision support systems development and secondary research development using medical data mining. The Telemedicine and e-Health Research Unit at the Instituto de Salud Carlos III, as a public institution, has developed this platform allowing its use as support to other research groups and taking one step closer to everyday generalized use of EHRs in hospitals, healthcare and research centers. © Springer International Publishing Sw itzerland 2014. ER - TY - JOUR T1 - Bridging Data Models and Terminologies to Support Adverse Drug Event Reporting Using EHR Data A1 - Declerck, G. A1 - Hussain, S. A1 - Daniel, C. A1 - Yuksel, M. A1 - Laleci, G. B. A1 - Twagirumukiza, M. A1 - Jaulent, M. -C. Y1 - 2015/01// KW - EHR data models KW - Focus Theme KW - Original Articles KW - secondary use of EHR KW - semantic interoperability PB - Schattauer GmbH JF - Methods of Information in Medicine VL - 54 IS - 01 SP - 24 EP - 31 DO - 10.3414/ME13-02-0025 UR - http://www.thieme-connect.de/DOI/DOI?10.3414/ME13-02-0025 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Declerck et al. - 2015 - Bridging Data Models and Terminologies to Support Adverse Drug Event Reporting Using EHR Data.pdf N2 -Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”.
ER - TY - CONF T1 - Improvement of cross-sector communication in the integrated health environment A1 - Demski, H A1 - Hildebrand, C A1 - Brass, A A1 - Jedamzik, S A1 - Engelbrecht, R Y1 - 2010/// KW - Computer Communication Networks KW - Continuity of Patient Care KW - EN13606 KW - Humans KW - Information Dissemination KW - Medical Informatics KW - Medical Record Linkage KW - archetype KW - computer network KW - conference paper KW - electronic health record KW - human KW - information dissemination KW - medical record KW - methodology KW - organization and management KW - patient care KW - semantic interoperability KW - standard KW - standardization VL - 155 SP - 95 EP - 100 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954608549&doi=10.3233%2F978-1-60750-563-1-95&partnerID=40&md5=3c124011c388f0ae1725ddb8935a3059 N1 - Cited By :5 Export Date: 10 September 2018 References: Blobel, B.G.M.E., Engel, K., Pharow, P., Semantic interoperability: HL7 version 3 compared to advanced architecture standards (2006) Methods of Information in Medicine, 45 (4), pp. 343-353; (2007) EN 13606: Health Informatics - Electronic Health Record Communication Part 1-4, , CEN-European Committee for Standardization; Garde, S., Hovenga, E., Buck, J., Knaup, P., Expressing Clinical Data Sets with openEHR Archetypes: A Solid Basis for Ubiquitous Computing International Journal of Medical Informatics, 76 (S3), pp. 334-341; Stroetmann, V., Kalra, D., Lewalle, P., Rector, A., Rodrigues, J.M., Stroetmann, K.A., Surjan, G., Zanstra, P.E., (2009) Semantic Interoperability for Better Health and Safer Healthcare, , Office, for Official Publications of the European Communities, Luxembourg; Leslie, H., Heard, S., Garde, S., McNicoll, I., Engaging clinicians in clinical content: Herding cats or piece of cake? (2009) Series Studies in Health Technology and Informatics, 150, pp. 125-129. , Adlassnig K-P, Blobel B, Mantas J, Masic I (Edrs.) Medical Informatics in a United and Healthy Europe - Proceedings of MIE 2009, IOS Press, Amsterdam, Berlin, Oxford, Tokyo, Washington; (2006) Standard Specification for Continuity of Care Record (CCR), , ASTM E2369, ASTM International, West Conshohocken; Moner, D., Maldonado, J.A., Boscá, D., Fernández-Breis, J.T., Angulo, C., Crespo, P., Vivancos, P.J., Robles, M., Archetype-Based Semantic Integration and Standardization of Clinical Data 28th Anual International Conference IEEE Engineering in Medicine and Biology, New York (2006); Rinner, C., Wrba, T., Duftschmid, G., Publishing relational medical data as prEN 13606 Archetype compliant EHR extracts using XML technologies (2007) Tagungsband der EHealth 2007 - Medical Informatics Meets EHealth, p. 3539. , Vienna; Birkmann, C., Demski, H., Engelbrecht, R., Introducing patient cards in clinical routine: Evaluation of two research projects (2006) Methods of Information in Medicine, 45 (1), pp. 73-78; EC Pilot on EHealth Indicators: Benchmarking ICT Use among General Practitioners in Europe, Final Report, p. 8. , http://ec.europa.eu/information_society/eeurope/i2010/docs/benchmarking/ gp_survey_final_report.pdf.(lastaccessed:23March2010) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Patient care is a complex process with different providers located in various institutions co-operating within an integrated health environment. In spite of technical improvements in medical care, patient information is usually exchanged by paper. Digital and timely communication between regional care providers can improve the exchange of information. Different systems and missing data standards are challenges that have to be met. ByMedConnect, a project sponsored by the Bavarian State Ministry of the Environment and Public Health, develops and demonstrates a communication solution based on the EN 13606 standard. In a first step the dataset, which will be exchanged by the care providers, is defined. ByMedConnect develops the dataset in cooperation with practicing clinicians and converts it via modeling tools into archetypes that provide the base for reliable cross-sector communication. Existing heterogeneous systems are integrated via a dedicated module that transforms legacy data into a normalized representation. Information provided in a standardized form thereby enables semantic interoperability between different systems and allows medical add-on applications to connect. A secure digital communication network guarantees easy and direct data sharing. ByMedConnect aims to evaluate the achieved theoretical preliminary work in practice and to draft approaches, which can be applied beyond the pilot application. © 2010 European Federation for Medical Informatics. All rights reserved. ER - TY - JOUR T1 - The long road to semantic interoperability in support of public health: Experiences from two states A1 - Dixon, Brian E. A1 - Vreeman, Daniel J. A1 - Grannis, Shaun J. Y1 - 2014/06// KW - Infectious disease reporting KW - Meaningful use KW - Medical Informatics KW - Medical informatics KW - Public Health KW - Public health informatics KW - Public policy KW - Semantics KW - health care policy KW - health care quality KW - health survey KW - human KW - medical informatics KW - medical information system KW - note KW - priority journal KW - public health KW - reimbursement KW - semantics KW - standard PB - Academic Press JF - Journal of Biomedical Informatics VL - 49 SP - 3 EP - 8 DO - 10.1016/j.jbi.2014.03.011 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902544777&doi=10.1016%2Fj.jbi.2014.03.011&partnerID=40&md5=912a196aadebdfe279a0e21236f29947 UR - https://www.sciencedirect.com/science/article/pii/S1532046414000781?via%3Dihub L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Dixon, Vreeman, Grannis - 2014 - The long road to semantic interoperability in support of public health Experiences from two states.pdf N1 - From Duplicate 1 (The long road to semantic interoperability in support of public health: Experiences from two states - Dixon, B E; Vreeman, D J; Grannis, S J) Cited By :19 Export Date: 5 April 2018 N2 - Proliferation of health information technologies creates opportunities to improve clinical and public health, including high quality, safer care and lower costs. To maximize such potential benefits, health information technologies must readily and reliably exchange information with other systems. However, evidence from public health surveillance programs in two states suggests that operational clinical information systems often fail to use available standards, a barrier to semantic interoperability. Furthermore, analysis of existing policies incentivizing semantic interoperability suggests they have limited impact and are fragmented. In this essay, we discuss three approaches for increasing semantic interoperability to support national goals for using health information technologies. A clear, comprehensive strategy requiring collaborative efforts by clinical and public health stakeholders is suggested as a guide for the long road towards better population health data and outcomes. © 2014 . ER - TY - JOUR T1 - Implementing GermWatcher, an enterprise infection control application. A1 - Doherty, J A1 - Noirot, L A A1 - Mayfield, J A1 - Ramiah, S A1 - Huang, C A1 - Dunagan, W C A1 - Bailey, T C Y1 - 2006/// KW - Expert Systems KW - Hospital Information Systems KW - Humans KW - Infection Control KW - Internet KW - Microbiological Techniques KW - Programming Languages KW - Software KW - article KW - computer language KW - computer program KW - expert system KW - hospital information system KW - human KW - infection control KW - microbiological examination JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium SP - 209 EP - 213 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-34748850020&partnerID=40&md5=b5cddcf7ed0350f11498f6897b1dd9a1 N1 - Cited By :8 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Automated surveillance tools can provide significant advantages to infection control practitioners. When stored in a relational database, the data collected can also be used to support numerous research and quality improvement opportunities. A previously described electronic infection control surveillance system was remodeled to provide multi-hospital support, an XML based rule set, and interoperability with an enterprise terminology server. This paper describes the new architecture being used at hospitals across BJC HealthCare. ER - TY - JOUR T1 - Software application profile: Opal and mica: Open-source software solutions for epidemiological data management, harmonization and dissemination A1 - Doiron, D A1 - Marcon, Y A1 - Fortier, I A1 - Burton, P A1 - Ferretti, V Y1 - 2017/// KW - Canada KW - Database Management Systems KW - Epidemiologic Studies KW - Humans KW - Information Dissemination KW - Internet KW - Software KW - database management system KW - epidemiology KW - human KW - information dissemination KW - procedures KW - software JF - International Journal of Epidemiology VL - 46 IS - 5 SP - 1372 EP - 1378 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040715213&doi=10.1093%2FIJE%2FDYX180&partnerID=40&md5=77a323a3dc0e26da1f0aea0fc757b467 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Doiron et al. - 2017 - Software application profile Opal and mica Open-source software solutions for epidemiological data management, ha.pdf N1 - Cited By :3 Export Date: 10 September 2018 References: Castillo, T., Gregory, A., Moore, S., (2014) Enhancing Discoverability of Public Health and Epidemiology Research Data, , London: Wellcome Trust; Thompson, A., Thinking big: large-scale collaborative research in observational epidemiology (2009) Eur J Epidemiol, 24, pp. 727-731; Piwowar, H.A., Becich, M.J., Bilofsky, H., Crowley, R.S., Towards a data sharing culture: recommendations for leadership from academic health centers (2008) PLoS Med, 5, pp. 1315-1319; Walport, M., Brest, P., Sharing research data to improve public health (2011) Lancet, 377, pp. 537-539; Roger, V.L., Boerwinkle, E., Crapo, J.D., Strategic transformation of population studies: recommendations of the working group on epidemiology and population sciences from the National Heart, Lung, and Blood Advisory Council and Board of External Experts (2015) Am J Epidemiol, 181, pp. 363-368; Murtagh, M.J., Turner, A., Minion, J.T., Fay, M., Burton, P.R., International data sharing in practice: new technologies meet old governance (2016) Biopreserv Biobank, 14, pp. 231-240; Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J.J., The FAIR Guiding Principles for scientific data management and stewardship (2016) Sci Data, 3; (2016), https://www.icpsr.umich.edu/, (19 December 2016, date last accessed); (2017), https://www.cessda.eu, (17 August 2017, date last accessed); Michener, W.K., Allard, S., Budden, A., Participatory design of DataONE-Enabling cyberinfrastructure for the biological and environmental sciences (2012) Ecol Inform, 11, pp. 5-15; Wichmann, H.-E., Kuhn, K.A., Waldenberger, M., Comprehensive catalog of European biobanks (2011) Nat Biotechnol, 29, pp. 795-797; (2016) CLOSER-Promoting Excellence in Longitudinal Research, , http://www.closer.ac.uk/, (21 December 2016, date last accessed); Gehring, U., Casas, M., Brunekreef, B., Environmental exposure assessment in European birth cohorts: results from the ENRIECO project (2013) Environ Health, 12, p. 8; (2016) CLS-Centre for Longitudinal Studies, , http://www.cls.ioe.ac.uk/, (21 December 2016, date last accessed); (2016) UK BiobankData Showcase, , http://www.ukbiobank.ac.uk/data-showcase/, (2 February 2017, date last accessed); Bickerstaffe, A., Ranaweera, T., Endersby, T., The Ark: a customizable web-based data management tool for health and medical research (2017) Bioinformatics, 33, pp. 624-626; Harris, P.A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., Conde, J.G., Research electronic data capture (REDCap)-a metadata-driven methodology and workflow process for providing translational research informatics support (2009) J Biomed Inform, 42, pp. 377-381; (2017) Electronic Data Capture, Randomization and Patient Engagement Made Easy, , https://www.openclinica.com/, (25 May 2017, date last accessed); Crosas, M., The Dataverse NetworkVR: An open-source application for sharing, discovering and preserving data (2011) d-lib magazine, 17, pp. 1-2; (2016) Nesstar, , http://www.nesstar.com/, (21 December 2016, date last accessed); (2016) CKAN-The Open Source Data Portal Software, , http://ckan.org/, (20 December 2016, date last accessed); (2015) NADA Microdata Cataloguing Tool, , http://www.ihsn.org/home/software/nada, (19 December 2016, date last accessed); Pang, C., van Enckevort, D., de Haan, M., MOLGENIS/connect: a system for semi-automatic integration of heterogeneous phenotype data with applications in biobanks (2016) Bioinformatics, 32, pp. 2176-2183; Winters, K., Netscher, S., Proposed standards for variable harmonization documentation and referencing: a case study using QuickCharmStats 1.1 (2016) PLoS One, 11; Fortier, I., Raina, P., Van den Heuvel, E.R., Maelstrom Research guidelines for rigorous retrospective data harmonization (2017) Int J Epidemiol, 46, pp. 103-105; Wolfson, M., Wallace, S.E., Masca, N., DataSHIELD: resolving a conflict in contemporary bioscience-performing a pooled analysis of individual-level data without sharing the data (2010) Int J Epidemiol, 39, pp. 1372-1382; Gaye, A., Marcon, Y., Isaeva, J., DataSHIELD: taking the analysis to the data, not the data to the analysis (2014) Int J Epidemiol, 43, pp. 1929-1944; Doiron, D., Burton, P., Marcon, Y., Data harmonization and federated analysis of population-based studies: the BioSHaRE project (2013) Emerg Themes Epidemiol, 10, p. 12; Raina, P.S., Wolfson, C., Kirkland, S.A., The Canadian longitudinal study on aging (CLSA) (2009) Can J Aging, 28, pp. 221-229; Borugian, M.J., Robson, P., Fortier, I., The Canadian Partnership for Tomorrow Project: building a pan-Canadian research platform for disease prevention (2010) CMAJ, 182, pp. 1197-1201; Staff, S., Challenges and opportunities (2011) Science, 331, pp. 692-693 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Motivation: Improving the dissemination of information on existing epidemiological studies and facilitating the interoperability of study databases are essential to maximizing the use of resources and accelerating improvements in health. To address this, Maelstrom Research proposes Opal and Mica, two inter-operable open-source software packages providing out-of-the-box solutions for epidemiological data management, harmonization and dissemination. Implementation: Opal and Mica are two standalone but inter-operable web applications written in Java, JavaScript and PHP. They provide web services and modern user interfaces to access them. General features: Opal allows users to import, manage, annotate and harmonize study data. Mica is used to build searchable web portals disseminating study and variable metadata. When used conjointly, Mica users can securely query and retrieve summary statistics on geographically dispersed Opal servers in real-time. Integration with the DataSHIELD approach allows conducting more complex federated analyses involving statistical models. Availability: Opal and Mica are open-source and freely available at [www.obiba.org] under a General Public License (GPL) version 3, and the metadata models and taxonomies that accompany them are available under a Creative Commons licence. © 2017 The Author . ER - TY - CONF T1 - The genomic epidemiology ontology and GEEM ontology reusability platform A1 - Dooley, D A1 - Griffiths, E A1 - Gosal, G A1 - Brinkman, F A1 - Hsiao, W Y1 - 2017/// KW - Biomedical metadata KW - Biomedical research KW - Controlled vocabulary KW - Epidemiology KW - Integration KW - Ontology KW - Portal JF - CEUR Workshop Proceedings VL - 2050 CY - Department of Pathology and Laboratory Medicine, University of British Columbia, BCCDC Site, 655 West 12th Avenue, Vancouver, BC, Canada UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045562052&partnerID=40&md5=169d74a0f5586c31d422b1aca66b0025 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Dooley et al. - 2017 - The genomic epidemiology ontology and GEEM ontology reusability platform.pdf N1 - Export Date: 4 May 2018 N2 - There is an increasing awareness within private and public organizations that ontologies (globally accessible and uniquely identified terms that have both natural language definitions and logic relations which can be queried and reasoned over by computers) are useful in solving interoperability quagmires between data silos and the add-hoc data dictionaries that describe them. However, the complexity of implementing evolving ontologies in content management and federated data querying applications is formidable. The Genomic Epidemiology Entity Mart (GEEM) web platform is a proof-of-concept web portal designed to provide non-ontologist users with an ontology-driven interface for examining data standards related to genomic sequence repository records. GEEM provides web forms that show labels and allowed-values for easy review. It also provides software developers with downloadable specifications in JSON and other data formats that can be used without the need for ontology expertise. New systems can adopt ontology-driven standards specifications from the start, and the same specifications can be used to facilitate and validate the conversion of legacy data. © 2017 CEUR-WS. All rights reserved. ER - TY - JOUR T1 - Drivers for the development of an Animal Health Surveillance Ontology (AHSO) A1 - Dórea, F C A1 - Vial, F A1 - Hammar, K A1 - Lindberg, A A1 - Lambrix, P A1 - Blomqvist, E A1 - Revie, C W Y1 - 2019/// JF - Preventive Veterinary Medicine VL - 166 SP - 39 EP - 48 DO - 10.1016/j.prevetmed.2019.03.002 N2 - ©2019 The Authors Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields of animal and public health, as well as computer scientists from the field of information management, have led to the conclusion that a major component of any solution will involve the adoption of ontologies. Here we describe the advantages of such an approach, and the steps taken to set up the Animal Health Surveillance Ontological (AHSO) framework. The AHSO framework is modelled in OWL, the W3C standard Semantic Web language for representing rich and complex knowledge. We illustrate how the framework can incorporate knowledge directly from domain experts or from data-driven sources, as well as by integrating existing mature ontological components from related disciplines. The development and extent of AHSO will be community driven and the final products in the framework will be open-access. ER - TY - JOUR T1 - A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres A1 - Draganski, B A1 - Kherif, F A1 - Damian, D A1 - Demonet, J.-F. Y1 - 2019/// JF - Current Opinion in Neurology VL - 32 IS - 4 SP - 557 EP - 563 DO - 10.1097/WCO.0000000000000721 N2 - ©Copyright 2019 Wolters Kluwer Health, Inc. All rights reserved. Purpose of review The goal of our nation-wide initiative is to provide clinicians intuitive and robust tools for accurate diagnosis, therapy monitoring and prognosis of cognitive decline that is based on large-scale multidomain data. Recent findings We describe a federation framework that allows for statistical analysis of aggregated brain imaging and clinical phenotyping data across memory clinics in Switzerland. The adaptation and deployment of readily available data capturing and federation modules is paralleled by developments in ontology, quality and regulatory control of brain imaging data. Our initiative incentivizes data sharing through the common resource in a way that provides individual researcher with access to large-scale data that surpasses the data acquisition capacity of a single centre. Clinicians benefit from fine-grained epidemiological characterization of own data compared with the rest additional to intuitive tools allowing for computer-based diagnosis of dementia. Finally, our concept aims at closing the loop between group-level results based on aggregate data and individual diagnosis by providing disease models, that is, classifiers for neurocognitive disorders that will enable the computer-based diagnosis of individual patients. Summary The obtained results will inform recommendations on best clinical practice in all relevant fields focusing on standardization and interoperability of acquired data, privacy protection framework and ethical consideration in the context of evolutive pathology. ER - TY - JOUR T1 - Barriers to cross--institutional health information exchange: a literature review. A1 - Edwards, A A1 - Hollin, I A1 - Barry, J A1 - Kachnowski, S Y1 - 2010/// KW - Diffusion of Innovation KW - Medical Informatics KW - Medical Record Linkage KW - Systems Integration KW - mass communication KW - medical informatics KW - medical record KW - review KW - system analysis JF - Journal of healthcare information management : JHIM VL - 24 IS - 3 SP - 22 EP - 34 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956644923&partnerID=40&md5=d181f56addb8374995d324b8384a5c4e N1 - Cited By :28 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - While the development of health information technology, particularly electronic health records (EHR), is a triumph for the advancement of healthcare, non-interoperable clinical data systems lead to fragmented communication and incomplete records. If interoperable HIT systems could be achieved integrated HIT could be leveraged to lessen medical errors, improve patient care and optimize epidemiological research. To understand the barriers to interoperability or health information exchange (HIE), we reviewed the literature on HIT and barriers to HIE. Our search yielded 492 articles, 25 meeting our inclusion criteria. In general, we found that the predominant barriers to HIE are need for standards, security concerns, economic loss to competitors, and federated systems. Research on interoperability is limited because most HIE programs are still in formative stages. More research is needed to fully understand interoperability of HIT, how to overcome the barriers to interoperability, and how to design HIT to better facilitate HIE. ER - TY - JOUR T1 - Integrating clinical research with the Healthcare Enterprise: From the RE-USE project to the EHR4CR platform A1 - El Fadly, A A1 - Rance, B A1 - Lucas, N A1 - Mead, C A1 - Chatellier, G A1 - Lastic, P.-Y. A1 - Jaulent, M.-C. A1 - Daniel, C Y1 - 2011/// KW - Algorithms KW - Biomedical Research KW - CDISE KW - Clinical protocols KW - Conformal mapping KW - Controlled vocabulary KW - Data acquisition KW - Decision support systems KW - Delivery of Health Care KW - Experiments KW - HL7 KW - Health Services Research KW - Hospitals KW - Humans KW - IHE KW - Industry KW - Information Storage and Retrieval KW - Information management KW - Information systems KW - Integration KW - Interoperability KW - Medical Record Linkage KW - Medical Records Systems, Computerized KW - Medical applications KW - Patient treatment KW - Population statistics KW - Semantic interoperability KW - Semantics KW - Software KW - Standards KW - Terminology KW - Translational Research KW - Translational research KW - accuracy KW - analytical error KW - article KW - automation KW - clinical research KW - data collection method KW - electronic medical record KW - health care system KW - medical documentation KW - medical record review KW - patient care KW - priority journal KW - semantics KW - treatment planning JF - Journal of Biomedical Informatics VL - 44 SP - S94 EP - S102 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-83955161855&doi=10.1016%2Fj.jbi.2011.07.007&partnerID=40&md5=e02c1ee8acc2b8d50bbdb85cd18f0061 N1 - Cited By :55 Export Date: 10 September 2018 References: Turisco, F., Keogh, D., Stubbs, C., Glaser, J., Crowley, J.W.F., Current status of integrating information technologies into the clinical research enterprise within US academic health centers: strategic value and opportunities for investment (2005) J Invest Med, 53 (8), pp. 425-433; Powell, J., Buchan, I., Electronic health records should support clinical research (2005) J Med Internet Res, 7 (1), pp. e4; West, S.L., Blake, C., Zhiwen, L., McKoy, J.N., Oertel, M.D., Carey, T.S., Reflections on the use of electronic health record data for clinical research (2009) Health Inform J, 15 (2), pp. 108-121; Ohmann, C., Kuchinke, W., Future developments of medical informatics from the viewpoint of networked clinical research. Interoperability and integration (2009) Methods Inf Med, 48 (1), pp. 45-54; Prokosch, H., Ganslandt, T., Perspectives for medical informatics. Reusing the electronic medical record for clinical research (2009) Methods Inf Med, 48 (1), pp. 38-44; Breil, B., Semjonow, A., Dugas, M., HIS-based electronic documentation can significantly reduce the time from biopsy to final report for prostate tumours and supports quality management as well as clinical research (2009) BMC Med Inform Decis Mak, 9, p. 5; Ohmann, C., Kuchinke, W., Meeting the challenges of patient recruitment. A role for electronic health records (2007) Int J Pharm Med, 21, pp. 263-270; Dugas, M., Lange, M., Müller, T.C., Kirchhof, P., Prokosch, H., Routine data from hospital information systems can support patient recruitment for clinical studies (2010) Clin Trials, 7 (2), pp. 183-189; Kush, R., Alschuler, L., Ruggeri, R., Cassells, S., Gupta, N., Bain, L., Implementing single source: the STARBRITE proof-of-concept study (2007) J Am Med Inform Assoc, 14 (5), pp. 662-673; Murphy, E.C., Frederick, L., An electronic medical records system for clinical research and the EMR-EDC interface (2007) Natl Inst Health, 48 (10), pp. 4383-4389; El Fadly, A., Lucas, N., Rance, B., Verplancke, P., Lastic, P.Y., Daniel, C., The REUSE project: EHR as single data source for biomedical research (2010) Health Technol Inform, 160 (PART 2), pp. 1324-1328; Williams, J.G., Cheung, W.Y., Cohen, D.R., Hutchings, H.A., Longo, M.F., Russell, I.T., Can randomised trials rely on existing electronic data? A feasibility study to explore the value of routine data in health technology assessment (2003) Health Technol Asses, 7 (26), pp. 111-117; Kahn, M.G., Kaplan, D., Configuration challenges: implementing translational research policies in electronic medical records (2007) Acad Med, 82 (7), pp. 661-669; Parexel's Bio/Pharmaceutical Statistical Sourcebook 2008/2009; http://www.cdisc.org/stuff/contentmgr/files/0/2f6eca8f0df7caac5bbd4fadfd 76d575/miscdocs/esdi.pdf, CDISC Electronic Source Data Interchange (eSDI) Group. Leveraging the CDISC standards to facilitate the use of electronic source data within clinical trials version, November 20, 2006. [cited 01.03.11]; http://www.esi-bethesda.com/ncrrworkshops/clinicalResearch/pdf/Catherine CeligrantPaper.pdf, eClinical Forum/PhRMA EDC/eSource Taskforce. The future vision of electronic health records as eSource for clinical research (Version 1.0), 2006, [cited 01.03.11]; http://www.ehrcr.org, EHR/CR Functional Profile Project. [cited 01.03.11]; http://www.cdisc.org/models/odm/v1.3/index.html, CDISC Operational Data Model. [cited 01.03.11]; Fridsma, D.B., Evans, J., Hastak, S., Mead, C.N., http://www.bridgmodel.org, The BRIDG project: a technical report. J Am Med Inform Assoc 2008;15:130-7. [cited 01.03.11]; http://www.ihe.net, Anonymous, Retrieve Form for Data capture (RFD) Supplement. IHE IT infrastructure technical framework; 2006. [cited 01.03.11]; Colquitt, J., http://www.ihe.net/Events/upload/ihe_webinar_2008_session_7_Quality-Rese arch-Public-Health_CRD_Capture_July10_2008_Colquitt.pdf, Clinical research document (CRD) profile. [cited 01.03.11]; Rosenbloom, S.T., Miller, R.A., Johnson, K.B., Interface terminologies: facilitating direct entry of clinical data into electronic health record systems (2006) J Am Med Inform Assoc, 13 (3), pp. 277-288; http://www.cdisc.org/stuff/contentmgr/files/0/70e1df7a3cd8a66f331770b0bc 0f149b/misc/share_pilot_report_1_0.pdf, CDISC Shared Health and Research Electronic Library Pilot Report; 2010. [cited 01.03.11]; Rector, A.L., Clinical terminology: why is it so hard? (1999) Methods Inf Med, 38 (4-5), pp. 239-252; Benson, T., Principles of health interoperability HL7 and SNOMED. Springer, Verlag; 2009; Rosenbloom, S.T., Brown, S.H., Froehling, D., Bauer, B.A., Wahner-Roedler, D.L., Gregg, W.M., Using SNOMED CT to represent two interface terminologies (2009) J Am Med Inform Assoc, 16 (1), pp. 81-88; Wade, G., Rosenbloom, S.T., Experiences mapping a legacy interface terminology to SNOMED CT (2008) BMC Med Inform Decis Mak, 27 (8 SUPPL. 1), pp. S3; Daniel, C., Buemi, A., Mazuel, L., Ouagne, D., Charlet, J., Functional requirements of terminology services for coupling interface terminologies to reference terminologies (2009) Stud Health Technol Inform, 150, pp. 205-209; Rance, B., Gibrat, J.F., Froidevaux, C., (2009), pp. 113-26. , An adaptive combination of matchers: application to the mapping of biological ontologies for genome annotation. Data Integration in the Life Sciences, Lecture Notes in Computer Science, DILS'09. LNBI 5647; http://www.ihe.net/Technical_Framework/upload/IHE_ITI_TF_Supplement_XDM_ TI_2006_08_15.pdf, Anonymous, Cross-Enterprise Document Media Interchange (XDM) supplement. IHE IT Infrastructure Technical Framework. [cited 03.01.11]; Stroetman, V., Kalra, D., Lewalle, P., Rector, A., Rodrigues, J., Stroetman, K., http://ec.europa.eu/information_society/activities/health/docs/publicati ons/2009/2009semantic-health-report.pdf, Semantic interoperability for better health and safer healthcare. The European Commission; 2009. [cited 01.03.11]; http://cabig.cancer.gov/perspectives/biomedicine/health20/soa/, NCI CBIIT. A semantic service oriented architecture (sSOA). [cited 01.03.11]; http://www.epcrn.bham.ac.uk/, Electronic Primary Care Research Network. [cited 01.03.11]; Weber, G.M., Murphy, S.N., McMurry, A.J., Macfadden, D., Nigrin, D.J., Churchill, S., The shared health research information network (SHRINE): a prototype federated query tool for clinical data repositories (2009) J Am Med Inform Assoc, 16 (5), pp. 624-630 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: There are different approaches for repurposing clinical data collected in the Electronic Healthcare Record (EHR) for use in clinical research. Semantic integration of "siloed" applications across domain boundaries is the raison d'être of the standards-based profiles developed by the Integrating the Healthcare Enterprise (IHE) initiative - an initiative by healthcare professionals and industry promoting the coordinated use of established standards such as DICOM and HL7 to address specific clinical needs in support of optimal patient care. In particular, the combination of two IHE profiles - the integration profile "Retrieve Form for Data Capture" (RFD), and the IHE content profile "Clinical Research Document" (CRD) - offers a straightforward approach to repurposing EHR data by enabling the pre-population of the case report forms (eCRF) used for clinical research data capture by Clinical Data Management Systems (CDMS) with previously collected EHR data. Objective: Implement an alternative solution of the RFD-CRD integration profile centered around two approaches: (i) Use of the EHR as the single-source data-entry and persistence point in order to ensure that all the clinical data for a given patient could be found in a single source irrespective of the data collection context, i.e. patient care or clinical research; and (ii) Maximize the automatic pre-population process through the use of a semantic interoperability services that identify duplicate or semantically-equivalent eCRF/EHR data elements as they were collected in the EHR context. Methods: The RE-USE architecture and associated profiles are focused on defining a set of scalable, standards-based, IHE-compliant profiles that can enable single-source data collection/entry and cross-system data reuse through semantic integration. Specifically, data reuse is realized through the semantic mapping of data collection fields in electronic Case Report Forms (eCRFs) to data elements previously defined as part of patient care-centric templates in the EHR context. The approach was evaluated in the context of a multi-center clinical trial conducted in a large, multi-disciplinary hospital with an installed EHR. Results: Data elements of seven eCRFs used in a multi-center clinical trial were mapped to data elements of patient care-centric templates in use in the EHR at the George Pompidou hospital. 13.4% of the data elements of the eCRFs were found to be represented in EHR templates and were therefore candidate for pre-population. During the execution phase of the clinical study, the semantic mapping architecture enabled data persisted in the EHR context as part of clinical care to be used to pre-populate eCRFS for use without secondary data entry. To ensure that the pre-populated data is viable for use in the clinical research context, all pre-populated eCRF data needs to be first approved by a trial investigator prior to being persisted in a research data store within a CDMS. Conclusion: Single-source data entry in the clinical care context for use in the clinical research context - a process enabled through the use of the EHR as single point of data entry, can - if demonstrated to be a viable strategy - not only significantly reduce data collection efforts while simultaneously increasing data collection accuracy secondary to elimination of transcription or double-entry errors between the two contexts but also ensure that all the clinical data for a given patient, irrespective of the data collection context, are available in the EHR for decision support and treatment planning. The RE-USE approach used mapping algorithms to identify semantic coherence between clinical care and clinical research data elements and pre-populate eCRFs. The RE-USE project utilized SNOMED International v.3.5 as its "pivot reference terminology" to support EHR-to-eCRF mapping, a decision that likely enhanced the "recall" of the mapping algorithms. The RE-USE results demonstrate the difficult challenges involved in semantic integration between the clinical care and clinical research contexts. © 2011 Elsevier Inc. ER - TY - JOUR T1 - Graph databases for openEHR clinical repositories A1 - El Helou, S A1 - Kobayashi, S A1 - Yamamoto, G A1 - Kume, N A1 - Kondoh, E A1 - Hiragi, S A1 - Okamoto, K A1 - Tamura, H A1 - Kuroda, T Y1 - 2019/// JF - International Journal of Computational Science and Engineering VL - 20 IS - 3 SP - 281 EP - 298 DO - 10.1504/IJCSE.2019.103955 N2 - Copyright ©2019 Inderscience Enterprises Ltd. The archetype-based approach has now been adopted by major EHR interoperability standards. Soon, due to an increase in EHR adoption, more health data will be created and frequently accessed. Previous research shows that conventional persistence mechanisms such as relational and XML databases have scalability issues when storing and querying archetype-based datasets. Accordingly, we need to explore and evaluate new persistence strategies for archetype-based EHR repositories. To address the performance issues expected to occur with the increase of data, we proposed an approach using labelled property graph databases for implementing openEHR clinical repositories. We implemented the proposed approach using Neo4j and compared it to an object relational mapping (ORM) approach using Microsoft SQL server. We evaluated both approaches over a simulation of a pregnancy home-monitoring application in terms of required storage space and query response time. The results show that the proposed approach provides a better overall performance for clinical querying. ER - TY - JOUR T1 - Does standardised structured reporting contribute to quality in diagnostic pathology? The importance of evidence-based datasets A1 - Ellis, D W A1 - Srigley, J Y1 - 2016/// KW - Benchmarking KW - Humans KW - Neoplasms KW - Pathology, Clinical KW - Quality KW - Reporting quality KW - Research Design KW - Review KW - Structured KW - Synoptic KW - accuracy KW - cancer registry KW - cancer staging KW - checklist KW - decision support system KW - evidence based medicine KW - health care quality KW - human KW - medical documentation KW - medical information KW - methodology KW - neoplasm KW - pathology KW - patient care KW - personalized medicine KW - priority journal KW - professional standard KW - prognostic assessment KW - standardized structured pathology reporting KW - standards KW - synoptic reporting KW - total quality management KW - world health organization JF - Virchows Archiv VL - 468 IS - 1 SP - 51 EP - 59 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958113113&doi=10.1007%2Fs00428-015-1834-4&partnerID=40&md5=0e47c4f517dddf23763474b33b6b0fc4 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Ellis, Srigley - 2016 - Does standardised structured reporting contribute to quality in diagnostic pathology The importance of evidence-.pdf N1 - Cited By :23 Export Date: 10 September 2018 References: http://www.rcpa.edu.au/Publications/StructuredReporting.htm, RCPA (Royal College of Pathologists of Australasia) (2009) Structured pathology reporting of cancer. Accessed 4 June 2015; http://www.rcpath.org/index.asp?PageID=254, RCPath (Royal College of Pathologists) datasets and tissue pathways. Accessed 4 June 2015; Cancer protocols and checklists (2009) Cancer checklists, , http://www.cap.org/apps/cap.portal?_nfpb=true&cntvwrPtlt_actionOverride=%2Fportlets%2FcontentViewer%2Fshow&_windowLabel=cntvwrPtlt&cntvwrPtlt%7BactionForm.contentReference%7D=committees%2Fcancer%2Fcancer_protocols%2Fprotocols_index.html&_state=maximized&_pageLabel=cntvwr; Casati, B., Bjugn, R., Structured electronic template for histopathology reporting on colorectal carcinoma resections: five-year follow-up shows sustainable long-term quality improvement (2012) Arch Pathol Lab Med, 136, pp. 652-656. , PID: 22646273; http://wiki.ihe.net/index.php?title=Anatomic_Pathology_Structured_Reports, Daniel C, Shrader T (2010) White paper: anatomic pathology structured reports. Accessed 4 June 2014 2015; Daniel, C., Macary, F., Rojo, M.G., Klossa, J., Recent advances in standards for collaborative digital anatomic pathology (2011) Diagn Pathol, 6, p. S17. , PID: 21489187; Digital imaging and communications in medicine, supplement 145: whole slide image IOD and SOP classes (2010) ftp://medical.nema.org/medical/dicom/final/sup145_ft.pdf, , ftp://medical.nema.org/medical/dicom/final/sup145_ft.pdf; Temple, W.J., Chin-Lenn, L., Mack, L.A., Cancer Surgery, A., Evaluating population-based breast cancer surgical practice in real time with a web-based synoptic operative reporting system (2014) Am J Surg, 207, pp. 693-696. , PID: 24576583, discussion 696–697; Edhemovic, I., Temple, W.J., de Gara, C.J., Stuart, G.C., The computer synoptic operative report—a leap forward in the science of surgery (2004) Ann Surg Oncol, 11, pp. 941-947. , PID: 15466354; Hoffer, D.N., Finelli, A., Chow, R., Liu, J., Structured electronic operative reporting: comparison with dictation in kidney cancer surgery (2012) Int J Med Inform, 81, pp. 182-191. , PID: 22217801; Aabakken, L., Barkun, A.N., Cotton, P.B., Fedorov, E., Standardized endoscopic reporting (2014) J Gastroenterol Hepatol, 29, pp. 234-240. , PID: 24329727; Kumarasinghe, M.P., Brown, I., Raftopoulos, S., Bourke, M.J., Standardised reporting protocol for endoscopic resection for Barrett oesophagus associated neoplasia: expert consensus recommendations (2014) Pathology, 46, pp. 473-480. , COI: 1:STN:280:DC%2BC2M%2Flt1Kqsg%3D%3D, PID: 25158823; Soekhoe, J.K., Groenen, M.J., van Ginneken, A.M., Khaliq, G., Computerized endoscopic reporting is no more time-consuming than reporting with conventional methods (2007) Eur J Intern Med, 18, pp. 321-325. , PID: 17574108; Powell, D.K., Silberzweig, J.E., State of structured reporting in radiology, a survey (2015) Acad Radiol, 22, pp. 226-233. , PID: 25442793; Larson, D.B., Towbin, A.J., Pryor, R.M., Donnelly, L.F., Improving consistency in radiology reporting through the use of department-wide standardized structured reporting (2013) Radiology, 267, pp. 240-250. , PID: 23329657; Brook, O.R., Brook, A., Vollmer, C.M., Kent, T.S., Structured reporting of multiphasic CT for pancreatic cancer: potential effect on staging and surgical planning (2015) Radiology, 274, pp. 464-472. , PID: 25286323; von Wangenheim, A., Barcellos, C.L., Jr., Andrade, R., de Carlos Back Giuliano, I., Implementing DICOM structured reporting in a large-scale telemedicine network (2013) Telemed J E Health, 19, pp. 535-541; Nayar, R., Wilbur, D.C., The Pap Test and Bethesda 2014. “The reports of my demise have been greatly exaggerated.” (after a quotation from Mark Twain) (2015) Acta Cytol, 59, pp. 121-132; Ali, S.Z., Thyroid cytopathology: Bethesda and beyond (2011) Acta Cytol, 55, pp. 4-12. , PID: 21135515; Srigley, J.R., McGowan, T., Maclean, A., Raby, M., Standardized synoptic cancer pathology reporting: a population-based approach (2009) J Surg Oncol, 99, pp. 517-524. , PID: 19466743; Merlin, T., Weston, A., Tooher, R., Extending an evidence hierarchy to include topics other than treatment: revising the Australian ‘levels of evidence’ (2009) BMC Med Res Methodol, 9, p. 34. , PID: 19519887; Simpson, R.W., Berman, M.A., Foulis, P.R., Divaris, D.X., Cancer biomarkers: the role of structured data reporting (2015) Arch Pathol Lab Med, 139, pp. 587-593. , PID: 25275812; Scolyer, R.A., Judge, M.J., Evans, A., Frishberg, D.P., Data set for pathology reporting of cutaneous invasive melanoma: recommendations from the International Collaboration on Cancer Reporting (ICCR) (2013) Am J Surg Pathol, 37, pp. 1797-1814. , PID: 24061524; McCluggage, W.G., Colgan, T., Duggan, M., Hacker, N.F., Data set for reporting of endometrial carcinomas: recommendations from the International Collaboration on Cancer Reporting (ICCR) between United Kingdom, United States, Canada, and Australasia (2013) Int J Gynecol Pathol, 32, pp. 45-65. , PID: 23202790; Jones, K.D., Churg, A., Henderson, D.W., Hwang, D.M., Data set for reporting of lung carcinomas: recommendations from International Collaboration on Cancer Reporting (2013) Arch Pathol Lab Med, 137, pp. 1054-1062. , PID: 23899061; Kench, J.G., Delahunt, B., Griffiths, D.F., Humphrey, P.A., Dataset for reporting of prostate carcinoma in radical prostatectomy specimens: recommendations from the International Collaboration on Cancer Reporting (2013) Histopathology, 62, pp. 203-218. , PID: 23240714; http://www.iccr-cancer.org, ICCR (2011) International Collaboration on Cancer Reporting. Accessed 4 June 2015; Valenstein, P.N., Formatting pathology reports: applying four design principles to improve communication and patient safety (2008) Arch Pathol Lab Med, 132, pp. 84-94. , PID: 18181680; Markel, S.F., Hirsch, S.D., Synoptic surgical pathology reporting (1991) Hum Pathol, 22, pp. 807-810. , COI: 1:STN:280:DyaK3MzjtFGlsw%3D%3D, PID: 1869264; Hutter, R.V., Rickert, R.R., Organization and management of the surgical pathology laboratory (1983) Principles and practice of surgical pathology, pp. 17-18. , Silverberg SG, (ed), Wiley, New York; Ellis, D.W., Surgical pathology reporting at the crossroads: beyond synoptic reporting (2011) Pathology, 43, pp. 404-409. , PID: 21753714; http://www.cap.org/apps/docs/committees/cancer/cancer_protocols/synoptic_report_definition_and_examples.pdf, Cancer Committee C (2011) Definition of synoptic reporting. Accessed 4 June 2015; Gill, A.J., Johns, A.L., Eckstein, R., Samra, J.S., Synoptic reporting improves histopathological assessment of pancreatic resection specimens (2009) Pathology, 41, pp. 161-167. , PID: 19320058; Hammond, E.H., Flinner, R.L., Clinically relevant breast cancer reporting: using process measures to improve anatomic pathology reporting (1997) Arch Pathol Lab Med, 121, pp. 1171-1175. , COI: 1:STN:280:DyaK1c%2FktVSisQ%3D%3D, PID: 9372744; Karim, R.Z., van den Berg, K.S., Colman, M.H., McCarthy, S.W., The advantage of using a synoptic pathology report format for cutaneous melanoma (2008) Histopathology, 52, pp. 130-138. , COI: 1:STN:280:DC%2BD1c%2Fit1artw%3D%3D, PID: 18184262; Cross, S.S., Feeley, K.M., Angel, C.A., The effect of four interventions on the informational content of histopathology reports of resected colorectal carcinomas (1998) J Clin Pathol, 51, pp. 481-482. , COI: 1:STN:280:DyaK1cvksVCitw%3D%3D, PID: 9771453; http://www.cancerinstitute.org.au/supporting-best-practice/treatments-and-protocols/structured-pathology-reporting, NSW CI (2007) Structured pathology reporting—report on a round table discussion. Accessed 4 June 2015; Lankshear, S., Srigley, J., McGowan, T., Yurcan, M., Standardized synoptic cancer pathology reports—so what and who cares? A population-based satisfaction survey of 970 pathologists, surgeons, and oncologists (2013) Arch Pathol Lab Med, 137, pp. 1599-1602. , PID: 23432456; Srigley, J., Lankshear, S., Brierley, J., McGowan, T., Closing the quality loop: facilitating improvement in oncology practice through timely access to clinical performance indicators (2013) J Oncol Pract, 9, pp. e255-e261. , PID: 23943888; McFadyen, C., Lankshear, S., Divaris, D., Berry, M., Physician level reporting of surgical and pathology performance indicators: a regional study to assess feasibility and impact on quality (2015) Can J Surg, 58, pp. 31-40. , PID: 25427336; Bosman, F., Jaffe, E.S., (2015) Lakhani SR, , Ohgaki H: WHO/IARC Classification of tumours. IARC Press, Lyon; Greene, F.L., Sobin, L.H., A worldwide approach to the TNM staging system: collaborative efforts of the AJCC and UICC (2009) J Surg Oncol, 99, pp. 269-272. , PID: 19170124; Edge, S.D., Byrd, D., Compton, C., Fritz, A.G., (2009) AJCC cancer staging manual, , Springer, New York; International Union against Cancer (UICC), (2009) TNM classification of malignant tumours, , Wiley-Blackwell, Chichester; Roder, D.M., Fong, K.M., Brown, M.P., Zalcberg, J., Realising opportunities for evidence-based cancer service delivery and research: linking cancer registry and administrative data in Australia (2014) Eur J Cancer Care (Engl), 23, pp. 721-727. , COI: 1:STN:280:DC%2BC2M7jsVGgtg%3D%3D; Chamie, K., Ballon-Landa, E., Bassett, J.C., Daskivich, T.J., Quality of diagnostic staging in patients with bladder cancer: a process-outcomes link (2015) Cancer, 121, pp. 379-385. , PID: 25339141; Sobin, L.H., Gospodarowicz, M.K., Wittekind, C., (2009) TNM classification of malignant tumours, , Wiley-Blackwell, Hoboken; Beckmann, K.R., Bennett, A., Young, G.P., Roder, D.M., Treatment patterns among colorectal cancer patients in South Australia: a demonstration of the utility of population-based data linkage (2014) J Eval Clin Pract, 20, pp. 467-477. , PID: 24851796; Mackillop, W.J., O’Sullivan, B., Gospodarowicz, M., The role of cancer staging in evidence-based medicine (1998) Cancer Prev Control, 2, pp. 269-277. , COI: 1:STN:280:DyaK1MzpvFCktQ%3D%3D, PID: 10470456; Brierley, J.D., Srigley, J.R., Yurcan, M., Li, B., The value of collecting population-based cancer stage data to support decision-making at organizational, regional and population levels (2013) Healthc Q, 16, pp. 27-33. , PID: 24034774; Walters, S., Maringe, C., Butler, J., Brierley, J.D., Comparability of stage data in cancer registries in six countries: lessons from the International Cancer Benchmarking Partnership (2013) Int J Cancer, 132, pp. 676-685. , COI: 1:CAS:528:DC%2BC38Xpt12ku78%3D, PID: 22623157; Maringe, C., Walters, S., Butler, J., Coleman, M.P., Stage at diagnosis and ovarian cancer survival: evidence from the International Cancer Benchmarking Partnership (2012) Gynecol Oncol, 127, pp. 75-82. , PID: 22750127; Walters, S., Maringe, C., Butler, J., Rachet, B., Breast cancer survival and stage at diagnosis in Australia, Canada, Denmark, Norway, Sweden and the UK, 2000-2007: a population-based study (2013) Br J Cancer, 108, pp. 1195-1208. , COI: 1:STN:280:DC%2BC3svitFChtg%3D%3D, PID: 23449362; Roder, D., Buckley, E., Translation from clinical trials to routine practice: how to demonstrate community benefit (2015) Asia Pac J Clin Oncol, 11, pp. 1-3. , PID: 25628060; Lankshear, S., Brierley, J.D., Imrie, K., Yurcan, M., Changing physician practice: an evaluation of knowledge transfer strategies to enhance physician documentation of cancer stage (2010) Healthc Q, 13, pp. 84-92. , PID: 20104043; Sheppard, A.J., Chiarelli, A.M., Marrett, L.D., Mirea, L., Detection of later stage breast cancer in First Nations women in Ontario, Canada (2010) Can J Public Health, 101, pp. 101-105. , PID: 20364549; http://gicr.iarc.fr/, IARC (2014) Global Initiative for Cancer Registry Development (GICR). Accessed 4 June 2015; Casati, B., Haugland, H.K., Barstad, G.M., Bjugn, R., Factors affecting the implementation and use of electronic templates for histopathology cancer reporting (2014) Pathology, 46, pp. 165-168. , PID: 24492317 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Key quality parameters in diagnostic pathology include timeliness, accuracy, completeness, conformance with current agreed standards, consistency and clarity in communication. In this review, we argue that with worldwide developments in eHealth and big data, generally, there are two further, often overlooked, parameters if our reports are to be fit for purpose. Firstly, population-level studies have clearly demonstrated the value of providing timely structured reporting data in standardised electronic format as part of system-wide quality improvement programmes. Moreover, when combined with multiple health data sources through eHealth and data linkage, structured pathology reports become central to population-level quality monitoring, benchmarking, interventions and benefit analyses in public health management. Secondly, population-level studies, particularly for benchmarking, require a single agreed international and evidence-based standard to ensure interoperability and comparability. This has been taken for granted in tumour classification and staging for many years, yet international standardisation of cancer datasets is only now underway through the International Collaboration on Cancer Reporting (ICCR). In this review, we present evidence supporting the role of structured pathology reporting in quality improvement for both clinical care and population-level health management. Although this review of available evidence largely relates to structured reporting of cancer, it is clear that the same principles can be applied throughout anatomical pathology generally, as they are elsewhere in the health system. © 2015, Springer-Verlag Berlin Heidelberg. ER - TY - JOUR T1 - Data Harmonization Process for Creating the National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Atlas A1 - Elmore, Kim A1 - Nelson, Rob A1 - Gant, Zanetta A1 - Jeffries, Carla A1 - Broeker, Lance A1 - Mirabito, Massimo A1 - Roberts, Henry Y1 - 2014/// JF - Public Health Reports VL - 129 IS - 1_suppl1 SP - 63 EP - 69 DO - 10.1177/00333549141291S110 UR - http://journals.sagepub.com/doi/10.1177/00333549141291S110 N2 - In 2009, the CDC National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) initiated the online, interactive NCHHSTP Atlas. The goal of the Atlas is to strengthen the capacity to monitor the diseases overseen by NCHHSTP and to illustrate demographic, spatial, and temporal variation in disease patterns. The Atlas includes HIV, AIDS, viral hepatitis, sexually transmitted disease, and tuberculosis surveillance data, and aims to provide a single point of access to meet the analytical and data dissemination needs of NCHHSTP. To accomplish this goal, an NCHHSTP-wide Data Harmonization Workgroup reviewed surveillance data collected by each division to harmonize the data across diseases, allowing one to query data and generate comparable maps and tables via the same user interface. Although we were not able to harmonize all data elements, data standardization is necessary and work continues toward that goal. ER - TY - CONF T1 - Assessing schizophrenia with an interoperable architecture A1 - Emerencia, A A1 - Van Der Krieke, L A1 - Petkov, N A1 - Aiello, M Y1 - 2011/// KW - Conversion process KW - Data format KW - Decoupling inputs KW - Diseases KW - Ehealth KW - Electronic medical record KW - Health KW - Intermediate layers KW - Interoperability KW - Knowledge management KW - Manual work KW - Medical computing KW - Multiple inputs KW - Ontology KW - Personal health record KW - Schizophrenia KW - Schizophrenia patients KW - WEB application KW - case-based reasoning KW - ontology KW - routine outcome monitoring SP - 79 EP - 82 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-83255165473&doi=10.1145%2F2064747.2064766&partnerID=40&md5=49569c69f7df83517eecf18e03d51498 N1 - Cited By :1 Export Date: 10 September 2018 References: Blobel, B., Oemig, F., Ontology-driven health information systems architectures (2009) Studies in Health Technology and Informatics, 150, p. 195; Dietterich, T., Domingos, P., Getoor, L., Muggleton, S., Tadepalli, P., Structured machine learning: The next ten years (2008) Machine Learning, 73 (1), pp. 3-23; Keet, C., Artale, A., Representing and reasoning over a taxonomy of part-whole relations (2008) Applied Ontology, 3 (1), pp. 91-110; Rotondi, A., Designing websites for persons with cognitive deficits: Design and usability of a psychoeducational intervention for persons with severe mental illness (2007) Psychological Services, 4 (3), p. 202; Välimäki, M., Design and development process of patient-centered computer-based support system for patients with schizophrenia spectrum psychosis (2008) Inf. for Health and Social Care, 33 (2), pp. 113-123; Van Der Krieke, L., Emerencia, A., Sytema, S., An Online Portal on Outcomes for Dutch Service Users, , Psychiatric Services, American Psychiatric Association. To appear; Wald, H.S., Dube, C.E., Anthony, D.C., Untangling the Web-The impact of Internet use on health care and the physician-patient relationship (2007) Patient Education and Counseling, 68 (3), pp. 218-224. , DOI 10.1016/j.pec.2007.05.016, PII S0738399107002212 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - With the introduction of electronic personal health records and e-health applications spreading, interoperability concerns are of increasing importance to hospitals and care facilities. Interoperability between distributed and complex systems requires, among other things, compatible data formats. The recommended approach is to store data using international terminology standards. For data that is not stored in this way, a conversion process must happen. This can be tedious manual work when multiple input and output formats are to be supported. We present WEGWEIS, a web application for schizophrenia patients that converts questionnaire answers into advice. The system's advice delivery is based on data extracted from the electronic medical records of 1379 patients. In WEGWEIS, we handle the conversion by decoupling input formats from output formats, using an ontology as intermediate layer. We present the algorithm and provide details on its implementation. © 2011 ACM. ER - TY - JOUR T1 - Clinical Data Integration Model A1 - Ethier, J -F. A1 - Curcin, V A1 - Barton, A A1 - McGilchrist, M M A1 - Bastiaens, H A1 - Andreasson, A A1 - Rossiter, J A1 - Zhao, L A1 - Arvanitis, T N A1 - Taweel, A A1 - Delaney, B C A1 - Burgun, A Y1 - 2015/// KW - Focus Theme KW - Original Articles KW - ontology KW - phenotyping KW - primary care PB - Schattauer GmbH JF - Methods of Information in Medicine VL - 54 IS - 1 SP - 16 EP - 23 UR - http://www.thieme-connect.de/DOI/DOI?10.3414/ME13-02-0024 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 -Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”.
ER - TY - JOUR T1 - A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm A1 - Ethier, Jean-François A1 - Dameron, Olivier A1 - Curcin, Vasa A1 - Mcgilchrist, Mark M A1 - Verheij, Robert A A1 - Arvanitis, Theodoros N A1 - Taweel, Adel A1 - Delaney, Brendan C A1 - Burgun, Anita DO - 10.1136/amiajnl-2012-001312 UR - https://academic.oup.com/jamia/article-abstract/20/5/986/2909276 N2 - Objective Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. Materials and methods We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Results Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. Conclusions We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration. ER - TY - JOUR T1 - A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm. A1 - Ethier, Jean-François A1 - Dameron, Olivier A1 - Curcin, Vasa A1 - McGilchrist, Mark M A1 - Verheij, Robert A A1 - Arvanitis, Theodoros N A1 - Taweel, Adel A1 - Delaney, Brendan C A1 - Burgun, Anita Y1 - 2013/// KW - Interoperability KW - LexEVS KW - Ontology KW - Semantics KW - Terminology KW - Translational Medical Research PB - American Medical Informatics Association JF - Journal of the American Medical Informatics Association : JAMIA VL - 20 IS - 5 SP - 986 EP - 994 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - OBJECTIVE Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. MATERIALS AND METHODS We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. RESULTS Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. CONCLUSIONS We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration. ER - TY - BOOK T1 - Steps towards online monitoring systems and interoperability A1 - Ferreira, D A1 - Neto, C A1 - Machado, J A1 - Abelha, A Y1 - 2019/// JF - Advances in Intelligent Systems and Computing VL - 932 SP - 527 EP - 536 SN - 9783030161866 DO - 10.1007/978-3-030-16187-3_51 N2 - ©Springer Nature Switzerland AG 2019. In the health area, there is, on a daily basis, an enormous amount of data being produced and disseminated. The fast-growing amount of collected data and the rich knowledge, possibly life-saving, that could be extracted from these data has demanded the search of new ways to ensure the reliability and availability of the information with an emphasis on the efficient use of information technology tools. Although the main focus of the information systems is the health professionals who contact directly with the patient, it is also imperative to have tools for the background of the health units (information services, managers of systems, etc.). The main purpose of this work is the development of an innovative and interactive web platform for the daily monitoring of the web services activities of a Portuguese hospital, Centro Hospitalar do Porto (CHP). This platform is a web application developed in React that aims to ensure the correct functioning of the web services, that are responsible for numerous tasks within the hospital environment, and which failure could result in disastrous consequences, both for the health institution and for the patients. The development of the web application followed the six stages of the Design Science Research (DSR) methodology and was submitted to the Strengths Weaknesses Opportunities and Threats (SWOT) analysis, which results were considered optimistic. ER - TY - JOUR T1 - Inventory of electronic health information exchange in Wisconsin, 2006 A1 - Foldy, S Y1 - 2007/// KW - Cross-Sectional Studies KW - Data Collection KW - Humans KW - Internet KW - Medical Informatics Applications KW - Medical Records Systems, Computerized KW - Program Development KW - Public Health Informatics KW - United States KW - Wisconsin KW - article KW - coordination KW - driver KW - electronic medical record KW - funding KW - health care organization KW - health care policy KW - health care utilization KW - marketing KW - medical information KW - medical staff JF - Wisconsin Medical Journal VL - 106 LA - English IS - 3 SP - 120 EP - 125 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250009070&partnerID=40&md5=7b1f189d57ab4dbbd8f94894bbd1b8d4 N1 - Ehealth AND governance Cited By :6 Export Date: 10 September 2018 References: (2004), www.whitehouse.gov/news/releases/2004/04/20040427-4.html, Executive Order: Incentives for the Use of Health Information Technology and Establishing the Position of the National Health Information Technology Coordinator. President George W. Bush, April 27, Available at:, Accessed May 15, 2007; States Getting Connected: State Policy-Makers Drive Improvements in Health care Quality and Safety Through IT. eHealth Initiative, Washington, DC, August, 2006. Available at: http://ehealthinitiative.org/assets/documents/ StateReportIssueBrief-08.31.06FINAL1001.pdf. Accessed May 14, 2007; (2004) The Value of Health care Information Exchange and Interoperability, , Center for Information Technology Leadership:Boston, MA;; Hillestad, R., Bigelow, J., Bower, A., Can electronic medical record systems transform health care? potential health benefits, savings and costs (2005) Health Affairs, 24 (5), pp. 1103-1117; Economic Value of a Community Clinical Information Sharing Network. Part 1: Value to Payers (Private, Medicare, Medicaid and Self-Insured Employers) and the Uninsured. Patient Safety Institute White Paper (Prepared by Emerging Practices, First Consulting Group); March 2004; Financial, Legal and Organizational Approaches to Achieving Electronic Connectivity in Health care. Connecting for Health, October 2004. Available at: www.connectingforhealth.org/resources/generalresources.html. Accessed May 15, 2007; Hanrahan, L.P., Foldy, S., Barthell, E.N., Wood, S., Medical informatics in population health: Building Wisconsin's strategic framework for health information technology (2006) WMJ, 105 (1), pp. 16-22; Foldy, S., Ross, D., (2005) Topics in Public Health Informatics June, Public Health Opportunities in Health Information Exchange: A resource for public health agencies and their health information exchange partners, , http://phii.org/Files/ Opportunities_0605.pdf, Public Health Informatics Institute, Atlanta, GA, Available at:, Accessed May 15; Using information technology (2001) Crossing the Quality Chasm: A New Health System for the 21st Century, , Committee on the Quality of Health care in America, Institute of Medicine, Washington DC: National Academy Press;; Executive Order # 129 Relating to the Governor's eHealth Care Quality and Patient Safety Board. Available at: www.wisgov.state.wi.us/ journal_media_detail. asp?locid=19&prid=1499. Accessed May 15, 2007; (2006) Wisconsin eHealth Action Plan. Board for eHealth Care Quality and Patient Safety, , http://ehealthboard.dhfs.wisconsin.gov/ actionplan2006-12.pdf, December, Available at:, Accessed May 15, 2007; Improving the Quality of Health care Through Health Information Exchange: Selected Findings from eHealth Initiative's Third Annual Survey of Health Information Exchange Activities at the State, Regional and Local Levels. eHealth Initiative; September 2006; CalRHIO Health Information Exchange Inventory. Available at: http://calrhio.org/crweb-files/docs-hie/CalHIE-InvMethodology. pdf and http://calrhio.org/crweb-files/docshie/CalHIE-InvAnalysis.pdf. Accessed May 15, 2007; Bergun, A.H., Hoekman, A.S., Jovaag, A., Transforming Wisconsin's Public Health System University of Wisconsin Population Health Institute Brief Report, , 2006;17; (2006), http://ehealthboard. dhfs.wisconsin.gov/ie-final-report. pdf, eHealth Care Quality and Patient Safety Board Information Exchange Workgroup. Final Report. November 28, Available at:, Accessed May 15, 2007UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250009070&partnerID=40&md5=7b1f189d57ab4dbbd8f94894bbd1b8d4 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: HIE N2 - Context: The Governor's Board for eHealth Care Quality and Patient Safety plans for universal adoption of electronic health records and information exchange. Objectives: The inventory sought to describe characteristics, challenges, and policy recommendations of health information exchange (HIE) projects and create a directory and baseline for periodic reassessment. Design, Setting, Subjects: A cross-sectional Internet survey of any project where electronic patient information was transmitted by multiple organizations in Wisconsin in 2006. Main Outcome Measures: A description of operational and planned HIE projects, including stage of development, information users, organizational home, funding, governance, geographic scope, data standardization, drivers, internal and external challenges, and recommendations for statewide action. Results: Twenty-one organizations sponsor 16 operational and 11 planned HIE projects. Most are surveillance programs, but a growing proportion serves clinicians and patients. Under half use data standards for interoperability. Leading internal challenges relate to funding, organizational and staff issues, governance, and technology. Leading external challenges are marketing, enlisting participants, regulatory issues, and sustainability. Conclusion: Wisconsin enjoys rich experience with HIE, but data remains largely in separate silos. Statewide collaboration, coordination and resource sharing can enhance the future of exchange efforts. ER - TY - JOUR T1 - Bioinformatics. Tools to Accelerate Population Science and Disease Control Research A1 - Forman, M R A1 - Greene, S M A1 - Avis, N E A1 - Taplin, S H A1 - Courtney, P A1 - Schad, P A A1 - Hesse, B W A1 - Winn, D M Y1 - 2010/// KW - Biomedical Research KW - Computational Biology KW - Epidemiologic Methods KW - Humans KW - Meta-Analysis as Topic KW - National Cancer Institute (U.S.) KW - Preventive Medicine KW - Public Health KW - Research Design KW - United States KW - bioinformatics KW - biomedicine KW - biotechnology KW - career KW - disease control KW - early diagnosis KW - information processing KW - information retrieval KW - information science KW - information storage KW - medical information system KW - medical research KW - molecular biology KW - patient care KW - population research KW - preventive medicine KW - public health KW - public health service KW - rare disease KW - review KW - standardization JF - American Journal of Preventive Medicine VL - 38 IS - 6 SP - 646 EP - 651 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952364294&doi=10.1016%2Fj.amepre.2010.03.002&partnerID=40&md5=c0b996c55a2e8973a046c3f70e776698 N1 - Cited By :11 Export Date: 10 September 2018 References: Fenton, J.J., Cai, Y., Green, P., Beckett, L.A., Franks, P., Baldwin, L.M., Trends in colorectal cancer testing among medicare subpopulations (2008) Am J Prev Med, 35 (3), pp. 194-202; Hiatt, R.A., The future of cancer surveillance (2006) Cancer Causes Control, 17 (5), pp. 639-646; Smith, P.C., Araya-Guerra, R., Bublitz, C., Missing clinical information during primary care visits (2005) JAMA, 293 (5), pp. 565-571; Shortliffe, E.H., Sondik, E.J., The public health informatics infrastructure: anticipating its role in cancer (2006) Cancer Causes Control, 17 (7), pp. 861-869; Lander, E.S., Linton, L.M., Birren, B., Initial sequencing and analysis of the human genome (2001) Nature, 409 (6822), pp. 860-921; Wolfsberg, T.G., Wetterstrand, K.A., Guyer, M.S., Collins, F.S., Baxevanis, A.D., A user's guide to the human genome (2002) Nat Genet, 32 (SUPPL), pp. 1-79; Liotta, L.A., Petricoin, E.F., Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold (2006) J Clin Invest, 116 (1), pp. 26-30; Calvo, K.R.P., Liotta, L.A., (2005) Genomics and proteomics in cancer: principles & practice of oncology. 7th ed., , Lippincott Williams & Wilkins, Philadelphia PA; Manolio, T.A., Collins, F.S., The HapMap and genome-wide association studies in diagnosis and therapy (2009) Annu Rev Med, 60, pp. 443-456; Manolio, T.A., Collins, F.S., Cox, N.J., Finding the missing heritability of complex diseases (2009) Nature, 461 (7265), pp. 747-753; Collins, F.S., Barker, A.D., Mapping the cancer genome. Pinpointing the genes involved in cancer will help chart a new course across the complex landscape of human malignancies (2007) Sci Am, 296 (3), pp. 50-57; Arking, D.E., Chakravarti, A., Understanding cardiovascular disease through the lens of genome-wide association studies (2009) Trends Genet, 25 (9), pp. 387-394; Buetow, K., (2005) Cancer: principles & practice of oncology. 7th ed., , Lippincott Williams & Wilkins, Philadelphia PA; Stone, A., (2007) The science of real-time data capture: self-reports in health research, , Oxford University Press, New York; Safran, C., The collaborative edge: patient empowerment for vulnerable populations (2003) Int J Med Inform, 69 (2-3), pp. 185-190; Doctorow, C., Big data: welcome to the petacentre (2008) Nature, 455 (7209), pp. 16-21; Howe, D., Costanzo, M., Fey, P., Big data: the future of biocuration (2008) Nature, 455 (7209), pp. 47-50; Huerta, M., Haseltine, F., Liu, Y., Downing, G., Seto, B., (2000) NIH working definition of bioinformatics and computational biology, , USDHHS, Washington DC; (2008), http://cabig.nci.nih.gov/overview/, USDHHS, NIH, National Cancer Institute About caBIG; Buetow, K.H., Cyberinfrastructure: empowering a "third way" in biomedical research (2005) Science, 308 (5723), pp. 821-824; Buetow, K.H., Niederhuber, J., Infrastructure for a learning healthcare system: CaBIG (2009) Health Aff (Millwood), 28 (3), pp. 923-924. , author reply 924-5; Nosowsky, R., Giordano, T.J., The health insurance portability and accountability act of 1996 (HIPAA) privacy rule: implications for clinical research (2006) Annu Rev Med, 57, pp. 575-590; (2001) Information for health: a strategy for building the National Health Information Inrastructure, , National Committee on Vital and Health Satistics, USDHHS, Washington DC; Ochs, M.F., Casagrande, J.T., Information systems for cancer research (2008) Cancer Invest, 26 (10), pp. 1060-1067; (2009), http://www.phenxtoolkit.org, NHGRI; Myers, J.E., Thompson, M.L., Meta-analysis and occupational epidemiology (1998) Occup Med, 48 (2), pp. 99-101; Hoover, R.N., The evolution of epidemiologic research: from cottage industry to "big" science (2007) Epidemiology, 18 (1), pp. 13-17; http://epi.grants.nci.gov/consortia, NIH. National Cancer Institute; Robison, L.L., Mertens, A.C., Boice, J.D., Study design and cohort characteristics of the Childhood Cancer Survivor Study: a multi-institutional collaborative project (2002) Med Pediatr Oncol, 38 (4), pp. 229-239; Murcray, C.E., Lewinger, J.P., Gauderman, W.J., Gene-environment interaction in genome-wide association studies (2009) Am J Epidemiol, 169 (2), pp. 219-226; http://www.rarediseasenetwork.usf.edu, Rare diseases clinical research network; Mailman, M.D., Feolo, M., Jin, Y., The NCBI dbGaP database of genotypes and phenotypes (2007) Nat Genet, 39 (10), pp. 1181-1186; Zhang, H., Morrison, M.A., Dewan, A., The NEI/NCBI dbGAP database: genotypes and haplotypes that may specifically predispose to risk of neovascular age-related macular degeneration (2008) BMC Med Genet, 9, p. 51; Hazlehurst, B., Sittig, D.F., Stevens, V.J., Natural language processing in the electronic medical record: assessing clinician adherence to tobacco treatment guidelines (2005) Am J Prev Med, 29 (5), pp. 434-439; Thomson, G.E., Mitchell, F., Williams, M., (2006) Examining the health disparities research plan of the National Institutes of Health: unfinished business, , National Research Council (U.S.). Committee on the Review and Assessment of the NIH's Strategic Research Plan and Budget to Reduce and Ultimately Eliminate Health Disparities, National Academy Press, Washington DC; Butte, A.J., Translational bioinformatics: coming of age (2008) J Am Med Inform Assoc, 15 (6), pp. 709-714; Aiello, E.J., Buist, D.S., Wagner, E.H., Diffusion of aromatase inhibitors for breast cancer therapy between 1996 and 2003 in the Cancer Research Network (2008) Breast Cancer Res Treat, 107 (3), pp. 397-403; Wagner, E.H., Bennett, S.M., Austin, B.T., Greene, S.M., Schaefer, J.K., Vonkorff, M., Finding common ground: patient-centeredness and evidence-based chronic illness care (2005) J Altern Complement Med, 11 (1 S), pp. S7-S15; Greene, S.M., Hart, G., Wagner, E.H., Measuring and improving performance in multicenter research consortia (2005) J Natl Cancer Inst Monogr, (35), pp. 26-32; (2009), http://www.cvrn.kaiser.org, National Heart, Lung, and Blood Institute; Magid, D.J., Gurwitz, J.H., Rumsfeld, J.S., Go, A.S., Creating a research data network for cardiovascular disease: the CVRN (2008) Expert Rev Cardiovasc Ther, 6 (8), pp. 1043-1045; Hazlehurst, B., Frost, H.R., Sittig, D.F., Stevens, V.J., MediClass: a system for detecting and classifying encounter-based clinical events in any electronic medical record (2005) J Am Med Inform Assoc, 12 (5), pp. 517-529; About Harvard Catalyst. Lee M. Nadler, , http://catalyst.harvard.edu/about.html; Weber, G.M., Murphy, S.N., McMurry, A.J., The Shared Health Research Information Network (SHRINE): a prototype federated query tool for clinical data repositories (2009) J Am Med Inform Assoc, 16 (5), pp. 624-630; Ogden, C.L., Flegal, K.M., Carroll, M.D., Johnson, C.L., Prevalence and trends in overweight among U.S. children and adolescents, 1999-2000 (2002) JAMA, 288 (14), pp. 1728-1732; Calle, E.E., Rodriguez, C., Walker-Thurmond, K., Thun, M.J., Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults (2003) N Engl J Med, 348 (17), pp. 1625-1638; Troiano, R.P., Berrigan, D., Dodd, K.W., Masse, L.C., Tilert, T., McDowell, M., Physical activity in the U.S. measured by accelerometer (2008) Med Sci Sports Exerc, 40 (1), pp. 181-188; Sallis, J.F., Linton, L.S., Kraft, M.K., The Active Living Research program: six years of grantmaking (2009) Am J Prev Med, 36 (2 S), pp. S10-S21; Schwartz, J., Byrd-Bredbenner, C., Portion distortion: typical portion sizes selected by young adults (2006) J Am Diet Assoc, 106 (9), pp. 1412-1418; Patrick, K., Griswold, W.G., Raab, F., Intille, S.S., Health and the mobile phone (2008) Am J Prev Med, 35 (2), pp. 177-181; Ambs, A., Warren, J.L., Bellizzi, K.M., Topor, M., Haffer, S.C., Clauser, S.B., Overview of the SEER-Medicare Health Outcomes Survey linked dataset (2008) Health Care Financ Rev, 29 (4), pp. 5-21; El-Serag, H.B., Siegel, A.B., Davila, J.A., Treatment and outcomes of treating of hepatocellular carcinoma among Medicare recipients in the U.S.: a population-based study (2006) J Hepatol, 44 (1), pp. 158-166; Shen, B., Toward cross-sectoral team science (2008) Am J Prev Med, 35 (2 S), pp. S240-S242; Hall, K.L., Feng, A.X., Moser, R.P., Stokols, D., Taylor, B.K., Moving the science of team science forward: collaboration and creativity (2008) Am J Prev Med, 35 (2 S), pp. S243-S249; Hall, K.L., Stokols, D., Moser, R.P., The collaboration readiness of transdisciplinary research teams and centers findings from the National Cancer Institute's TREC Year-One evaluation study (2008) Am J Prev Med, 35 (2 S), pp. S161-S172; Masse, L.C., Moser, R.P., Stokols, D., Measuring collaboration and transdisciplinary integration in team science (2008) Am J Prev Med, 35 (2 S), pp. S151-S160; Stokols, D., Hall, K.L., Taylor, B.K., Moser, R.P., The science of team science: overview of the field and introduction to the supplement (2008) Am J Prev Med, 35 (2 S), pp. S77-S89; Stokols, D., Misra, S., Moser, R.P., Hall, K.L., Taylor, B.K., The ecology of team science: understanding contextual influences on transdisciplinary collaboration (2008) Am J Prev Med, 35 (2 S), pp. S96-S115 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Population science and disease control researchers can benefit from a more proactive approach to applying bioinformatics tools for clinical and public health research. Bioinformatics utilizes principles of information sciences and technologies to transform vast, diverse, and complex life sciences data into a more coherent format for wider application. Bioinformatics provides the means to collect and process data, enhance data standardization and harmonization for scientific discovery, and merge disparate data sources. Achieving interoperability (i.e. the development of an informatics system that provides access to and use of data from different systems) will facilitate scientific explorations and careers and opportunities for interventions in population health. The National Cancer Institute's (NCI's) interoperable Cancer Biomedical Informatics Grid (caBIG®) is one of a number of illustrative tools in this report that are being mined by population scientists. Tools are not all that is needed for progress. Challenges persist, including a lack of common data standards, proprietary barriers to data access, and difficulties pooling data from studies. Population scientists and informaticists are developing promising and innovative solutions to these barriers. The purpose of this paper is to describe how the application of bioinformatics systems can accelerate population health research across the continuum from prevention to detection, diagnosis, treatment, and outcome. © 2010 American Journal of Preventive Medicine. ER - TY - JOUR T1 - Integrated Nationwide Electronic Health Records system: Semi-distributed architecture approach A1 - Fragidis, L L A1 - Chatzoglou, P D A1 - Aggelidis, V P Y1 - 2016/// KW - Article KW - Computer Communication Networks KW - Ehealth KW - Electronic Health Records KW - Electronic health records KW - Greece KW - Humans KW - Interoperability KW - Medical Errors KW - Medication Errors KW - Middleware KW - Semi-distributed architecture KW - System integration KW - Systems Integration KW - computer network KW - electronic health record KW - health care cost KW - health care organization KW - health care personnel KW - health care system KW - human KW - medical information system KW - organization and management KW - priority journal KW - system analysis JF - Technology and Health Care VL - 24 IS - 6 SP - 827 EP - 842 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84999277527&doi=10.3233%2FTHC-161231&partnerID=40&md5=3ed8b8d45dcda9cdf0385f86317ef219 N1 - Cited By :1 Export Date: 10 September 2018 References: Samuel, W.J., Blackford, M., Lisa, P.A., Christiana, B.G., Cynthia, S.D., Patricia, C.J., Anne, K.F., David, B.W., A cost-benefit analysis of electronic medical records in primary care (2003) The American Journal of Medicine, 114, pp. 397-403; Iakovidis, I., Towards personal health record: Current situation, obstacles and trends in implementation of electronic healthcare records in Europe (1998) International Journal of Medical Informatics, 52, pp. 105-117; Dobrev, A., Stroetmann, K., Stroetmann, V., Artmann, J., Jones, T., Hammerschmidt, R., (2008) Report on the Conceptual Framework of Interoperable Electronic Health Record and EPrescribing Systems, EHR IMPACT European Commission-Information Society and Media; Dobrev, A., Jones, T., Stroetmann, V., Stroetmann, K., Vatter, Y., Peng, K., Interoperable ehealth is worth it: Securing benefits from electronic health records and eprescribing, study report 2010 (2010) European Commission-Information Society and Media-Unit ICT for Healt Bonn/Brussels; Deutsch, E., Duftschmid, G., Dorda, W., Critical areas of national electronic health record programs-Is our focus correct (2010) International Journal of Medical Informatics, 79, pp. 211-222; Jarullah, A.A., El-Masri, S., A novel system architecture for the national integration of electronic health records: A semi-centralized approach (2013) Journal of Medical Systems, 37, p. 9953; Daglish, D., Archer, N., Electronic personal health record systems: A brief review of privacy, security, and architectural issues, world congress on privacy, security (2009) Trust and the Management of E-Business, pp. 110-120; Moller, J.E., Vosegaard, H., Experiences with electronic health records (2008) IT Professional, 10 (2), pp. 19-23; (2006) Canada Health Infoway. EHRS Bluprint v2, , https://?knowledge.?infowayinforoute.?.ca/?EHRSRA/?doc/?EHRS-Blueprint.?pdf, March. cited 2015 April; (2008) Australian Government, National Health &Hospitals Reform Commission, Christopher Bartlett, Klaus Boehncke. EHealth: Enabler for Australia's Health Reform, p. 2; Liu, V., Caelli, W., Smith, J., May, L., Lee, M.H., Ng, Z.H., Foo, J.H., Li, W., A secure architecture for Australia's index based e-health environment (2010) Proceedings of the Fourth Australasian Workshop on Health Informatics and Knowledge Management, 108, pp. 7-16. , In: Maeder, A., and Hansen, A. (Eds. ). Australian Computer Society Inc. Darlinghurst; Cresswell, K.M., Robertson, A., Sheik, A., Lessons learned from England's national electronic health record implementation: Implications for the international community (2012) Proc the 2nd ACM SIGHIT International Health Informatics Symposium (IHI '12), pp. 685-690. , New York: ACM; (2015) National Health Service. Cited, , http://?www.?nhs.?uk/?Pages/?HomePage.?aspx, April; Spronk, R., (2008) AORTA, the Dutch National Infrastructure, , http://?www.?.ringholm.?de/?docs/?00980_?en.?htm, Righolm; Smet, K., The Dutch nationwide electronic health record: Why the centralised services architecture (2011) WICSA Ninth Working IEEE/IFIP Conference on Software Architecture, pp. 181-186; Leonidas, F., Prodromos, C., The use of electronic health record in Greece: Current status (2011) 11th IEEE International Conference on Computer and Information Technology, pp. 475-480; Dimitrios, G., Georgia, K., How did the economic crisis in Greece affected the steps in applying egovernment at the first degree self government of Greece (2013) Journal of Governance and Regulation, (2), pp. 7-12; (2015) Spiliotopoulos George. Syzefxis MAN-Technical Approach Information Society SA, , http://www.syzefxis.gov.gr/en, 2014; cited April; (2015) National Public Administration Network (SYZEFXIS), , http://www.syzefxis.gov.gr/pdfs/3_man.pdf, cited April; Schiza, E.C., Neokleous, K.C., Petkov, N., Schizas, C.N., A patient centered electronic health: EHealth system development (2015) Technology and Health Care, (23), pp. 509-522; Simborg, D.W., Detmer, D.E., Berner, E.S., The wave has finally broken: Now what (2013) Journal of the American Medical Informatics Association, (20), pp. 21-25; Creating and protecting a public good workshop summary (2010) Institute of Medicine (US) Roundtable on Value &Science-Driven Health Care, , Clinical Data as the Basic Staple of Health Learning Washington (DC): National Academies Press (US); (2015) Clinical Information Modeling Initiative (CIMI), , http://opencimi.org, cited October; (2015) Fast Healthcare Interoperability Resources (FHIR), , https://www.hl7.org/fhir, cited October; (2015) Health Level Seven International (HL7), , http://www.hl7.org, cited April; Jalal-Karim, A., Balachandran, W., The optimal network model's performance for sharing Electronic Health record (2008) Proceedings of the 12th IEEE International Multitopic Conference, pp. 149-154; Santos-Pereira, C., Augusto, A.B., Correia, M.E., Ferreira, A., Cruz-Correia, R., A mobile based authorization mechanism for patient managed role based access control (2012) Proceedings of the Third International Conference in Information Technology in Bio-And Medical Informatics, pp. 54-68; Shao, Z., Yang, B., Zhang, W., Zhao, Y., Wu, Z., Miao, M., Secure medical information sharing in cloud computing (2015) Technology and Health Care, (23), pp. 133-137 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND: The integration of heterogeneous electronic health records systems by building an interoperable nationwide electronic health record system provides undisputable benefits in health care, like superior health information quality, medical errors prevention and cost saving. OBJECTIVE: This paper proposes a semi-distributed system architecture approach for an integrated national electronic health record system incorporating the advantages of the two dominant approaches, the centralized architecture and the distributed architecture. METHODS: The high level design of the main elements for the proposed architecture is provided along with diagrams of execution and operation and data synchronization architecture for the proposed solution. RESULTS: The proposed approach effectively handles issues related to redundancy, consistency, security, privacy, availability, load balancing, maintainability, complexity and interoperability of citizen's health data. CONCLUSIONS:The proposed semi-distributed architecture offers a robust interoperability framework without healthcare providers to change their local EHR systems. It is a pragmatic approach taking into account the characteristics of the Greek national healthcare system along with the national public administration data communication network infrastructure, for achieving EHR integration with acceptable implementation cost. © 2016 - IOS Press and the authors. All rights reserved. ER - TY - JOUR T1 - Online genomics facilities in the new millennium A1 - Frishman, D A1 - Kaps, A A1 - Mewes, H.-W. Y1 - 2002/// KW - Animalia KW - Animals KW - Bioinformatics KW - Computational Biology KW - Database KW - Databases, Genetic KW - Genome KW - Genome analysis KW - Genomics KW - Germany KW - Humans KW - Integration KW - Internet KW - Online Systems KW - Proteomics KW - Structural genomics KW - amino acid KW - amino acid sequence KW - animal cell KW - article KW - data base KW - fungal genetics KW - gene expression KW - gene function KW - genetic analysis KW - genomics KW - health care facility KW - human KW - human cell KW - information center KW - information processing KW - medical information system KW - nonhuman KW - online system KW - protein KW - protein protein interaction KW - sequence analysis JF - Pharmacogenomics VL - 3 IS - 2 SP - 265 EP - 271 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036122694&doi=10.1517%2F14622416.3.2.265&partnerID=40&md5=655d8cd1f5bd761478578b84fcd7ad01 N1 - Cited By :6 Export Date: 10 September 2018 References: Wheeler, D.L., Church, D.M., Lash, A.E., Database resources of the National Center for Biotechnology Information: 2000 update (2002) Nuc. Acids Res., 30, pp. 13-16; Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J., Rapp, B.A., Wheeler, D.L., GenBank (2000) Nuc. Acids Res., 30, pp. 17-20; Altschul, S.F., Madden, T.L., Schaffer, A.A., Gapped BLAST and PSI-BLAST: A new generation of protein database search programs (1997) Nuc. Acids Res., 25, pp. 3389-3402; Etzold, T., Ulyanov, A., Argos, P., SRS: Information retrieval system for molecular biology data banks (1996) Meth. Enzymol., 266, pp. 114-128; Fujibuchi, W., Goto, S., Migimatsu, H., DBGET/LinkDB: An integrated database retrieval system (1998) Pacific Symposium on Biocomputing' 98, pp. 683-694. , Altman RB, Dunker AK, Hunter L, Klein TE (Eds.), World Scientific; Schoof, H., Zaccaria, P., Gundlach, H., MIPS Arabidopsis thaliana Database (MatDB): An integrated biological knowledge resource based on the first complete plant genome (2002) Nucl. Acids Res., 30, pp. 91-93; The FlyBase database of the Drosophila Genome Projects and community literature. The FlyBase Consortium (1999) Nucl. Acids Res., 27, pp. 85-88; Stein, L., Sternberg, P., Durbin, R., Thierry-Mieg, J., Spieth, J., Worm Base: Network access to the genome and biology of Caenorhabditis elegans (2001) Nuc. Acids Res., 29, pp. 82-86; Birney, E., Bateman, A., Clamp, M.E., Hubbard, T.J., Mining the draft human genome (2001) Nature, 409, pp. 827-828; Dowell, R.D., Jokerst, R.M., Day, A., Eddy, S.R., Stein, L., The distributed annotation system (2001) BMC. Bioinfor., 2, p. 7; Frishman, D., Albermann, K., Hani, J., Functional and structural genomics using PEDANT (2001) Bioinformatics, 17, pp. 44-57; Andrade, M.A., Brown, N.P., Leroy, C., Automated genome sequence analysis and annotation (1999) Bioinformatics, 15, pp. 391-412; Tatusov, R.L., Koonin, E.V., Lipman, D.J., A genomic perspective on protein families (1997) Science, 278, pp. 631-637; Kanehisa, M., Goto, S., KEGG: Kyoto encyclopedia of genes and genomes (2000) Nuc. Acids Res., 28, pp. 27-30; Qian, J., Stenger, B., Wilson, C.A., PartsList: A web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information (2001) Nuc. Acids Res., 29, pp. 1750-1764; Besemer, J., Lomsadze, A., Borodovsky, M., GeneMarkS: A self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions (2001) Nuc. Acids Res., 29, pp. 2607-2618; Scherf, M., Klingenhoff, A., Werner, T., Highly specific localization of promoter regions in large genomic sequences by promoter inspector: A novel context analysis approach (2000) J. Mol. Biol., 297, pp. 599-606; Brett, D., Lehmann, G., Hanke, J., Gross, S., Reich, J., Bork, P., EST analysis online: WWW tools for detection of SNPs and alternative splice forms (2000) Trends Genet., 16, pp. 416-418; Sherlock, G., Hernandez-Boussard, T., Kasarskis, A., The stanford microarray database (2001) Nuc. Acids Res., 29, pp. 152-155; Thiede, B., Siejak, F., Dimmler, C., Jungblut, P.R., Rudel, T., A two dimensional electrophoresis database of a human Jurkat T-cell line (2000) Electrophoresis, 21, pp. 2713-2720; Sachidanandam, R., Weissman, D., Schmidt, S.C., A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms (2001) Nature, 409, pp. 928-933; Strausberg, R.L., Greenhut, S.F., Grouse, L.H., Schaefer, C.F., Buetow, K.H., In silico analysis of cancer through the cancer genome anatomy project (2001) Trends Cell Biol., 11, pp. S66-S71; Bernal, A., Ear, U., Kyrpides, N., Genomes OnLine Database (GOLD): A monitor of genome projects world-wide (2001) Nuc. Acids Res., 29, pp. 126-127; Mewes, H.W., Albermann, K., Bahr, M., Overview of the yeast genome (1997) Nature, 387, pp. 7-65; Mewes, H.W., Frishman, D., Güldener, U., MIPS: A database for genomes and protein sequences (2002) Nucl. Acids Res., 30, pp. 35-37; Riley, M., Functions of the gene products of Escherichia coli (1993) Microbiol. Rev., 57, pp. 862-952; Oliver, S.G., Winson, M.K., Kell, D.B., Baganz, F., Systematic functional analysis of the yeast genome (1998) Trends Biotechnol., 16, pp. 373-378; Entian, K.D., Schuster, T., Hegemann, J.H., Functional analysis of 150 deletion mutants in Saccharomyces cerevisiae by a systematic approach (1999) Mol. Gen. Genet., 262, pp. 683-702; Uetz, P., Giot, L., Cagney, G., A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae (2000) Nature, 403, pp. 623-627; Souciet, J., Aigle, M., Artiguenave, F., Genomic exploration of the hemiascomycetous yeasts: 1. A set of yeast species for molecular evolution studies (2000) FEBS Lett., 487, pp. 3-12; Frishman, D., Heumann, K., Lesk, A., Mewes, H.W., Comprehensive, comprehensible, distributed and intelligent databases: Current status (1998) Bioinformatics., 14, pp. 551-561; Achard, F., Vaysseix, G., Barillot, E., XML, bioinformatics and data integration (2001) Bioinformatics, 17, pp. 115-125; Creating the gene ontology resource: Design and implementation (2001) Genome Res., 11, pp. 1425-1433 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The review begins by providing a brief typology of biological databases on the Internet, illustrated by examples of the most influential resources of each kind. We then take an insider look at one typical on-line genomic resource - the yeast genome database hosted at the Munich Information Center for Protein Sequences (MIPS) - and explain how and why it has evolved from a basic sequence repository to a multidomain knowledge base. The role of community efforts in curating and annotating genome data is discussed. The crucial role of data integration and interoperability in developing next-generation genomic facilities is underscored. ER - TY - CHAP T1 - Interoperability A1 - Frisse, M E Y1 - 2017/// KW - Data representation KW - Data standards KW - FHIR KW - Health information exchange KW - Information Systems KW - Medical Informatics KW - SMART KW - Semantic interoperability JF - Key Advances in Clinical Informatics: Transforming Health Care through Health Information Technology SP - 69 EP - 77 N1 - Export Date: 10 September 2018 References: Collins, F.S., PCORnet: turning a dream into reality (2014) J. Am. Med. Inform. Assoc., 21 (4), pp. 576-577; (2017), http://www.commonwellalliance.org/, [cited 2017 January 10]. Available from: ; (2017) Home Page: Chesapeake Regional Information System for our Patients, , https://www.crisphealth.org/, [cited 2017 January 10]. Available from: ; (2017), https://www.directtrust.org/, The Direct Trust Home Page [cited 2017 January 10]. Available from: ; Dixon, B., (2016) Health Information Exchange: Navigating and Managing a Network of Health Information Systems, , Elsevier, Boston, MA; Dolin, R.H., Alschuler, L., Approaching semantic interoperability in Health Level Seven (2011) J. Am. Med. Inform. Assoc., 18 (1), pp. 99-103; (2017), https://www.epic.com/careeverywhere/, The Epic Systems Care Everywhere Network [cited 2017 January 10]. Available from: ; Frey, L.J., Bernstam, E.V., Denny, J.C., Precision medicine informatics (2016) J. Am. Med. Inform. Assoc., 23 (4), pp. 668-670; Frisse, M.E., The financial impact of health information exchange on emergency department care (2012) J. Am. Med. Inform. Assoc., 19 (3), pp. 328-333; What is Interoperability? (2013), http://www.himss.org/library/interoperability-standards/what-is, [cited 2016 June 1]. Available from: ; (2016), http://www.hl7.org/implement/standards/product_brief.cfm?product_id=7, CDA Release 2 [cited 2016 June 1]. Available from: ; Hudson, K.L., Collins, F.S., The 21st Century Cures Act-a view from the NIH (2017) N. Engl. J. Med., 376 (2), pp. 111-113; Indiana Health Information Exchange: Home Page (2017), http://www.ihie.org/, [cited 2017 January 10]. Available from: ; (2017), https://www.infoway-inforoute.ca/en/component/tags/tag/1166-health-information-exchange, Health Infoway Home Page [cited 2017 January 10]. Available from: ; Magrabi, F., A comparative review of patient safety initiatives for national health information technology (2013) Int. J. Med. Inform., 82 (5), pp. e139-e148; Mandel, J.C., SMART on FHIR: a standards-based, interoperable apps platform for electronic health records (2016) J. Am. Med. Inform. Assoc., 23 (5), pp. 899-908; Nelson, S.J., Normalized names for clinical drugs: RxNorm at 6 years (2011) J. Am. Med. Inform. Assoc., 18 (4), pp. 441-448; (2015) Connecting Health and Care for the Nation: A Shared Nationwide Interoperability Roadmap Final Version 1.0, , Office of the National Coordinator for Health Information Technology, Washington, DC; Park, H., Can a health information exchange save healthcare costs? Evidence from a pilot program in South Korea (2015) Int. J. Med. Inform., 84 (9), pp. 658-666; Park, Y.-T., Atalag, K., Current national approach to healthcare ICT standardization: focus on progress in New Zealand (2015) Healthcare Inform. Res., 21 (3), pp. 144-151; Peterson, J.F., Attitudes of clinicians following large-scale pharmacogenomics implementation (2016) Pharmacogenomics J., 16 (4), pp. 393-398; Pulley, J.M., Operational implementation of prospective genotyping for personalized medicine: the design of the Vanderbilt PREDICT project (2012) Clin. Pharmacol. Ther., 92 (1), pp. 87-95; (2013) Best Care at Lower Cost: The Path to Continuously Learning Health Care in America, , Committee on the Learning Health Care System in America; Institute of Medicine, M. Smith (Ed.); Stead, W.W., Kelly, B.J., Kolodner, R.M., Achievable steps toward building a national health information infrastructure in the United States (2005) J. Am. Med. Inform. Assoc., 12 (2), pp. 113-120; Tenenbaum, J.D., Sansone, S.-A., Haendel, M., A sea of standards for omics data: sink or swim? (2014) J. Am. Med. Inform. Assoc., 21 (2), pp. 200-203; (2016), http://sequoiaproject.org/, The Sequoia Project [cited 2017 January 12]. Available from: ; Zelmer, J., International health IT benchmarking: learning from cross-country comparisons (2016) J. Am. Med. Inform. Assoc; (2005), Ending the Document Game; Thompson, T.G., Brailer, D.J., The Decade of Health Information Technology: Delivering Consumer-Centric and Information-Rich Health Care Framework for Strategic Action (2004), p. 178. , Department of Health and Human Services, Washington, DCUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040383446&doi=10.1016%2fB978-0-12-809523-2.00005-4&partnerID=40&md5=cff27e89cfdce1cb60a1651e25c82721 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Interoperable health information technologies are essential for patient care, population health management, public health, and research. The term "interoperability" can be defined both functionally and technically. Interoperable systems allow for the exchange of health information from one system to another. This health information exchange can be realized through point-to-point capabilities of electronic health records or through dedicated technologies managed by separate health information organizations. An understanding of the current and future capabilities of interoperable systems requires a familiarity with data standards and health information exchange technologies. New types of devices and scientific data sources will necessitate ongoing efforts to realize the true potential of data through health information systems. © 2017 Elsevier Inc. All rights reserved. ER - TY - JOUR T1 - Sharing health data among general practitioners: The Nu.Sa. project A1 - Frontoni, E A1 - Mancini, A A1 - Baldi, M A1 - Paolanti, M A1 - Moccia, S A1 - Zingaretti, P A1 - Landro, V A1 - Misericordia, P Y1 - 2019/// JF - International Journal of Medical Informatics VL - 129 SP - 267 EP - 274 DO - 10.1016/j.ijmedinf.2019.05.016 N2 - ©2019 Elsevier B.V. Today, e-health has entered the everyday work flow in the form of a variety of healthcare providers. General practitioners (GPs) are the largest category in the public sanitary service, with about 60,000 GPs throughout Italy. Here, we present the Nu.Sa. project, operating in Italy, which has established one of the first GP healthcare information systems based on heterogeneous data sources. This system connects all providers and provides full access to clinical and health-related data. This goal is achieved through a novel technological infrastructure for data sharing based on interoperability specifications recognised at the national level for messages transmitted from GP providers to the central domain. All data standards are publicly available and subjected to continuous improvement. Currently, the system manages more than 5,000 GPs with about 5,500,000 patients in total, with 4,700,000 pharmacological e-prescriptions and 1,700,000 e-prescriptions for laboratory exams per month. Hence, the Nu.Sa. healthcare system that has the capacity to gather standardised data from 16 different form of GP software, connecting patients, GPs, healthcare organisations, and healthcare professionals across a large and heterogeneous territory through the implementation of data standards with a strong focus on cybersecurity. Results show that the application of this scenario at a national level, with novel metrics on the architecture's scalability and the software's usability, affect the sanitary system and on GPs' professional activities. ER - TY - JOUR T1 - Semantic data interoperability, digital medicine, and e-health in infectious disease management: a review A1 - Gansel, X A1 - Mary, M A1 - van Belkum, A Y1 - 2019/// JF - European Journal of Clinical Microbiology and Infectious Diseases VL - 38 IS - 6 SP - 1023 EP - 1034 DO - 10.1007/s10096-019-03501-6 N2 - ©2019, Springer-Verlag GmbH Germany, part of Springer Nature. Disease management requires the use of mixed languages when discussing etiology, diagnosis, treatment, and follow-up. All phases require data management, and, in the optimal case, such data are interdisciplinary and uniform and clear to all those involved. Such semantic data interoperability is one of the technical building blocks that support emerging digital medicine, e-health, and P4-medicine (predictive, preventive, personalized, and participatory). In a world where infectious diseases are on a trend to become hard-to-treat threats due to antimicrobial resistance, semantic data interoperability is part of the toolbox to fight more efficiently against those threats. In this review, we will introduce semantic data interoperability, summarize its added value, and analyze the technical foundation supporting the standardized healthcare system interoperability that will allow moving forward to e-health. We will also review current usage of those foundational standards and advocate for their uptake by all infectious disease-related actors. ER - TY - CONF T1 - Non-spatial and geospatial semantic query of health information A1 - Gao, S A1 - Anton, F A1 - Mioc, D A1 - Boley, H Y1 - 2012/// KW - Computer programming languages KW - Disease Outbreaks KW - Geo-spatial data KW - Geospatial data KW - Health KW - Health informations KW - Machine understanding KW - Ontologies KW - Ontologies and rules KW - Ontology KW - Photogrammetry KW - Public health KW - Pulmonary diseases KW - Remote sensing KW - Respiratory diseases KW - RuleML KW - Semantic interoperability KW - Semantics KW - Spatial informations KW - Spatial semantics VL - 39 SP - 167 EP - 172 N1 - Cited By :1 Export Date: 10 September 2018 References: Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P., (2003) The Description Logic Handbook, , Cambridge University Press, Cambridge, UK, New York; Berners-Lee, T., Hendler, J., Lassila, O., (2001) The Semantic Web. Scientific American; Bishr, Y., Overcoming the semantic and other barriers to GIS interoperability (1998) International Journal of Geographical Information Science, 12, pp. 299-314; Bishr, Y.A., Pundt, H., Ruther, C., Proceeding on the road of semantic interoperability-design of a semantic mapper based on a case study from transportation (1999) Proceedings of INTEROPP'99: 2nd International Conference on Interoperating Geographic Information Systems, pp. 203-215; Clementini, E., Di Felice, P., A comparison of methods for representing topological relationships (1994) Inf. Sci., 80, pp. 1-34; Clementini, E., Di Felice, P., A model for representing topological relationships between complex geometric features in spatial databases (1996) Inf. Sci., 90, pp. 121-136; Egenhofer, M.J., Reasoning about binary topological relations (1991) Lecture Notes in Computer Science, 525, pp. 143-160; Grosof, B.N., Horrocks, I., Volz, R., Decker, S., Description logic programs: Combining logic programs with description logic (2003) Twelfth International World Wide Web Conference; Gruber, T.R., A translation approach to portable ontology specifications (1993) Knowledge Acquisition, 5, pp. 199-220; Jones, C.B., Abdelmoty, A.I., Fu, G., Maintaining ontologies for geographical information retrieval on the web (2003) Lecture Notes in Computer Science, 2888, pp. 934-951; Kammersell, W., Dean, M., Conceptual search: Incorporating geospatial data into semantic queries (2006) Terra Cognita-Directions to the Geospatial Semantic Web; Kieler, B., Derivation of semantic relationships between different ontologies with the help of geometry (2008) Workshop "Semantic Web Meets Geospatial Applications", p. 2008; Klien, E., Lutz, M., The role of spatial relations in automating the semantic annotation of geodata (2005) Lecture Notes in Computer Science, 3693, pp. 133-148; Lee, Y., Supekar, K., Geller, J., Ontology integration experienced on medical terminologies (2006) J. Comput. Biol. Med., 36, pp. 893-919; Lober, W.B., Karras, B.T., Wagner, M.M., Overhage, J.M., Davidson, A.J., Fraser, H., Trigg, L.J., Tsui, F., Roundtable on bioterrorism detection: Information system-based surveillance (2002) Journal of the American Medical Informatics Association, 9, pp. 105-115; Lutz, M., Riedemann, C., Probst, F., A classification framework for approaches to achieving semantic interoperability between GI web services (2003) Spatial Information Theory, Proceedings, 2825, pp. 186-203; McKenney, M., Pauly, A., Praing, R., Schneider, M., Local topological relationships for complex regions (2007) Lecture Notes in Computer Science, LNCS, 4605, pp. 203-220; (2012), http://www.jdrew.org/oojdrew/, Available online (28. Jan. 2012; McLafferty, S.L., GIS and health care (2003) Annual Review of Public Health, 24, pp. 25-42; Pérez-Rey, D., Maojo, V., García-Remesal, M., Alonso-Calvo, R., Billhardt, H., Martin-Sánchez, F., Sousa, A., ONTOFUSION: Ontology-based integration of genomic and clinical databases (2006) Comput. Biol. Med., 36, pp. 712-730; Perry, M., Sheth, A., Arpinar, I.B., Geospatial and temporal semantic analytics (2007) Book Geospatial and Temporal Semantic Analytics;, , Karimi, H. A., Ed; Rashid, A., Shariff, B.M., Egenhofer, M.J., Mark, D.M., Natural-language spatial relations between linear and areal objects: The topology and metric of english-language terms (1998) International Journal of Geographical Information Science, 12, pp. 215-245; (2010), http://www.w3.org/2005/rules/wiki/RIF_Working_Group/, Available online(14 Oct. 2010); Ryan, A., Towards semantic interoperability in healthcare: Ontology mapping from SNOMED-CT to HL7 version 3 (2006) Proceedings of the Second Australasian Workshop on Advances in Ontologies, p. 2006; Schneider, M., Implementing topological predicates for complex regions (2002) Proceedings of the International Symposium on Spatial Data Handling, 2002, pp. 313-328; (2004), http://www.w3.org/Submission/SWRL/, Available online: (21. May 2004; (2005), http://www.w3.org/Submission/SWSF-SWSL/, Available online: (9 Sep. 2005); Smart, P.D., Abdelmoty, A.I., El-Geresy, B.A., Jones, C.B., A framework for combining rules and geo-ontologies (2007) First International Conference, RR, 2007, pp. 133-147; (2012), http://www.ruleml.org/, Available online (4 Apr. 2012; (2012) JTS Topology Suite, , http://www.vividsolutions.com/jts/jtshome.htm, Available online: (29 Apr. 2012; (2005), http://www.w3.org/Submission/WRL/, Available online: (9 Sep. 2005)UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84918494900&partnerID=40&md5=5288f4b58789d4249a5f1c2bf6e5101d RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - With the growing amount of health information and frequent outbreaks of diseases, the retrieval of health information is given more concern. Machine understanding of spatial information can improve the interpretation of health data semantics. Most of the current research focused on the non-spatial semantics of health data, using ontologies and rules. Utilizing the spatial component of health data can assist in the understanding of health phenomena. This research proposes a semantic health information query architecture that allows the incorporation of both non-spatial semantics and geospatial semantics in health information integration and retrieval. ER - TY - JOUR T1 - Online GIS services for mapping and sharing disease information A1 - Gao, S A1 - Mioc, D A1 - Anton, F A1 - Yi, X A1 - Coleman, D J Y1 - 2008/// KW - Adolescent KW - Adult KW - Aged KW - Aged, 80 and over KW - Canada KW - Child KW - Child, Preschool KW - Communicable Diseases KW - Disease Outbreaks KW - Female KW - Geographic Information Systems KW - Humans KW - Infant KW - Infant, Newborn KW - Information Dissemination KW - Internet KW - Maine KW - Male KW - Maps as Topic KW - Middle Aged KW - New Brunswick KW - Population Surveillance KW - United States KW - adolescent KW - adult KW - aged KW - article KW - audiovisual equipment KW - child KW - communicable disease KW - epidemic KW - female KW - geographic information system KW - health survey KW - human KW - infant KW - information dissemination KW - male KW - methodology KW - middle aged KW - newborn KW - preschool child JF - International Journal of Health Geographics VL - 7 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-41749101487&doi=10.1186%2F1476-072X-7-8&partnerID=40&md5=d7140286d19561782a7f8c301f0d733c N1 - Cited By :51 Export Date: 10 September 2018 References: Koch, T., (2005) Cartographies of Disease: Maps, Mapping, and Medicine, , ESRI Press; Gupta, R., Shriram, R., Disease surveillance and monitoring using GIS (2004) 7th Annual International Conference Map India, , http://www.gisdevelopment.net/application/health/planning/pdf/mi04054.pdf; Boulos, M.N., Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in United Kingdom (2004) International Journal of Health Geographics, 3, p. 1. , 343292 14748927 10.1186/1476-072X-3-1; Benneyan, J.C., Satz, D., Flowers, S.H., Development of a Web-based multifacility healthcare surveillance information system (2000) J Healthc Inf Manag, 14 (3), pp. 19-26. , 11186795; Edberg, S.C., Global Infectious Diseases and Epidemiology Network (GIDEON): A world wide Web-based program for diagnosis and informatics in infectious diseases (2005) Clin Infect Dis, 40 (1), pp. 123-126. , 10.1086/426549 15614701; Boulos, M.N., Web GIS in practice III: Creating a simple interactive map of England's strategic Health Authorities using Google Maps API, Google Earth KML, and MSN Virtual Earth Map Control (2005) International Journal of Health Geographics, 4, p. 22. , 1242244 16176577 10.1186/1476-072X-4-22; Inoue, M., Hasegawa, S., Suyama, A., Meshitsuka, S., Automated graphic image generation system for effective representation of infectious disease surveillance data (2003) Computer Methods and Programs in Biomedicine, 72 (3), pp. 251-256. , 10.1016/S0169-2607(02)00129-3 14554138; Blanton, J.D., Manangan, A., Manangan, J., Hanlon, C.A., Slate, D., Rupprecht, C.E., Development of a GIS-based, real-time Internet mapping tool for rabies surveillance (2006) International Journal of Health Geographics, 5, p. 47. , 1635048 17078890 10.1186/1476-072X-5-47; Qian, Z., Zhang, L., Yang, J., Yang, C., Global SARS information WebGIS design and development (2004) International Geoscience and Remote Sensing Symposium (IGARSS), 5, pp. 2861-2863. , http://ieeexplore.ieee.org/iel5/9436/29948/01370289.pdf; Kamadjeu, R., Tolentino, H., Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: A proof of concept applied to the expanded program on immunization data (2006) International Journal of Health Geographics, 5, p. 24. , 1523338 16749942 10.1186/1476-072X-5-24; Foody, G.M., GIS: Health applications (2006) Progress in Physical Geography, 30 (5), pp. 691-695. , 10.1177/0309133306071152; Greene, S.K., Schmidt, M.A., Stobierski, M.G., Wilson, M.L., Spatio-temporal pattern of viral meningitis in Michigan, 1993-2001 (2005) Journal of Geographical Systems, 7 (1), pp. 85-99. , 10.1007/s10109-005-0151-x; Greiling, D.A., Jacquez, G.M., Kaufmann, A.M., Rommel, R.G., Space-time visualization and analysis in the Cancer Atlas Viewer (2005) Journal of Geographical Systems, 7 (1), pp. 67-84. , 10.1007/s10109-005-0150-y; Bishr, Y., Overcoming the semantic and other barriers to GIS interoperability (1998) International Journal of Geographical Information Science, 12, pp. 299-314. , 10.1080/136588198241806; Zeng, D., Chen, H., Tseng, C., Larson, C.A., Eidson, M., Gotham, I., Lynch, C., Ascher, M., Towards a national infectious disease information infrastructure: A case study in West Nile virus and botulism (2004) Proceedings of the 2004 Annual National Conference on Digital Government Research, , http://dgrc.org/dgo2004/disc/presentations/crisis/zeng.pdf; Boulos, M.N., Honda, K., Web GIS in practice IV: Publishing your health maps and connecting to remote WMS sources using the Open Source UMN MapServer and DM Solutions MapLab (2006) International Journal of Health Geographics, 5, p. 6. , 1352347 16420699 10.1186/1476-072X-5-6; Bell, B.S., Hoskins, R.E., Pickle, L.W., Wartenberg, D., Current practices in spatial analysis of cancer data: Mapping health statistics to inform policymakers and the public (2006) International Journal of Health Geographics, 5, p. 49. , 1647272 17092353 10.1186/1476-072X-5-49; Leitner, M., Curtis, A., A first step towards a framework for presenting the location of confidential point data on maps-results of an empirical perceptual study (2006) International Journal of Geographical Information Science, 20 (7), pp. 813-822. , 10.1080/13658810600711261; Ogao, P.J., A tool for exploring space-time patterns: An animation user research (2006) International Journal of Health Geographics, 5, p. 35. , 1570344 16938138 10.1186/1476-072X-5-35; Web Map Server Implementation Specification, , http://portal.opengeospatial.org/files/index.php?artifact_id=14416, OGC; Styled Layer Descriptor Application Profile of the Web Map Service, , http://portal.opengeospatial.org/files/?artifact_id=22364, OGC; Web Map Context Documents, , http://portal.opengeospatial.org/files/?artifact_id=8618, OGC; Tang, T., Zhao, J., Coleman, D.J., Design of a GIS-enabled Online Discussion Forum for Participatory Planning (2005) Proceedings of the 4th Annual Public Participation GIS Conference, , http://downloads2.esri.com/campus/uploads/library/pdfs/55426.pdf, Cleveland State University, Cleveland, Ohio, USA, August; Zhao, J., Coleman, D.J., GeoDF: Towards a SDI-based PPGIS application for E-Governance (2006) Proceedings of the GSDI 9 Conference, , http://gsdidocs.org/gsdiconf/GSDI-9/papers/TS9.3paper.pdf, Santiago, Chile, 6-10 November RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: Disease data sharing is important for the collaborative preparation, response, and recovery stages of disease control. Disease phenomena are strongly associated with spatial and temporal factors. Web-based Geographical Information Systems provide a real-time and dynamic way to represent disease information on maps. However, data heterogeneities, integration, interoperability, and cartographical representation are still major challenges in the health geographic fields. These challenges cause barriers in extensively sharing health data and restrain the effectiveness in understanding and responding to disease outbreaks. To overcome these challenges in disease data mapping and sharing, the senior authors have designed an interoperable service oriented architecture based on Open Geospatial Consortium specifications to share the spatio-temporal disease information. Results: A case study of infectious disease mapping across New Brunswick (Canada) and Maine (USA) was carried out to evaluate the proposed architecture, which uses standard Web Map Service, Styled Layer Descriptor and Web Map Context specifications. The case study shows the effectiveness of an infectious disease surveillance system and enables cross-border visualization, analysis, and sharing of infectious disease information through interactive maps and/or animation in collaboration with multiple partners via a distributed network. It enables data sharing and users' collaboration in an open and interactive manner. Conclusion: In this project, we develop a service oriented architecture for online disease mapping that is distributed, loosely coupled, and interoperable. An implementation of this architecture has been applied to the New Brunswick and Maine infectious disease studies. We have shown that the development of standard health services and spatial data infrastructure can enhance the efficiency and effectiveness of public health surveillance. © 2008 Gao et al; licensee BioMed Central Ltd. ER - TY - CONF T1 - Geospatial services for decision support on public health A1 - Gao, S A1 - Mioc, D A1 - Yi, X A1 - Anton, F A1 - Oldfield, E Y1 - 2008/// KW - Decision making KW - Decision support KW - Decision support systems KW - Decision supports KW - Different services KW - Distributed data KW - GIS KW - Geo-spatial services KW - Geographic information systems KW - Health KW - Health informations KW - Health professionals KW - Hypothesis generation KW - Information dissemination KW - Internet/web KW - Interoperability KW - Mapping KW - Portals KW - Public health KW - Public health systems KW - Remote sensing KW - Reusability KW - Websites KW - XML VL - 37 SP - 1361 EP - 1366 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044166130&partnerID=40&md5=e9980f68539ff5cd3df2d623e867537b N1 - Export Date: 10 September 2018 References: Albert, D.P., Gesler, W.M., Levergood, B., (2000) Spatial Analysis, GIS and Remote Sensing: Applications in the Health Sciences, , Ann Arbor Press, Chelsea, MI; Bedard, Y., Bernier, E., Supporting multiple representations with spatial view management and the concept of "VUEL" (2002) Proceedings of Joint Workshop on Multi-scale Representations of Spatial Data, ISPRS WG IV/3, ICA Commission on Map Generalisation, , Ottawa, Canada, July 7-8; Benneyan, J.C., Satz, D., Flowers, S.H., Development of a web-based multifacility healthcare surveillance information system (2000) Journal of Healthcare Information Management, 14 (3), pp. 19-26; Blanton, J.D., Manangan, A., Manangan, J., Hanlon, C.A., Slate, D., Rupprecht, C.E., Development of a GIS-based, realtime internet mapping tool for rabies surveillance (2006) International Journal of Health Geographics, p. 5; Boulos, M.N., Web GIS in practice III: Creating a simple interactive map of England's strategic health authorities using google maps api, google earth kml, and msn virtual earth map control (2005) International Journal of Health Geographics, p. 4; Boulos, M.N., Honda, K., Web GIS in practice IV: Publishing your health maps and connecting to remote wms sources using the open source umn mapserver and dm solutions maplab (2006) International Journal of Health Geographics, p. 5; Cromley, E.K., McLafferty, S., (2002) GIS and Public Health, , New York: Guilford Press; Edberg, S.C., Global infectious diseases and epidemiology network (gideon): A world wide web-based program for diagnosis and informatics in infectious diseases (2005) Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, 40 (1), pp. 123-126; He, L.L., Yang, J.G., Deng, C., Qi, H.N., Multi-agent framework for service-oriented geospatial computing (2005) 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, pp. 143-148; Inoue, M., Hasegawa, S., Suyama, A., Meshitsuka, S., Automated graphic image generation system for effective representation of infectious disease surveillance data (2003) Computer Methods and Programs in Biomedicine, 72 (3), pp. 251-256; Kamadjeu, R., Tolentino, H., Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: A proof of concept applied to the expanded program on immunization data (2006) International Journal of Health Geographics, p. 5; Leitner, M., Curtis, A., A first step towards a framework for presenting the location of confidential point data on mapsresults of an empirical perceptual study (2006) International Journal of Geographical Information Science, 20 (7), pp. 813-822; McLeod, K.S., Our sense of snow: The myth of John snow in medical geography (2000) Social Science and Medicine, 50 (7-8), pp. 923-935; (2001) Web Map Service Implementation Specification, , http://portal.opengeospatial.org/files/?artifact_id=1058, OGC; (2005) OpenGIS Web Processing Service, , http://portal.opengeospatial.org/files/?artifact_id=13149, OGC; (2005) Web Feature Service Implementation Specification, , http://portal.opengeospatial.org/files/?artifact_id=8339, OGC; Qian, Z., Zhang, L., Yang, J., Yang, C., Global SARS information webgis design and development (2004) International Geoscience and Remote Sensing Symposium (IGARSS), pp. 2861-2863; (2007) The World Health Report 2007: A Safer Future: Global Public Health Security in the 21st Century, , WHO; Wright, D.J., O'Dea, E., Cushing, J.B., Cuny, J.E., Toomey, D.R., Why web GIS may not be enough: A case study with the virtual research vessel (2003) Marine Geodesy, 26 (1-2), pp. 73-86; Zeng, D., Chen, H., Tseng, C., Larson, C.A., Eidson, M., Gotham, I., Lynch, C., Ascher, M., Towards a national infectious disease information infrastructure: A case study in west nile virus and botulism (2004) Proceedings of Proceedings of the 2004 Annual National Conference on Digital Government Research, , Seattle, Washington RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Sharing of health information is critical for preventing disease, responding to emergencies, educating the public and policy makers. Protecting privacy and confidentiality of health information remain important cornerstones of the public health system, however many health professionals and authorities do not have the ability to visualize health information to make time-sensitive decisions, since they do not have the time, money, or skills to statistically analyze vast amounts of distributed data and render aggregated results into a geographic interface for quick interpretation. The technology to do so, web based geographic information systems and related standards, has matured yet confidence in such technology to visualize or share health information is only beginning to emerge. Currently, four major problems still exist in health geographic applications. They are related to health mapping methods, mapping variables, reusability of health applications, and interoperability issues. To handle these problems, we designed a Health Representation XML schema and SOA based architecture to support health data sharing and representation. The schema makes it possible to exchange the statistical results of health data as well as representation through XML and GML. The OGC services such as WMS, WFS, and WPS enable the statistical exploration and representation of health information. A Web-portal is developed to support the integration of different services for visualization of health maps, hypothesis generation, and decision making. This architecture provides quick access to spatial and health data for understanding the trends in diseases, and promotes the growth and enrichment of the SDI in the public health sector. © 2008 International Society for Photogrammetry and Remote Sensing. All rights reserved. ER - TY - JOUR T1 - An Assessment of Information Exchange Practices, Challenges, and Opportunities to Support US Disease Surveillance in 3 States A1 - Garcia, M C A1 - Garrett, N Y A1 - Singletary, V A1 - Brown, S A1 - Hennessy-Burt, T A1 - Haney, G A1 - Link, K A1 - Tripp, J A1 - Mac Kenzie, W R A1 - Yoon, P Y1 - 2018/// JF - Journal of Public Health Management and Practice VL - 24 IS - 6 SP - 546 EP - 553 DO - 10.1097/PHH.0000000000000625 N2 - ©2018 Wolters Kluwer Health, Inc. All rights reserved. Background: State and local public health agencies collect and use surveillance data to identify outbreaks, track cases, investigate causes, and implement measures to protect the public's health through various surveillance systems and data exchange practices. Purpose: The purpose of this assessment was to better understand current practices at state and local public health agencies for collecting, managing, processing, reporting, and exchanging notifiable disease surveillance information. Methods: Over an 18-month period (January 2014-June 2015), we evaluated the process of data exchange between surveillance systems, reporting burdens, and challenges within 3 states (California, Idaho, and Massachusetts) that were using 3 different reporting systems. Results: All 3 states use a combination of paper-based and electronic information systems for managing and exchanging data on reportable conditions within the state. The flow of data from local jurisdictions to the state health departments varies considerably. When state and local information systems are not interoperable, manual duplicative data entry and other work-arounds are often required. The results of the assessment show the complexity of disease reporting at the state and local levels and the multiple systems, processes, and resources engaged in preparing, processing, and transmitting data that limit interoperability and decrease efficiency. Conclusions: Through this structured assessment, the Centers for Disease Control and Prevention (CDC) has a better understanding of the complexities for surveillance of using commercial off-the-shelf data systems (California and Massachusetts), and CDC-developed National Electronic Disease Surveillance System Base System. More efficient data exchange and use of data will help facilitate interoperability between National Notifiable Diseases Surveillance Systems. ER - TY - JOUR T1 - Towards Semantic Interoperability for Electronic Health Records A1 - Garde, S A1 - Knaup, P A1 - Hovenga, E J S A1 - Heard, S Y1 - 2007/// KW - Semantics KW - computerized medical record systems KW - domain knowledge governance KW - openEHR archetypes KW - paper KW - semantic interoperability PB - Schattauer GmbH JF - Methods of Information in Medicine VL - 46 IS - 3 SP - 332 EP - 343 UR - http://www.thieme-connect.de/DOI/DOI?10.1160/ME5001 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 -Objectives: In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability.
ER - TY - JOUR T1 - Healthcare associated infections: An interoperable infrastructure for multidrug resistant organism surveillance A1 - Gazzarata, R A1 - Monteverde, M E A1 - Ruggiero, C A1 - Maggi, N A1 - Palmieri, D A1 - Parruti, G A1 - Giacomini, M Y1 - 2020/// JF - International Journal of Environmental Research and Public Health VL - 17 IS - 2 DO - 10.3390/ijerph17020465 N2 - ©2020 by the authors. Licensee MDPI, Basel, Switzerland. Prevention and surveillance of healthcare associated infections caused by multidrug resistant organisms (MDROs) has been given increasing attention in recent years and is nowadays a major priority for health care systems. The creation of automated regional, national and international surveillance networks plays a key role in this respect. A surveillance system has been designed for the Abruzzo region in Italy, focusing on the monitoring of the MDROs prevalence in patients, on the appropriateness of antibiotic prescription in hospitalized patients and on foreseeable interactions with other networks at national and international level. The system has been designed according to the Service Oriented Architecture (SOA) principles, and Healthcare Service Specification (HSSP) standards and Clinical Document Architecture Release 2 (CDAR2) have been adopted. A description is given with special reference to implementation state, specific design and implementation choices and next foreseeable steps. The first release will be delivered at the Complex Operating Unit of Infectious Diseases of the Local Health Authority of Pescara (Italy). ER - TY - JOUR T1 - Factors influencing harmonized health data collection, sharing and linkage in Denmark and Switzerland: A systematic review A1 - Geneviève, L D A1 - Martani, A A1 - Mallet, M C A1 - Wangmo, T A1 - Elger, B S Y1 - 2019/// JF - PLoS ONE VL - 14 IS - 12 DO - 10.1371/journal.pone.0226015 N2 - ©2019 Geneviève et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction The digitalization of medicine has led to a considerable growth of heterogeneous health datasets, which could improve healthcare research if integrated into the clinical life cycle. This process requires, amongst other things, the harmonization of these datasets, which is a prerequisite to improve their quality, re-usability and interoperability. However, there is a wide range of factors that either hinder or favor the harmonized collection, sharing and linkage of health data. Objective This systematic review aims to identify barriers and facilitators to health data harmonization—including data sharing and linkage—by a comparative analysis of studies from Denmark and Switzerland. Methods Publications from PubMed, Web of Science, EMBASE and CINAHL involving cross-institutional or cross-border collection, sharing or linkage of health data from Denmark or Switzerland were searched to identify the reported barriers and facilitators to data harmonization. Results Of the 345 projects included, 240 were single-country and 105 were multinational studies. Regarding national projects, a Swiss study reported on average more barriers and facilitators than a Danish study. Barriers and facilitators of a technical nature were most frequently reported. Conclusion This systematic review gathered evidence from Denmark and Switzerland on barriers and facilitators concerning data harmonization, sharing and linkage. Barriers and facilitators were strictly interrelated with the national context where projects were carried out. Structural changes, such as legislation implemented at the national level, were mirrored in the projects. This underlines the impact of national strategies in the field of health data. Our findings also suggest that more openness and clarity in the reporting of both barriers and facilitators to data harmonization constitute a key element to promote the successful management of new projects using health data and the implementation of proper policies in this field. Our study findings are thus meaningful beyond these two countries. ER - TY - JOUR T1 - SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services. A1 - Gessler, Damian D G A1 - Schiltz, Gary S A1 - May, Greg D A1 - Avraham, Shulamit A1 - Town, Christopher D A1 - Grant, David A1 - Nelson, Rex T Y1 - 2009/// KW - Semantics PB - BioMed Central JF - BMC bioinformatics VL - 10 SP - 309 EP - 309 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND SSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies. RESULTS There are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at http://sswap.info (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at http://sswap.info/protocol.jsp, developer tools at http://sswap.info/developer.jsp, and a portal to third-party ontologies at http://sswapmeet.sswap.info (a "swap meet"). CONCLUSION SSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing the concept of a canonical yet mutable OWL DL graph that allows data and service providers to describe their resources, to allow discovery servers to offer semantically rich search engines, to allow clients to discover and invoke those resources, and to allow providers to respond with semantically tagged data. SSWAP allows for a mix-and-match of terms from both new and legacy third-party ontologies in these graphs. ER - TY - CONF T1 - COSMOS: A web-based, collaborative knowledge system using ontologies and managing uncertainty A1 - Giannoulis, M A1 - Kondylakis, H A1 - Marakakis, E Y1 - 2018/// KW - Collaborative update KW - Conflict detection KW - Decision support systems KW - Health KW - Interoperability KW - Knowledge based systems KW - Knowledge management KW - Ontology KW - Patient monitoring KW - Temporal reasoning KW - Temporal rule KW - Temporal rules KW - Uncertainty SP - 441 EP - 448 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049894110&doi=10.1145%2F3197768.3201555&partnerID=40&md5=2ac7dfe534f2e9b6a56a8788ff77aea4 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Giannoulis, Kondylakis, Marakakis - 2018 - COSMOS A web-based, collaborative knowledge system using ontologies and managing uncertainty.pdf N1 - Export Date: 10 September 2018 References: Bader, A.A., Decision support system and knowledge-based strategic management (2015) Procedia Computer Science, 65, pp. 278-284; Knaus, W., Wagner, D., Draper, E., The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill-hospitalized adults (1991) Chest, 100 (6), pp. 1619-1636; Bury, J., Hurt, C., Bateman, C., (2002) LISA: A Clinical Information and Decision Support System for Childhood Acute Lymphoblastic Leukaemia, , AMIA; Vardell, E., Moore, M., Isabel, a clinical decision support system (2011) Medical Reference Services Quarterly, 30 (2), pp. 158-166; Aikins, J.S., Kunz, J.C., Shortliffe, E.H., Fallat, R.J., PUFF: An expert system for interpretation of pulmonary function data (1983) Comp. Biom. Res., 16 (3), pp. 199-208; Boulme, R., Gonzalez, D., Schmit, J.C., Storing genotypic resistance data and linking to other clinical information (2004) XV International AIDS Conference; Giannoulis, M., (2017) Development of A Web-Based Knowledge System with Collaborative Update of Knowledge by Using Ontologies and Managing Uncertainty, , Bachelor Thesis, Technological Institute of Crete; Giannoulis, M., Marakakis, E., Kondylakis, H., Developing a collaborative knowledge system for Cancer Diseases (2017) IEEE CBMS; Kondylakis, H., Bucur, A., Dong, F., IManageCancer: Developing a platform for Empowering patients and strengthening self-management in cancer diseases (2017) IEEE CBMS; Kondylakis, H., Koumakis, L., Kazantzaki, E., Patient empowerment through personal medical recommendations (2017) MedInfo, 2015, p. 1117; Smiley, D., Pugh, E., Parisa, K., Mitchell, M., (2015) Apache Solr Enterprise Search Server, , Third Edition; Allen, J.F., Maintaining knowledge about temporal intervals (1983) Communications of The ACM, 26 (11), pp. 832-843; Schwalb, E., Vila, L., Temporal constraints: A survey (1998) Contstraints, 3 (2), pp. 127-149; Shortlife, E., (1976) Computer Based Medical Consultation MYCIN, , Elsevier; Barták, R., Morris, R., Venable, K.B., (2014) An Introduction to Constraint-Based Temporal Reasoning, , Morgan & Claypool; Koumakis, L., Kondylakis, H., Chatzimina, M., Designing smart analytical data services for a personal health framework (2016) pHealth, pp. 123-128 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The huge diversity, big quantity of data and information, and the requirements for knowledge extraction out of them put new challenges for knowledge management, synthesis, conflict detection and reasoning. In this paper, we present COSMOS, a knowledge system that fully addresses these challenges, in an efficient way, paving the way for a new generation of knowledge systems. Using our approach, it is possible for domain experts to generate temporal knowledge rules. As those rules are saved to our knowledge base, a conflict detection mechanism detects and solves rule conflicts. Then, an inference engine is able to perform efficiently, accurate decisions, based on available factual information using reasoning and handling uncertainty. Ontologies are used to model both the factual information and the data items in the rules enabling also interoperability with existing systems. To validate our approach, as an application scenario, we deploy our infrastructure in a health environment where doctors provide rules that are activated over a patient health record. Preliminary results indicate the benefits of our approach for decision support based on health data, successfully identifying adverse events and enabling intelligent patient monitoring. © 2018 Copyright is held by the owner/author(s). ER - TY - JOUR T1 - Improving interoperability and clinical data standards. A1 - Goldstein, D Y1 - 2003/// KW - Computer Communication Networks KW - Delivery of Health Care KW - Humans KW - Information Dissemination KW - Leadership KW - Medical Informatics KW - Public Health KW - Systems Integration KW - United States KW - article KW - computer network KW - health care delivery KW - human KW - information dissemination KW - leadership KW - medical informatics KW - public health KW - standard KW - system analysis JF - Managed care interface VL - 16 IS - 3 SP - 68 EP - 69 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037980253&partnerID=40&md5=91951b416346a70a5e5aaf2baf0b3851 N1 - Cited By :3 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} ER - TY - JOUR T1 - Terminology Services: Standard Terminologies to Control Health Vocabulary A1 - González Bernaldo de Quirós, F A1 - Otero, C A1 - Luna, D Y1 - 2018/// JF - Yearbook of medical informatics VL - 27 IS - 1 SP - 227 EP - 233 DO - 10.1055/s-0038-1641200 N2 - Georg Thieme Verlag KG Stuttgart. Healthcare Information Systems should capture clinical data in a structured and preferably coded format. This is crucial for data exchange between health information systems, epidemiological analysis, quality and research, clinical decision support systems, administrative functions, among others. Structured data entry is an obstacle for the usability of electronic health record (EHR) applications and their acceptance by physicians who prefer to document patient EHRs using "free text". Natural language allows for rich expressiveness but at the same time is ambiguous; it has great dependence on context and uses jargon and acronyms. Although much progress has been made in knowledge and natural language processing techniques, the result is not yet satisfactory enough for the use of free text in all dimensions of clinical documentation. In order to address the trade-off between capturing data with free text and at the same time coding data for computer processing, numerous terminological systems for the systematic recording of clinical data have been developed. The purpose of terminology services consists of representing facts that happen in the real world through database management in order to allow for semantic interoperability and computerized applications. These systems interrelate concepts of a particular domain and provide references to related terms with standards codes. In this way, standard terminologies allow the creation of a controlled medical vocabulary, making terminology services a fundamental component for health data management in the healthcare environment. The Hospital Italiano de Buenos Aires has been working in the development of its own terminology server. This work describes its experience in the field. ER - TY - JOUR T1 - Federated ontology-based queries over cancer data. A1 - González-Beltrán, Alejandra A1 - Tagger, Ben A1 - Finkelstein, Anthony Y1 - 2012/// KW - Information Dissemination PB - BioMed Central JF - BMC bioinformatics VL - 13 SP - S9 EP - S9 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND Personalised medicine provides patients with treatments that are specific to their genetic profiles. It requires efficient data sharing of disparate data types across a variety of scientific disciplines, such as molecular biology, pathology, radiology and clinical practice. Personalised medicine aims to offer the safest and most effective therapeutic strategy based on the gene variations of each subject. In particular, this is valid in oncology, where knowledge about genetic mutations has already led to new therapies. Current molecular biology techniques (microarrays, proteomics, epigenetic technology and improved DNA sequencing technology) enable better characterisation of cancer tumours. The vast amounts of data, however, coupled with the use of different terms - or semantic heterogeneity - in each discipline makes the retrieval and integration of information difficult. RESULTS Existing software infrastructures for data-sharing in the cancer domain, such as caGrid, support access to distributed information. caGrid follows a service-oriented model-driven architecture. Each data source in caGrid is associated with metadata at increasing levels of abstraction, including syntactic, structural, reference and domain metadata. The domain metadata consists of ontology-based annotations associated with the structural information of each data source. However, caGrid's current querying functionality is given at the structural metadata level, without capitalising on the ontology-based annotations. This paper presents the design of and theoretical foundations for distributed ontology-based queries over cancer research data. Concept-based queries are reformulated to the target query language, where join conditions between multiple data sources are found by exploiting the semantic annotations. The system has been implemented, as a proof of concept, over the caGrid infrastructure. The approach is applicable to other model-driven architectures. A graphical user interface has been developed, supporting ontology-based queries over caGrid data sources. An extensive evaluation of the query reformulation technique is included. CONCLUSIONS To support personalised medicine in oncology, it is crucial to retrieve and integrate molecular, pathology, radiology and clinical data in an efficient manner. The semantic heterogeneity of the data makes this a challenging task. Ontologies provide a formal framework to support querying and integration. This paper provides an ontology-based solution for querying distributed databases over service-oriented, model-driven infrastructures. ER - TY - JOUR T1 - Global health information networks get a boost A1 - Goth, G Y1 - 2006/// KW - Bureaucratic challenges KW - Disease Outbreaks KW - Disease control KW - Disease outbreaks KW - Distributed computer systems KW - Global Pandemic Initiative (GPI) KW - Health care KW - IBM (CO) KW - Information Services KW - Information retrieval KW - Interoperability JF - IEEE Distributed Systems Online VL - 7 IS - 7 SP - 4 EP - 4 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-33748160615&doi=10.1109%2FMDSO.2006.43&partnerID=40&md5=82c26ff54c0a9e348ec1a044c2425f82 N1 - Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - IBM and public health groups, including the World Health Organization and the US Centers for Disease Control and Prevention, announced the Global Pandemic Initiative (GPI) in May, 2006. The Initiative responds to concerns over the avian flu outbreaks around the world. IBM pledged to contribute several pieces of its healthcare technology portfolio to the open source community. This offer is intended to speed the flow of information about virulent disease outbreaks. Healthcare experts are seeing this GPI project and other projects like Eclipse Open Healthcare Framework, and the IOpen Gropu's Universeal Data Element framework, as an expansion of the interoperable and open source mindset among healthcare developers. Some experts see the technological challenges of these projects far outweighed by cultural restiveness among healthcare executives and providers. The initiatives like GPI are expected to give momentum to addressing both the technological and bureaucratic challenges. ER - TY - JOUR T1 - Evaluating the effect of data standardization and validation on patient matching accuracy A1 - Grannis, S J A1 - Xu, H A1 - Vest, J R A1 - Kasthurirathne, S A1 - Bo, N A1 - Moscovitch, B A1 - Torkzadeh, R A1 - Rising, J Y1 - 2019/// JF - Journal of the American Medical Informatics Association VL - 26 IS - 5 SP - 447 EP - 456 DO - 10.1093/jamia/ocy191 N2 - ©The Author(s) 2019. Objective: This study evaluated the degree to which recommendations for demographic data standardization improve patient matching accuracy using real-world datasets. Materials and Methods: We used 4 manually reviewed datasets, containing a random selection of matches and nonmatches. Matching datasets included health information exchange (HIE) records, public health registry records, Social Security Death Master File records, and newborn screening records. Standardized fields including last name, telephone number, social security number, date of birth, and address. Matching performance was evaluated using 4 metrics: sensitivity, specificity, positive predictive value, and accuracy. Results: Standardizing address was independently associated with improved matching sensitivities for both the public health and HIE datasets of approximately 0.6% and 4.5%. Overall accuracy was unchanged for both datasets due to reduced match specificity. We observed no similar impact for address standardization in the death master file dataset. Standardizing last name yielded improved matching sensitivity of 0.6% for the HIE dataset, while overall accuracy remained the same due to a decrease inmatch specificity.We noted no similar impact for other datasets. Standardizing other individual fields (telephone, date of birth, or social security number) showed no matching improvements. As standardizing address and last name improved matching sensitivity, we examined the combined effect of address and last name standardization, which showed that standardization improved sensitivity from 81.3% to 91.6% for the HIE dataset. Conclusions: Data standardization can improve match rates, thus ensuring that patients and clinicians have better data on which to make decisions to enhance care quality and safety. ER - TY - CONF T1 - Linking information systems for HIV care and research in Kenya A1 - Guidry, A F A1 - Walson, J L A1 - Abernethy, N F Y1 - 2010/// KW - Computer software KW - Data handling KW - Data integration KW - Developing Countries KW - Developing countries KW - Electronic medical record KW - Health KW - Information Systems KW - Information science KW - Information systems KW - Interoperability KW - Kenya KW - Management information systems KW - Medical computing KW - Ontology KW - Open Source Software KW - Population statistics KW - Research KW - Standards KW - data integration KW - data standards KW - electronic medical records KW - hiv KW - interoperability KW - ontologies KW - open source software SP - 531 EP - 535 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650981395&doi=10.1145%2F1882992.1883078&partnerID=40&md5=4b9bd5f1d42da5a3777427894d517b45 N1 - Cited By :1 Export Date: 10 September 2018 References: Abernethy, N., (2005) Automating Social Network Models for Tuberculosis Contact Investigation, , Stanford University; Chandrasekaran, B., Josephson, J., Benjamins, V., What are ontologies, and why do we need them? (1999) IEEE Intelligent Systems and Their Applications, 14 (1), pp. 20-26; NCBO BioPortal: RadLex, , http://bioportal.bioontology.org/ontologies/40885, accessed on May 2, 2010; OpenMRS - OpenMRS, , http://openmrs.org/wiki/OpenMRS, accessed on June 3, 2010; Clinical Trial Software, , http://openclinica.org/, accessed on June 3, 2010; Hannan, T.J., Rotich, J.K., Odero, W.W., Menya, D., Esamai, F., Einterz, R.M., Sidle, J., Tierney, W.M., The Mosoriot medical record system: Design and initial implementation of an outpatient electronic record system in rural Kenya International Journal of Medical Informatics, pp. 21-28. , 602000; Hillestad, R., Bigelow, J.H., Chaudhry, B., Dreyer, P., Greenberg, M.D., Meili, R.C., Ridgely, M.S., Taylor, R., (2008) Identity Crisis: An Examination of the Costs and Benefits of a Unique Patient Identifier for the U.S. Health Care System, , Rand Health; http://www.aidskenya.org/, National AIDS/STD Control Programme (NASCOP), accessed on May 2, 2010; Common Core Data Elements 2009 CSTE Position Statement 09-SI-01, , http://cste.org/ps2009/09-SI-01.pdf, accessed on May 2, 2010; Patient Monitoring Guidelines for HIV Care and Antiretroviral Therapy (Art ), , http://who.int/3by5/capacity/ptmonguidelinesfinalv1.pdf, accessed on May 2, 2010; Information Technology @ Johns Hopkins-Patient Identification System, , http://it.jhu.edu/fas/pid.html, accessed on June 3, 2010; NCBO BioPortal: Welcome to the NCBO BioPortal, , http://bioportal.bioontology.org/, accessed on May 2, 2010; http://loinc.org/, accessed on May 2, 2010; The Protege Ontology Editor and Knowledge Acquisition System, , http://protege.stanford.edu/, accessed on May 2, 2010; Unified Medical Language System (UMLS) - Home, , http://www.nlm.nih.gov/research/umls/, accessed on June 3, 2010; Health Level Seven International - Homepage, , http://www.hl7.org/, accessed on June 3, 2010 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The provision of HIV care in developing countries may involve complex and overlapping resources; including government-run facilities non-governmental organization (NGO) or international non-governmental organization (INGO) supported services and research affiliated clinics. These resources are often motivated and funded by distinct health priorities and as a result, standards for clinical data representation and exchange are rare and data management systems are often redundant. Open-source systems such as OpenMRS and OpenClinica provide an opportunity to leverage available systems to improve standards and increase interoperability. Nevertheless, continuity of care and data sharing between these systems remains a challenge, particularly in populations with changing health needs, high mobility, and inconsistent access to health resources. As a prerequisite to improving interoperability between systems, use cases for clinical information exchange are first identified. We then characterize data models from nine clinical information systems, standards, and ontologies pertinent to HIV clinical care and research in Kenya. The data fields commonly used as patient identifiers are summarized, including name, date of birth, family relations and location. Finally, we present a prototype ontology to describe data standards and to enable mapping between data elements in diverse information systems. © 2010 ACM. ER - TY - JOUR T1 - Harmonization may be counterproductive - At least for parts of Europe where public health research operates effectively A1 - Hakulinen, T A1 - Arbyn, M A1 - Brewster, D H A1 - Coebergh, J W A1 - Coleman, M P A1 - Crocetti, E A1 - Forman, D A1 - Gissler, M A1 - Katalinic, A A1 - Luostarinen, T A1 - Pukkala, E A1 - Rahu, M A1 - Storm, H A1 - Sund, R A1 - Törnberg, S A1 - Tryggvadottir, L Y1 - 2011/// KW - Computer Security KW - Europe KW - Humans KW - Population Surveillance KW - Public Health KW - computer security KW - health survey KW - human KW - legal aspect KW - note KW - public health JF - European Journal of Public Health VL - 21 IS - 6 SP - 686 EP - 687 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-82355181263&doi=10.1093%2Feurpub%2Fckr149&partnerID=40&md5=193143417fce61bdd77daf281723574a N1 - Cited By :10 Export Date: 5 April 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} ER - TY - JOUR T1 - Harmonizing clinical terminologies: driving interoperability in healthcare. A1 - Hamm, R A A1 - Knoop, S E A1 - Schwarz, P A1 - Block, A D A1 - Davis 4th., W L Y1 - 2007/// KW - Computer Communication Networks KW - Forms and Records Control KW - Medical Record Linkage KW - Quality Assurance, Health Care KW - Systems Integration KW - Vocabulary, Controlled KW - article KW - computer network KW - health care quality KW - linguistics KW - medical record KW - methodology KW - standard KW - system analysis JF - Medinfo. MEDINFO VL - 12 SP - 660 EP - 663 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-38449120110&partnerID=40&md5=4f7a956e8438bee666dcafe0818a6e9a N1 - Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Internationally, there are countless initiatives to build National Healthcare Information Networks (NHIN) that electronically interconnect healthcare organizations by enhancing and integrating current information technology (IT) capabilities. The realization of such NHINs will enable the simple and immediate exchange of appropriate and vital clinical data among participating organizations. In order for institutions to accurately and automatically exchange information, the electronic clinical documents must make use of established clinical codes, such as those of SNOMED-CT, LOINC and ICD-9 CM. However, there does not exist one universally accepted coding scheme that encapsulates all pertinent clinical information for the purposes of patient care, clinical research and population heatlh reporting. In this paper, we propose a combination of methods and standards that target the harmonization of clinical terminologies and encourage sustainable, interoperable infrastructure for healthcare. ER - TY - CHAP T1 - Semantic interoperability: Issue of standardizing medical vocabularies A1 - Hammond, W E Y1 - 2010/// JF - Ubiquitous Health and Medical Informatics: The Ubiquity 2.0 Trend and Beyond SP - 19 EP - 42 DO - 10.4018/978-1-61520-777-0.ch002 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84900598273&doi=10.4018%2F978-1-61520-777-0.ch002&partnerID=40&md5=b684c3f42e785d3f75ac833bc4b84e0e N1 - Cited By :1 Export Date: 5 April 2018 N2 - Semantic interoperability is the key to achieving global interoperability in healthcare information technology. The benefits are tremendous - the sharing of clinical data for multiple uses including patient care, research, reimbursement, audit and analyses, education, health surveillance, and many other uses. Patient safety, higher quality healthcare, more effective and efficient healthcare, increased outcomes, and potentially improved performance, higher quality of life and longer lifetimes are potential results. Decision support and the immediate linking of knowledge to the care process become easier. Semantic interoperability is a worthy goal. There are many barriers to achieving semantic interoperability. Key among these is the resolution of the many issues relating to the terminologies used in defining, describing and documenting health care. Each of these controlled terminologies has a reason for being and a following. The terminologies conflict and overlap; the granularity is not sufficiently rich for direct clinical use; there are gaps that prevent an exhaustive set; there are major variances in cost and accessibility; and no one appears eager or willing to make the ultimate decisions required to solve the problem. This chapter defines and describes the purpose and characteristics of the major terminologies in use in healthcare today. Terminology sets are compared in purpose, form and content. Finally, a proposed solution is presented based on a global master metadictionary of data elements with a rich set of attributes including names that may come from existing controlled terminologies, precise definitions to remove ambiguity in use, and complete value sets of possible values. The focus is on data elements because data elements are the basic unit of data interchange. © 2010, IGI Global. ER - TY - JOUR T1 - eHealth interoperability. A1 - Hammond, W E Y1 - 2008/// KW - Germany KW - Health Care Costs KW - History, 20th Century KW - Hospital Information Systems KW - Humans KW - Medical Informatics KW - Systematized Nomenclature of Medicine KW - Terminology as Topic KW - history KW - hospital information system KW - human KW - medical informatics KW - nomenclature KW - organization and management KW - review KW - systematized nomenclature of medicine JF - Studies in health technology and informatics VL - 134 SP - 245 EP - 253 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-43849090518&partnerID=40&md5=f0803a64128453f8583df126cf5b1657 N1 - Cited By :12 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - For improving quality and safety of patient's care, for keeping the costs of health services, but also for successfully managing public health communication and cooperation between all stakeholders is inevitable. Such interoperability can be provided at different levels from simple data exchange up to business interoperability. The paper introduces those interoperability levels and international standards specifying and facilitating them. In that context, the expression of business requirements by domain analysis models or story boards as well as by functional models of the core applications enabling interoperability like EHR systems have been tackled. The role of decision support systems and infrastructural services has been considered as well. ER - TY - JOUR T1 - Global Health Innovation Technology Models A1 - Harding, Kimberly Y1 - 2016/12// KW - Africa KW - Bioinformatics KW - Business Process KW - CRO KW - Clinical KW - Clinical Imaging KW - Clinical Trials KW - Commercialization KW - Drug Discovery KW - Epidemiology KW - FDA KW - Frameworks KW - GCP KW - Global Health KW - HIV KW - Hardware KW - Health Information Management KW - Health Information Technology KW - ICH KW - Imaging KW - Infectious Diseases KW - Informatics KW - Innovation KW - Interoperability KW - Low Income Countries KW - Low Middle Income Countries KW - Malaria KW - Medical Device KW - Nanomedicine KW - Nanotechnology KW - Open Science KW - Open Source: Big Data KW - Product Development KW - Public Health KW - Radiology KW - Rare Diseases KW - Regulatory KW - Semantics KW - Software KW - Standards KW - Syntax KW - TB KW - Tanzania KW - Tropical Diseases KW - WHO KW - ehealth KW - mHealth PB - SAGE PublicationsSage UK: London, England JF - Nanobiomedicine VL - 3 SP - 7 EP - 7 DO - 10.5772/62921 UR - http://journals.sagepub.com/doi/10.5772/62921 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Harding - 2016 - Global Health Innovation Technology Models.pdf N2 - Chronic technology and business process disparities between High Income, Low Middle Income and Low Income (HIC, LMIC, LIC) research collaborators directly prevent the growth of sustainable Global Health innovation for infectious and rare diseases. There is a need for an Open Source-Open Science Architecture Framework to bridge this divide. We are proposing such a framework for consideration by the Global Health community, by utilizing a hybrid approach of integrating agnostic Open Source technology and healthcare interoperability standards and Total Quality Management principles. We will validate this architecture framework through our programme called Project Orchid. Project Orchid is a conceptual Clinical Intelligence Exchange and Virtual Innovation platform utilizing this approach to support clinical innovation efforts for multi-national collaboration that can be locally sustainable for LIC and LMIC research cohorts. The goal is to enable LIC and LMIC research organizations to accelerate their clinical... ER - TY - JOUR T1 - A toxicology ontology roadmap A1 - Hardy, B A1 - Apic, G A1 - Carthew, P A1 - Clark, D A1 - Cook, D A1 - Dix, I A1 - Escher, S A1 - Hastings, J A1 - Heard, D J A1 - Jeliazkova, N A1 - Judson, P A1 - Matis-Mitchell, S A1 - Mitic, D A1 - Myatt, G A1 - Shah, I A1 - Spjuth, O A1 - Tcheremenskaia, O A1 - Toldo, L A1 - Watson, D A1 - White, A A1 - Yang, C Y1 - 2012/// KW - Animal Testing Alternatives KW - Animals KW - Computational Biology KW - Databases, Factual KW - Emigrants and Immigrants KW - Framework KW - Humanism KW - Humanities KW - Humans KW - Interoperability KW - Ontology KW - Research KW - Risk Assessment KW - Risk assessment KW - Roadmap KW - Toxicology KW - Vocabulary, Controlled KW - animal KW - animal testing alternative KW - animal testing reduction KW - article KW - biology KW - drug research KW - economics KW - factual database KW - health hazard KW - human KW - law KW - legal aspect KW - linguistics KW - methodology KW - nomenclature KW - nonhuman KW - research KW - review KW - risk assessment KW - toxic substance KW - toxicity testing KW - toxicology KW - validation study JF - Altex VL - 29 IS - 2 SP - 129 EP - 137 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84860815641&partnerID=40&md5=a537007a5a466e4592aea4de09b74704 N1 - Cited By :11 Export Date: 10 September 2018 References: Arvidson, K.B., FDA toxicity databases and real-time data entry (2008) Toxicol. Appl. Pharmacol., 233, pp. 17-19; Ashburner, M., Ball, C.A., Blake, J.A., Gene ontology: Tool for the unification of biology (2000) Nat. Genet., 25, pp. 25-29. , The Gene Ontology Consortium; Hardy, B., Douglas, N., Helma, C., Collaborative development of predictive toxicology applications (2010) J. Cheminform., 2, p. 7; Hardy, B., Apic, G., Carthew, P., Toxicology ontology perspectives (2012) ALTEX, 29, pp. 139-156; (2007) Toxicity Testing in the 21st Century: A Vision and a Strategy, , NRC - National Research Council Washington DC, USA: National Academies Press RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Foreign substances can have a dramatic and unpredictable adverse effect on human health. In the development of new therapeutic agents, it is essential that the potential adverse effects of all candidates be identified as early as possible. The field of predictive toxicology strives to profile the potential for adverse effects of novel chemical substances before they occur, both with traditional in vivo experimental approaches and increasingly through the development of in vitro and computational methods which can supplement and reduce the need for animal testing. To be maximally effective, the field needs access to the largest possible knowledge base of previous toxicology findings, and such results need to be made available in such a fashion so as to be interoperable, comparable, and compatible with standard toolkits. This necessitates the development of open, public, computable, and standardized toxicology vocabularies and ontologies so as to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. Such ontology development will support data management, model building, integrated analysis, validation and reporting, including regulatory reporting and alternative testing submission requirements as required by guidelines such as the REACH legislation, leading to new scientific advances in a mechanistically-based predictive toxicology. Numerous existing ontology and standards initiatives can contribute to the creation of a toxicology ontology supporting the needs of predictive toxicology and risk assessment. Additionally, new ontologies are needed to satisfy practical use cases and scenarios where gaps currently exist. Developing and integrating these resources will require a well-coordinated and sustained effort across numerous stakeholders engaged in a public-private partnership. In this communication, we set out a roadmap for the development of an integrated toxicology ontology, harnessing existing resources where applicable. We describe the stakeholders' requirements analysis from the academic and industry perspectives, timelines, and expected benefits of this initiative, with a view to engagement with the wider community. ER - TY - JOUR T1 - Toward a roadmap in global biobanking for health A1 - Harris, J R A1 - Burton, P A1 - Knoppers, B M A1 - Lindpaintner, K A1 - Bledsoe, M A1 - Brookes, A J A1 - Budin-Ljosne, I A1 - Chisholm, R A1 - Cox, D A1 - Deschênes, M A1 - Fortier, I A1 - Hainaut, P A1 - Hewitt, R A1 - Kaye, J A1 - Litton, J.-E. A1 - Metspalu, A A1 - Ollier, B A1 - Palmer, L J A1 - Palotie, A A1 - Pasterk, M A1 - Perola, M A1 - Riegman, P H J A1 - Van Ommen, G.-J. A1 - Yuille, M A1 - Zatloukal, K Y1 - 2012/// KW - Biological Specimen Banks KW - Data Collection KW - Databases, Factual KW - analytic method KW - article KW - funding KW - government KW - health care facility KW - health care personnel KW - health care policy KW - health care system KW - health science KW - human KW - information processing KW - investment KW - medical ethics KW - medicolegal aspect KW - patient care KW - patient safety KW - preservation and storage KW - priority journal KW - standardization JF - European Journal of Human Genetics VL - 20 IS - 11 SP - 1105 EP - 1111 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867741263&doi=10.1038%2Fejhg.2012.96&partnerID=40&md5=dee954cd1de81c43dc9e39b4377f57b4 N1 - Cited By :76 Export Date: 10 September 2018 References: (2001) Biological Resource Centres: Underpinning the Future of Life Sciences and Biotechnology, , Organisation for Economic Co-operation and Development (OECD) Paris: OECD; Knoppers, B.M., Kent, A., Policy barriers in coherent population-based research (2006) Nat Rev Genet, 7, p. 8; (2011) Sharing Research Data to Improve Public Health: Full Joint Statement by Funders of Health Research, , The Wellcome Trust UK: Wellcome Trust; Fortier, I., Doiron, D., Burton, P., Raina, P., Invited commentary: Consolidating data harmonization\how to obtain quality and applicability? (2011) Am J Epidemiol, 174, pp. 261-264; Fortier, I., Doiron, D., Little, J., Is rigorous retrospective harmonization possible? Application of the DataSHaPER approach across 53 large studies (2011) Int J Epidemiol, 40, pp. 1314-1328; Knoppers, B.M., Fortier, I., Legault, D., Burton, P., The Public Population Project in Genomics (P3G): A proof of concept? (2008) Eur J Hum Genet, 16, pp. 664-665; (2009) OECD Guidelines on Human Biobanks and Genetic Research Databases, , Organisation for Economic Co-operation and Development (OECD) Organisation for Economic Co-operation and Development (OECD): Paris; Collection, Storage, Retrieval, and distribution of biological materials for research (2012) Biopreserv Biobank, 10, pp. 79-161. , International Society for Biological and Environmental Repositories (ISBER): 2012 Best Practices for Repositories; (2011) Best Practices for Biospeci-men Resources, , http://biospecimens.cancer.gov/bestpractices/2011-NCIBestPractices.pdf, National Cancer Institute and National Cancer Institute (NCI); Guerin, J.S., Murray, D.W., McGrath, M.M., Ma, Y., McPartlin, J.M., Doran, P.P., Molecular medicine ireland guidelines for standardized biobanking (2010) Biopreservation and Biobanking, 8, pp. 3-63; Yuille, M., Illig, T., Hveem, K., Laboratory management of samples in biobanks: European consensus expert group report (2010) Biopreservation and Biobanking, 8, pp. 65-69; Bevilacqua, G., Bosman, F., Dassesse, T., The role of the pathologist in tissue banking: European consensus expert group report (2010) Virchows Arch, 456, pp. 449-454; Burton, P.R., Hansell, A.L., Fortier, I., Size matters: Just how big is BIG?: Quantifying realistic sample size requirements for human genome epidemiology (2009) Int J Epidemiol, 38, pp. 263-273; Hindorff, L.A., Sethupathy, P., Junkins, H.A., Potential etiologic and functional implications of genome-wide association loci for human diseases and traits (2009) Proc Natl Acad Sci USA, 106, pp. 9362-9367; Spencer, C.C., Su, Z., Donnelly, P., Marchini, J., Designing genome-wide association studies: Sample size, power, imputation, and the choice of genotyping chip (2009) PLoS Genet, 5, pp. e1000477; Barabasi, A.L., Gulbahce, N., Loscalzo, J., Network medicine: A network-based approach to human disease (2011) Nat Rev Genet, 12, pp. 56-68; http://www.bbmri.eu/index.php/publications-a-reports, Annex 16: Final Report from WP5. (accessed 17 May 2011); Schofield, P.N., Eppig, J., Huala, E., Research funding. Sustaining the data and bioresource commons (2010) Science, 330, pp. 592-593; Knoppers, B.M., Chadwick, R., Human genetic research: Emerging trends in ethics (2005) Nat Rev Genet, 6, pp. 75-79; Chadwick, R., Berg, K., Solidarity and equity: New ethical frameworks for genetic databases (2001) Nat Rev Genet, 2, pp. 318-321; Prainsack, B., Buy, A., (2011) Solidarity: Reflections on An Emerging Concept in Biobanks, , Swindon, UK: ESP Colour Ltd; Statement on human genomic databases December 2002 (2003) J Int Bioethique, 14, pp. 207-210. , Human Genome Organisation (HUGO) Ethics Committee; Yuille, M., Dixon, K., Platt, A., The UK DNA Banking Network: A 'fair access' biobank (2010) Cell Tissue Bank, 11, pp. 241-251; Knoppers, B.M., Harris, J.R., Tasse, A.M., Towards a data sharing Code of Conduct for international genomic research (2011) Genome Med, 3, p. 46; Kaye, J., Heeney, C., Hawkins, N., De Vj Boddington, P., Data sharing in genomics\re-shaping scientific practice (2009) Nat Rev Genet, 10, pp. 331-335; Wolfson, M., Wallace, S.E., Masca, N., DataSHIELD: Resolving a conflict in contemporary bioscience\performing a pooled analysis of individual-level data without sharing the data (2010) Int J Epidemiol, 39, pp. 1372-1382; Knoppers, B.M., Harris, J.R., Burton, P.R., From genomic databases to translation: A call to action (2011) J Med Ethics, 37, pp. 515-516; Wagstaff, A., International Biobanking Regulations: The Promise and the Pitfalls, 2011 Cancer World (Online), , http://www.cancerworld.org/pdf/3827_agina_22-29_cuttingedge.pdf; http://about.orcid.org/, Open Researcher and Contributor ID (ORCID 2011); Birney, E., Hudson, T.J., Green, E.D., Prepublication data sharing (2009) Nature, 461, pp. 168-170; Ioannidis, J.P., Adami, H.O., Nested randomized trials in large cohorts and biobanks: Studying the health effects of lifestyle factors (2008) Epidemiology, 19, pp. 75-82; (2011) Coriell Cell Repositories, , Coriell Institute for Medical Research: Coriell Institute for Medical Research; Poste, G., Bring on the biomarkers (2011) Nature, 469, pp. 156-157; Riegman, P.H., Morente, M.M., Betsou, F., De Bp Geary, P., Biobanking for better healthcare (2008) Mol Oncol, 2, pp. 213-222; http://biochem118.stanford.edu/Papers/Genome%20Papers/ Estonian%20Genome%20Res%20Act.pdf, Estonian Human Genes Research Act 2000; Lindpaintner, K., Biomarkers: Call on industry to share (2011) Nature, 470, p. 175; Murtagh, M.J., Demir, I., Harris, J.R., Burton, P.R., Realizing the promise of population biobanks: A new model for translation (2011) Hum Genet, 130, pp. 333-345; Yuille, M., Van Ommen, G.J., Brechot, C., Biobanking for Europe (2008) Brief Bioinform, 9, pp. 14-24; http://www.bbmri.eu/index.php?option=com_content&view=article&id= 99&Itemid=78, Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) Final Report 2011;; Cambon-Thomsen, A., Assessing the impact of biobanks (2003) Nat Genet, 34, pp. 25-26; Cambon-Thomsen, A., Thorisson, G.A., Mabile, L., The role of a bioresource research impact factor as an incentive to share human bioresources (2011) Nat Genet, 43, pp. 503-504; Vaught, J.B., Caboux, E., Hainaut, P., International efforts to develop biospecimen best practices (2010) Cancer Epidemiol Biomarkers Prev, 19, pp. 912-915; Fortier, I., Burton, P.R., Robson, P.J., Quality, quantity and harmony: The DataSHaPER approach to integrating data across bioclinical studies (2010) Int J Epidemiol, 39, pp. 1383-1393; Lim, M.D., Dickherber, A., Compton, C.C., Before you analyze a human specimen, think quality, variability, and bias (2011) Anal Chem, 83, pp. 8-13 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Biobanks can have a pivotal role in elucidating disease etiology, translation, and advancing public health. However, meeting these challenges hinges on a critical shift in the way science is conducted and requires biobank harmonization. There is growing recognition that a common strategy is imperative to develop biobanking globally and effectively. To help guide this strategy, we articulate key principles, goals, and priorities underpinning a roadmap for global biobanking to accelerate health science, patient care, and public health. The need to manage and share very large amounts of data has driven innovations on many fronts. Although technological solutions are allowing biobanks to reach new levels of integration, increasingly powerful data-collection tools, analytical techniques, and the results they generate raise new ethical and legal issues and challenges, necessitating a reconsideration of previous policies, practices, and ethical norms. These manifold advances and the investments that support them are also fueling opportunities for biobanks to ultimately become integral parts of health-care systems in many countries. International harmonization to increase interoperability and sustainability are two strategic priorities for biobanking. Tackling these issues requires an environment favorably inclined toward scientific funding and equipped to address socio-ethical challenges. Cooperation and collaboration must extend beyond systems to enable the exchange of data and samples to strategic alliances between many organizations, including governmental bodies, funding agencies, public and private science enterprises, and other stakeholders, including patients. A common vision is required and we articulate the essential basis of such a vision herein. © 2012 Macmillan Publishers Limited. All rights reserved. ER - TY - JOUR T1 - A population health measurement framework: Evidence-based metrics for assessing community-level population health in the global budget context A1 - Hatef, E A1 - Lasser, E C A1 - Kharrazi, H H K A1 - Perman, C A1 - Montgomery, R A1 - Weiner, J P Y1 - 2018/// JF - Population Health Management VL - 21 IS - 4 SP - 261 EP - 270 DO - 10.1089/pop.2017.0112 N2 - ©2018 Mary Ann Liebert, Inc. Population health is one of the pillars of the Triple Aim to improve US health care. The authors developed a framework for population health measurement and a proposed set of measures for further exploration to guide the population health efforts in Maryland. The authors searched peer-reviewed, expert-authored literature and current public health measures. Using a semi-structured analysis, a framework was proposed, which consisted of a conceptual model of several domains and identified population health measures addressing them. Stakeholders were convened to review the framework and identified the most feasible population health measures considering the underlying health information technology (IT) infrastructure in Maryland. The framework was organized based on health system factors, determinants of health, and population-based and clinical outcomes. Measurement specifications were developed that addressed different aspects of selected measures and assessed various national and local data sources for selected measures. Data sources were identified based on their key characteristics, challenges, opportunities, and potential applicability to the proposed measures, as well as the issue of interoperability of data sources among different organizations. The proposed framework and measures can act as a platform to quantify the determinants of health and the state overall population health goals. Key considerations for developing a population health measures framework include health IT infrastructure, data denominators, feasibility, health system environment, and policy factors. Measurement development and progression using the framework will largely depend on the users' focus areas and availability of data. The authors believe that the proposed framework and road map can serve as a model for communities elsewhere. ER - TY - JOUR T1 - Minimum Data Elements for Radiation Oncology: An American Society for Radiation Oncology Consensus Paper A1 - Hayman, J A A1 - Dekker, A A1 - Feng, M A1 - Keole, S R A1 - McNutt, T R A1 - Machtay, M A1 - Martin, N E A1 - Mayo, C S A1 - Pawlicki, T A1 - Smith, B D A1 - Dawes, S A1 - Yu, J B Y1 - 2019/// JF - Practical Radiation Oncology VL - 9 IS - 6 SP - 395 EP - 401 DO - 10.1016/j.prro.2019.07.017 N2 - ©2019 Purpose: In recent years, the American Society for Radiation Oncology (ASTRO) has received requests for a standard list of data elements from other societies, database architects, Electronic Health Record vendors and, most recently, the pharmaceutical industry. These requests point to a growing interest in capturing radiation oncology data within registries and for quality measurement, interoperability initiatives, and research. Identifying a short and consistent list will lead to improved care coordination, a reduction in data entry by practice staff, and a more complete view of the holistic approach required for cancer treatment. Methods and Materials: The task force formulated recommendations based on analysis from radiation specific data elements currently in use in registries, accreditation programs, incident learning systems, and electronic health records. The draft manuscript was peer reviewed by 8 reviewers and ASTRO legal counsel and was revised accordingly and posted on the ASTRO website for public comment in April 2019 for 2 weeks. The final document was approved by the ASTRO Board of Directors in June 2019. ER - TY - JOUR T1 - Using the PhenX toolkit to add standard measures to a study A1 - Hendershot, T A1 - Pan, H A1 - Haines, J A1 - Harlan, W R A1 - Marazita, M L A1 - McCarty, C A A1 - Ramos, E M A1 - Hamilton, C M Y1 - 2015/// KW - Anemia, Sickle Cell KW - Article KW - Environmental Exposure KW - Environmental exposures KW - Epidemiology KW - Genome-wide association studies (GWAS) KW - Humans KW - Internet KW - PhenX KW - Phenotype KW - Research KW - Software KW - User-Computer Interface KW - Web Browser KW - access to information KW - clinical protocol KW - computer interface KW - environmental exposure KW - genetic analysis KW - genetic association KW - genetic database KW - genotype environment interaction KW - human KW - information processing KW - online system KW - phenotype KW - phenotypes KW - priority journal KW - software KW - standard measures KW - translational research KW - web browser JF - Current Protocols in Human Genetics VL - 2015 SP - 1.21.1 EP - 1.21.17 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949229950&doi=10.1002%2F0471142905.hg0121s86&partnerID=40&md5=d542eb27f45804b5f484ebd0a8369501 N1 - Cited By :4 Export Date: 10 September 2018 References: Bennett, S.N., Caporaso, N., Fitzpatrick, A.L., Agrawal, A., Barnes, K., Boyd, H.A., Cornelis, M.C., Williams, K., Phenotype harmonization and cross-study collaboration in GWAS consortia: The GENEVA experience (2011) Genet. Epidemiol, 35, pp. 159-173; Conway, K.P., Vullo, G.C., Kennedy, A.P., Finger, M.S., Arpana, A., Bjork, J.M., Farrer, L.A., Sher, K.J., Data compatibility in the addiction sciences: An examination of measure commonality (2014) Drug Alcohol Depend, 141, pp. 153-158; Maiese, D.R., Hendershot, T.P., Strader, L.C., Wagener, D.K., Hammond, J.A., Huggins, W., Kwok, R.K., Hamilton, C.M., PhenX-Establishing a Consensus Process to Select Common Measures for Collaborative Research (2013), RTI Press publication no. MR-0027-1310. RTI Press, Research Triangle Park, N.C; Mailman, M.D., Feolo, M., Jin, Y., Kimura, M., Tryka, K., Bagoutdinov, R., Hao, L., Sherry, S.T., The NCBI dbGaP database of genotypes and phenotypes (2007) Nat. Genet, 39, pp. 1181-1186; McCarty, C.A., Huggins, W., Aiello, A.E., Bilder, R.M., Hariri, A., Jernigan, T.L., Newman, E., Junkins, H.A., PhenX RISING: Real world implementation and sharing of PhenX measures (2014) BMC Med. Genom, 7, p. 16; Stover, P.J., Harlan, W.R., Hammond, J.A., Hendershot, T., Hamilton, C.M., PhenX: A toolkit for interdisciplinary genetics research (2010) Curr. Opin. Lipidol, 21, pp. 136-140 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The PhenX (consensus measures for Phenotypes and eXposures) Toolkit (https://www.phenxtoolkit.org/) offers high-quality, well-established measures of phenotypes and exposures for use by the scientific community. The goal is to promote the use of standard measures, enhance data interoperability, and help investigators identify opportunities for collaborative and translational research. The Toolkit contains 395 measures drawn from 22 research domains (fields of research), along with additional collections of measures for Substance Abuse and Addiction (SAA) research, Mental Health Research (MHR), and Tobacco Regulatory Research (TRR). Additional measures for TRR that are expected to be released in 2015 include Obesity, Eating Disorders, and Sickle Cell Disease. Measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The Toolkit provides a description of each PhenX measure, the rationale for including it in the Toolkit, protocol(s) for collecting the measure, and supporting documentation. Users can browse measures in the Toolkit or can search the Toolkit using the Smart Query Tool or a full text search. PhenX Toolkit users select measures of interest to add to their Toolkit. Registered Toolkit users can save their Toolkit and return to it later to revise or complete. They then have options to download a customized Data Collection Worksheet that specifies the data to be collected, and a Data Dictionary that describes each variable included in the Data Collection Worksheet. The Toolkit also has a Register Your Study feature that facilitates cross-study collaboration by allowing users to find other investigators using the same PhenX measures. © 2015 by John Wiley & Sons, Inc. ER - TY - JOUR T1 - Challenges of scientific data management for large epidemiologic studies A1 - Henderson, M K A1 - Mohla, C A1 - Jacobs, K B A1 - Vaught, J B Y1 - 2005/// KW - Epidemiologic Studies KW - Internet KW - automation KW - bioinformatics KW - cancer center KW - cancer epidemiology KW - cancer genetics KW - comparative study KW - computer program KW - epidemiological data KW - health care organization KW - human KW - information processing KW - information science KW - laboratory KW - management KW - medical informatics KW - medical research KW - planning KW - priority journal KW - review KW - technology JF - Cell Preservation Technology VL - 3 IS - 1 SP - 49 EP - 53 N1 - Export Date: 10 September 2018 References: Choudhary, A., Taylor, V., (1998) High-Performance Data Management, Access, and Storage for Tera-Scale Scientific Applications: Project, , sponsored by the Department of Energy's (DOE) Accelerated Strategic Computing Initiative (ASCI); http://www.plone.org/, Plone; http://cabig.nci.nih.gov/, NCI's cancer Biomedical Informatics Grid, caBIGUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-17044440624&doi=10.1089%2fcpt.2005.3.49&partnerID=40&md5=4dbb29811fd47e29329678d410e04d4d RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The U.S. National Cancer Institute's Division of Cancer Epidemiology and Genetics (DCEG) conducts population-based and interdisciplinary research to discover the genetic and environmental determinants of cancer. Many DCEG studies are large, multi-institutional, and long-term with national and international study sites involved in the multiple research steps. Current information technology challenges involved in such epidemiological studies include: (1) management and harmonization of a multitude of data types (demographic, environmental, biospecimen, laboratory, analytic, molecular, etc.); (2) unprecedented amounts of data; (3) efficient data mining to derive insights into disease etiology; and (4) secure collaboration between study management systems. If not adequately addressed, all of these challenges will increase the cost of performing studies and decrease the speed of publication. DCEG is examining current data management practices to better utilize recent advances in information technology to enhance its scientific program. This analysis is providing strategic guidance in enhancing interoperability among current data systems, further automating specimen management practices, defining metadata strategies to allow for better cross study comparability and reusability, and in planning for integration of new technologies in support of DCEG's epidemiology research. Early results from the effort include better communication of information technology requirements between contractors and investigators, as well as progress on several focused data interoperability projects, including Web services transactions for biorepository interoperability and improved analytic support utilizing data warehouses. © Mary Ann Liebert, Inc. ER - TY - JOUR T1 - OBML - Ontologies in Biomedicine and Life Sciences A1 - Herre, H A1 - Hoehndorf, R A1 - Kelso, J A1 - Loebe, F A1 - Schulz, S Y1 - 2011/// KW - Biological Science Disciplines KW - Medical Informatics JF - Journal of Biomedical Semantics VL - 2 IS - 4 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875975630&doi=10.1186%2F2041-1480-2-S4-I1&partnerID=40&md5=8cc276589c0744ae1630505f85654377 N1 - Cited By :2 Export Date: 10 September 2018 References: Röhl, J., Jansen, L., Representing Dispositions (2010), pp. F1-F5. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, OBML 2010 Workshop Proceedings. Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Jansen, L., Schulz, S., Components and Mixtures in Biomedical Ontologies (2010), pp. G1-G4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, OBML 2010 Workshop Proceedings. Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Armstrong, D.M., A World of States of Affairs (Cambridge Studies in Philosophy) (1997), Cambridge University Press; Choi, S., The Simple Vs. Reformed Conditional Analysis of Dispositions (2006) Synthese, 148 (2), pp. 369-379. , http://dx.doi.org/10.1007/s11229-004-6229-z; Lewis, D., Finkish Dispositions (1997) The Philosophical Quarterly, 47 (187), pp. 143-158. , http://dx.doi.org/10.1111/1467-9213.00052; Johansson, I., Functions, function concepts, and scales (2004) The Monist, 87, pp. 96-114; Hoehndorf, R., Kelso, J., Herre, H., Contributions to the formal ontology of functions and dispositions: An application of non-monotonic reasoning (2009) Proceedings of Bio-Ontologies 2009: Knowledge in Biology.; Arp, R., Smith, B., Function, Role, and Disposition in Basic Formal Ontology (2008) Proceedings of The 11th Annual Bio-Ontologies Meeting; Batchelor, C., Hastings, J., Steinbeck, C., Ontological dependence, dispositions and institutional reality in chemistry (2010) Formal Ontology in Information Systems - Proceedings of the Sixth International Conference (FOIS 2010)., pp. 271-284. , Edited by: Galton A, Mizoguchi R; Hoehndorf, R., Oellrich, A., Dumontier, M., Kelso, J., Rebholz-Schuhmann, D., Herre, H., Relations as patterns: Bridging the gap between OBO and OWL (2010) BMC Bioinformatics, 11, pp. 441 and; Goldfain, A., Smith, B., Cowell, L., Dispositions and the Infectious Disease Ontology (2010) Proceedings of Formal Ontologies in Information Systems (FOIS), pp. 400-413; Schulz, S., Stenzhorn, H., Boeker, M., Smith, B., Strengths and limitations of formal ontologies in the biomedical domain (2009) RECIIS Rev Electron Comun Inf Inov Saude, 3 (1), pp. 31-45; Grau, B., Horrocks, I., Motik, B., Parsia, B., Patelschneider, P., Sattler, U., OWL 2: The next step for OWL (2008) Web Semantics: Science, Services and Agents on the World Wide Web, 6 (4), pp. 309-322. , http://dx.doi.org/10.1016/j.websem.2008.05.001; Horrocks, I., Kutz, O., Sattler, U., The Even More Irresistible SROIQ (2006), pp. 57-67. , http://dblp.uni-trier.de/db/conf/kr/kr2006.html#HorrocksKS06, KR. Edited by: Doherty P, Mylopoulos J, Welty CA. AAAI Press; Schulz, S., Beisswanger, E., Wermter, J., Hahn, U., Towards an upper level ontology for molecular biology (2006) AMIA Annu Symp Proc., pp. 694-698. , http://view.ncbi.nlm.nih.gov/pubmed/17238430; Rosse, C., Mejino, J.L.V., A Reference Ontology for Biomedical Informatics: the Foundational Model of Anatomy (2003) Journal of Biomedical Informatics, 36 (6), pp. 478-500. , http://dx.doi.org/10.1016/j.jbi.2003.11.007; Mungall, C., Gkoutos, G., Smith, C., Haendel, M., Lewis, S., Ashburner, M., Integrating phenotype ontologies across multiple species (2010) Genome Biology, 11, pp. R2 and. , http://dx.doi.org/10.1186/gb-2010-11-1-r2; Herre, H., General Formal Ontology (GFO): A Foundational Ontology for Conceptual Modelling (2010) Theory and Applications of Ontology: Computer Applications., pp. 297-345. , http://dx.doi.org/10.1007/978-90-481-8847-5_14, Edited by: Poli R, Healy M, Kameas A. Heidelberg: Springer; Krötzsch, M., Vrandečić, D., Völkel, M., Haller, H., Studer, R., Semantic Wikipedia (2007) Web Semantics: Science, Services and Agents on the World Wide Web, 5 (4), pp. 251-261; Hucka, M., Finney, A., Sauro, H.M., Bolouri, H., Doyle, J.C., Kitano, H., Arkin, A.P., Hunter, P.J., The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models (2003) Bioinformatics, 19 (4), pp. 524-531. , http://bioinformatics.oxfordjournals.org/content/19/4/524.abstract; Mathäss, T., Haase, P., Kitano, H., Toldo, L., SBML2SMW: Bridging System Biology with Semantic Web Technologies for Biomedical Knowledge Acquisition and Hypothesis Elicitation (2010) OBML 2010 Workshop Proceedings., pp. A1-A4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Cocos, C., MacCaull, W., An Ontological Implementation of a Role-Based Access Control Policy for Health Care Information (2010) OBML 2010 Workshop Proceedings., pp. B1-B5. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Grenon, P., BFO in a Nutshell: A Bi-categorial Axiomatization of BFO and Comparison with DOLCE (2003) Institute for Formal Ontology and Medical Information Science (IFOMIS), , http://www.ifomis.uni-saarland.de/Research/IFOMISReports/IFOMIS%20Report%2006_2003.pdf, IFOMIS Report 06/2003. University of Leipzig, Leipzig, Germany; Zaveri, A., Pietrobon, R., Ermilov, T., Martin, M., Heino, N., Auer, S., Evaluating the Disparity between Active Areas of Biomedical Research and the Global Burden of Disease Employing Linked Data and Data-driven Discovery (2010) OBML 2010 Workshop Proceedings., pp. C1-C7. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Grewe, N., A Generic Reification Strategy for n-ary Relations in DL (2010) OBML 2010 Workshop Proceedings., pp. N1-N5. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Niggemann, J., Straub, H.R., Herre, H., Can a Hole Be Inflamed? On the Relation of Morphologic Abnormalities and Anatomical Cavities in SNOMED CT (2010) OBML 2010 Workshop Proceedings., pp. E1-E4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Adams, N., Hennig, C., Hoehndorf, R., Oellrich, A., Rebholz-Schuhmann, D., Hansen, G., The Ontology of Primary Immunodeficiency Diseases (PIDs) - Using PIDs to Rethink the Ontology of Phenotypes (2010) OBML 2010 Workshop Proceedings., pp. I1-I4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Burek, P., Herre, H., Röder, I., Glauche, I., Scherf, N., Löffler, M., Towards a Cellular Genealogical Tree Ontology (2010) OBML 2010 Workshop Proceedings., pp. K1-K5. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Oellrich, A., Rebholz-Schuhmann, D., A Classification of Existing Phenotypical Representations and Methods for Improvement (2010) OBML 2010 Workshop Proceedings., pp. J1-J4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Schober, D., Boeker, M., Ontology Simplification: New Buzzword or Real Need? (2010) OBML 2010 Workshop Proceedings., pp. M1-M5. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler; Schulz, S., Schober, D., Raufie, D., Boeker, M., Pre- and Postcoordination in Biomedical Ontologies (2010) OBML 2010 Workshop Proceedings., pp. L1-L4. , http://www.onto-med.de/obml/ws2010/obml2010report.pdf, Edited by: Herre H, Hoehndorf R, Kelso J, Schulz S, Institut fuer Medizinische Informatik, Statistik und Epidemiologie (IMISE), Markus Loeffler RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The OBML 2010 workshop, held at the University of Mannheim on September 9-10, 2010, is the 2nd in a series of meetings organized by the Working Group "Ontologies in Biomedicine and Life Sciences" of the German Society of Computer Science (GI) and the German Society of Medical Informatics, Biometry and Epidemiology (GMDS). Integrating, processing and applying the rapidly expanding information generated in the life sciences - from public health to clinical care and molecular biology - is one of the most challenging problems that research in these fields is facing today. As the amounts of experimental data, clinical information and scientific knowledge increase, there is a growing need to promote interoperability of these resources, support formal analyses, and to pre-process knowledge for further use in problem solving and hypothesis formulation. The OBML workshop series pursues the aim of gathering scientists who research topics related to life science ontologies, to exchange ideas, discuss new results and establish relationships. The OBML group promotes the collaboration between ontologists, computer scientists, bio-informaticians and applied logicians, as well as the cooperation with physicians, biologists, biochemists and biometricians, and supports the establishment of this new discipline in research and teaching. Research topics of OBML 2010 included medical informatics, Semantic Web applications, formal ontology, bio-ontologies, knowledge representation as well as the wide range of applications of biomedical ontologies to science and medicine. A total of 14 papers were presented, and from these we selected four manuscripts for inclusion in this special issue. An interdisciplinary audience from all areas related to biomedical ontologies attended OBML 2010. In the future, OBML will continue as an annual meeting that aims to bridge the gap between theory and application of ontologies in the life sciences. The next event emphasizes the special topic of the ontology of phenotypes, in Berlin, Germany on October 6-7, 2011. © 2011 Herre et al; licensee BioMed Central Ltd. ER - TY - JOUR T1 - Designing interoperable health information systems using Enterprise Architecture approach in resource-limited countries: A literature review A1 - Higman, S A1 - Dwivedi, V A1 - Nsaghurwe, A A1 - Busiga, M A1 - Sotter Rulagirwa, H A1 - Smith, D A1 - Wright, C A1 - Nyinondi, S A1 - Nyella, E Y1 - 2019/// JF - International Journal of Health Planning and Management VL - 34 IS - 1 SP - e85 EP - -e99 DO - 10.1002/hpm.2634 N2 - ©2018 John Wiley & Sons, Ltd. Background: Enterprise Architecture (EA) integrates business and technical processes in health information systems (HIS). Low-income and middle-income countries (LMIC) use EA to combine management components with disease tracking and health care service monitoring. Using an EA approach differs by country, addressing specific needs. Methods: Articles in this review referenced EA, were peer-reviewed or gray literature reports published in 2010 to 2016 in English, and were identified using PubMed, Scopus, Web of Science, and Google Scholar. Results: Fourteen articles described EA use in LMICs. India, Sierra Leone, South Africa, Mozambique, and Rwanda reported building the system to meet country needs and implement a cohesive HIS framework. Jordan and Taiwan focused on specific HIS aspects, ie, disease surveillance and electronic medical records. Five studies informed the context. The Millennium Villages Project employed a “uniform but contextualized” approach to guide systems in 10 countries; Malaysia, Indonesia, and Tanzania used interviews and mapping of existing components to improve HIS, and Namibia used of Activity Theory to identify technology-associated activities to better understand EA frameworks. South Africa, Burundi, Kenya, and Democratic Republic of Congo used EA to move from paper-based to electronic systems. Conclusions: Four themes emerged: the importance of multiple sectors and data sources, the need for interoperability, the ability to incorporate system flexibility, and the desirability of open group models, data standards, and software. Themes mapped to EA frameworks and operational components and to health system building blocks and goals. Most articles focused on processes rather than outcomes, as countries are engaged in implementation. ER - TY - BOOK T1 - A Method for Converting Current Data to RDF in the Era of Industry 4.0 A1 - Hildebrand, M A1 - Tourkogiorgis, I A1 - Psarommatis, F A1 - Arena, D A1 - Kiritsis, D Y1 - 2019/// JF - IFIP Advances in Information and Communication Technology VL - 566 SP - 307 EP - 314 SN - 9783030299996 DO - 10.1007/978-3-030-30000-5_39 N2 - ©IFIP International Federation for Information Processing 2019. In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, the data produced on assembly lines within factories is becoming particularly interesting to leverage precious information. However, adding semantics to data that already exists remains a challenging process. Most manufacturing assembly lines predate the outbreak of graph data, or have adopted other data format standards, and the data they produce is therefore difficult to automatically map to RDF. This has been a topic of research an ongoing technical issue for almost a decade, and if certain mapping approaches and mapping languages have been developed, they are difficult to use for an automatic, large-scale data conversion and are not standardized. In this research, a technical approach for converting existing data to semantics has been developed. This paper presents an overview of this approach, as well as two concrete tools that we have built based on it. The results of these tools are discussed as well as recommendations for future research. ER - TY - CONF T1 - Enterprise architecture implementation and management: A case study on interoperability A1 - Hjort-Madsen, K Y1 - 2006/// KW - Economic and social effects KW - Enterprise architecture KW - Government KW - Health care KW - Health sector KW - Hospitals KW - Information retrieval systems KW - Interoperability KW - Project management KW - Public agencies KW - Societies and institutions VL - 4 SP - - EP - - UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-33749604299&doi=10.1109%2FHICSS.2006.154&partnerID=40&md5=1c73b4a9e493685913f5737c1d472d81 N1 - Cited By :46 Export Date: 10 September 2018 References: Attride-Stirling, J., Thematic networks: An analytic tool for qualitative research (2001) Qualitative Research, 1 (3), pp. 385-405; Bernard, S.A., (2004) An Introduction to Enterprise Architecture, , Author House, Indiana; Boar, B.H., (1999) Constructing Blueprints for Enterprise IT Architectures, , John Wiley & Sons; Ferlie, E., Pettigrew, A., Ashburner, L., Fitzgerald, L., (1996) The New Public Management in Action, , Oxford University Press; Fountain, J., (2002) Building the Virtual State: Information Technology and Institutional Change, , Brookings Institution Press; Hall, P.A., Taylor, R.C.R., Political science and the three new institutions (1996) Political Studies, 44 (5). , PSA & Blackwell Public; Hjort-Madsen, K., Gøtze, J., Enterprise architecture in government - Towards a multi-level framework for managing IT in government (2004) Proceedings of ECEG04, pp. 365-374. , Dublin, Irland; Iyer, B., Gottlieb, R.M., The four-domain architecture: An approach to support enterprise architecture design (2004) IBM Systems Journal, 43 (3), pp. 587-597; Janssen, M., Cresswell, A., The development of a reference architecture for local government (2005) Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences; Janssen, M., Wagenaar, R., Beerens, J., Towards a flexible ICT-architecture for multi-channel e-govemment service provisioning (2003) Proceedings of the 36th Hawaii International Conference on System Sciences; Klischewski, R., Top down or bottom up (2003) Proceedings of 1st International Workshop on E-government at ICAIL, pp. 17-26. , Traunmüller, R., Palmirani, M; Lankhorst, M., (2005) Enterprise Architecture at Work, , Springer Verlag; Layne, K., Lee, J., Developing fully functional e-government: A four stage model (2001) Government Information Quarterly, 18, pp. 122-136; Leben, A., Bohanec, M., Evaluation of life-event portals: Multi-attribute model and case study (2003) Lecture Notes in Computer Science, 2645, pp. 25-36; March, J.G., Olsen, J.P., (1989) Rediscovering Institutions: The Organizational Basis of Politics, , The Free Press, New York; McNurlin, B.C., Sprague, R.H., (2002) Information Systems Management, 5th Edition, , Prentice Hall, Pearson Education; Meyer, J.W., Rowan, B., Institutionalized organizations: Formal structure as myth and ceremony (1977) American Journal of Sociology, 83, pp. 340-363; Orlikowski, W., Baroudi, J., Studying information technology in organizations: Research approaches and assumptions (1991) Information Systems Research, 2 (1), pp. 1-28; Ostrom, E., An agenda for the study of institutions (1986) Public Choice, , Martin Nijhoff Publishers; Papazoglou, M.P., Georgakopoulos, D., Service oriented computing: Introduction (2003) Communications of the ACM, 46 (10), pp. 25-28; Park, J., Ram, S., Information systems interoperability: What lies beneath? (2004) ACM Transactions on Information Systems, 22 (4), pp. 595-632; Peristera, V., Tarabanis, K., Towards an enterprise architecture for public administration using a top-down approach (2000) European Journal of Information Systems, 9, pp. 252-260; Pulkkinen, M., Hirvonen, A., EA planning, development and management process for agile enterprise development (2005) Proceedings of the 38th Annual Hawaii International Conference on System Sciences; Ross, J., Creating a strategic IT architecture competency: Learning in stages (2003) MISQ Executive, 2 (1); Schekkerman, J., (2004) How to Survive in the Jungle of Enterprise Architecture Frameworks, , Trafford Publishing, Victoria; Schultz, U., Boland Jr., R.J., Knowledge management technology and the reproduction of knowledge work practice (2000) Journal of Strategic Information Systems, 9, pp. 193-212; Stamoulis, D., Gouscos, D., Georgiadis, P., Martakos, D., Revisiting public information management for effective e-government services (2001) Information Management & Computer Security, 9 (4), pp. 146-153; Traunmüller, R., Wimmer, M., E-government at a decisive moment: Sketching a roadmap to excellence (2003) Proceedings of the 2nd International Conference, pp. 1-14. , R. Traunmüller (Ed.). EGOV, Springer Verlag; Walsham, G., Interpretive case studies in IS research: Nature and method (1995) European Journal of Information Systems, 4, pp. 74-81; Ward, J., Peppard, J., (2002) Strategic Planning for Information Systems. (3rd Ed.), , Wiley, Chichester; Weill, P., Ross, J.W., (2004) IT Governance - How Top Performers Manage IT Decision Rights for Superior Results, , Harvard Business School Press, Boston, Massachusetts; Wilson, J.Q., (1989) Bureaucracy - What Government Agencies Do and Why They Do It, , Basic Books, New York; Yin, R., (1994) Case Study Research - Design and Methods, , Sage Publications, Thousand Oaks; Yourdon, E., Constantine, L., (1986) Structured Design: Fundamentals of a Discipline of Computer Program and Systems Design, , Yourdon Press, Englewood Cliffs, New Jersey; Zachman, J.A., A framework for information systems architecture (1987) IBM Systems Journal, 26 (3) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The focus of this study is to explore why public agencies implement enterprise architecture programs and the interoperability challenges they are faced with when governing these programs at different levels (vertical) and different functions (horizontal) of government. With a theoretical lens based on institutional theory from the political science field, the analysis shows that interoperability is not just a technical issue and that economic and political factors are just as important when implementing enterprise architecture programs in government. The findings suggest that implementing enterprise architectures in government challenge the way information systems are organized and governed in public agencies and calls for a broader definition of interoperability. The case study indicates that interoperability challenges arise because there is no overall coordination of different information systems initiatives in the health sector and because public hospitals have no economic and/or immediate political incentives to share data and business functionality with other organizations. © 2006 IEEE. ER - TY - CONF T1 - Intelligent mortality reporting with FHIR A1 - Hoffman, R A A1 - Wu, H A1 - Venugopalan, J A1 - Braun, P A1 - Wang, M D Y1 - 2017/// KW - Electronic health record KW - Health KW - Healthcare Interoperability KW - Intelligence KW - Interoperability KW - Medical applications KW - Medical professionals KW - Reusable technology KW - Third parties SP - 181 EP - 184 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018442805&doi=10.1109%2FBHI.2017.7897235&partnerID=40&md5=2ba482124cdfc32b5a45e0ef163fd77c L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Hoffman et al. - 2017 - Intelligent mortality reporting with FHIR.pdf N1 - Cited By :1 Export Date: 10 September 2018 References: (2013) Top 10 Causes of Death-Factsheet, , W. H. O. (W.H.O), Ed., ed; (2015) Health, United States, 2014: With Special Feature on Adults Aged 55-64, , N. C. f. H. Statistics; Randall, B., Death certification: A primer part i-an introduction to the death certificate (2014) South Dakota Medicine, 67; (1997) Possible Solutions to Common Problems in Death Certification, , N. C. f. H. Statistics, Ed., ed: Centers for Disease Control and Prevention; Cowper, D.C., Kubal, J.D., Maynard, C., Hynes, D.M., A primer and comparative review of major US mortality databases (2002) Annals of Epidemiology, 12, pp. 462-468; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., HL7 clinical document architecture, release 2 (2006) Journal of the American Medical Informatics Association, 13, pp. 30-39; Dolin, R.H., Alschuler, L., Beebe, C., Biron, P.V., Boyer, S.L., Essin, D., The HL7 clinical document architecture (2001) Journal of the American Medical Informatics Association, 8, pp. 552-569; Eichelberg, M., Aden, T., Riesmeier, J., Dogac, A., Laleci, G.B., Electronic health record standards-A brief overview (2006) Proceedings of the 4th IEEE International Conference on Information and Communications Technology (ICICT 2006); Blumenthal, D., Tavenner, M., The "meaningful use" regulation for electronic health records (2010) New England Journal of Medicine, 363, pp. 501-504; Bender, D., Sartipi, K., HL7 FHIR: An Agile and RESTful approach to healthcare information exchange (2013) Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on, pp. 326-331; Alterovitz, G., Warner, J., Zhang, P., Chen, Y., Ullman-Cullere, M., Kreda, D., SMART on FHIR Genomics: Facilitating standardized clinico-genomic apps (2015) Journal of the American Medical Informatics Association, 22, pp. 1173-1178; Smits, M., Kramer, E., Harthoorn, M., Cornet, R., A comparison of two detailed clinical model representations: FHIR and CDA (2015) European Journal for Biomedical Informatics, 11; Tao, C., Wongsuphasawat, K., Clark, K., Plaisant, C., Shneiderman, B., Chute, C.G., Towards event sequence representation, reasoning and visualization for EHR data (2012) The Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, , Miami, Florida, USA; Wang, T.D., Plaisant, C., Quinn, A.J., Stanchak, R., Murphy, S., Shneiderman, B., Aligning temporal data by sentinel events: Discovering patterns in electronic health records (2008) Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 457-466; Syed, H., Das, A.K., Identifying chemotherapy regimens in electronic health record data using interval-encoded sequence alignment (2015) Artificial Intelligence in Medicine, pp. 143-147. , ed: Springer; Casanova, I.J., Campos, M., Juarez, J.M., Fernandez-Arroyo, A., Lorente, J.A., Using multivariate sequential patterns to improve survival prediction in intensive care burn unit (2015) Artificial Intelligence in Medicine: 15th Conference on Artificial Intelligence in Medicine, AIME 2015, pp. 277-286. , Pavia, Italy, June 17-20, 2015. Proceedings, H. J. Holmes, R. Bellazzi, L. Sacchi, and N. Peek, Eds., ed Cham: Springer International Publishing; Batal, I., Valizadegan, H., Cooper, G.F., Hauskrecht, M., A pattern mining approach for classifying multivariate temporal data (2011) Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on, pp. 358-365; Yang, H., Yang, C.C., Using health-consumer-contributed data to detect adverse drug reactions by association mining with temporal analysis (2015) ACM Trans. Intell. Syst. Technol, 6, pp. 1-27; Bellazzi, R., Ferrazzi, F., Sacchi, L., Predictive data mining in clinical medicine: A focus on selected methods and applications (2011) Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1, pp. 416-430; Zhao, Q., Bhowmick, S.S., Sequential pattern mining: A survey (2003) ITechnical Report CAIS Nayang Technological University Singapore, pp. 1-26; Agrawal, R., Srikant, R., Fast algorithms for mining association rules (1994) Proc. 20th Int. Conf. Very Large Data Bases, VLDB, pp. 487-499; Agrawal, R., Srikant, R., Mining sequential patterns (1995) Data Engineering, 1995. Proceedings of the Eleventh International Conference on, pp. 3-14; Zaki, M.J., SPADE: An efficient algorithm for mining frequent sequences (2001) Machine Learning, 42, pp. 31-60; Pei, J., Han, J., Mortazavi-Asl, B., Wang, J., Pinto, H., Chen, Q., Mining sequential patterns by pattern-growth: The prefixspan approach (2004) Knowledge and Data Engineering, IEEE Transactions on, 16, pp. 1424-1440; Lin, M.-Y., Lee, S.-Y., Fast discovery of sequential patterns by memory indexing (2002) Data Warehousing and Knowledge Discovery, pp. 150-160. , ed: Springer; Mistry, B.R., Desai, A., Privacy preserving heuristic approach for association rule mining in distributed database (2015) Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on, pp. 1-7; Fu, A.W.-C., Wong, R.C.-W., Wang, K., Privacy-preserving frequent pattern mining across private databases (2005) Data Mining, Fifth IEEE International Conference on, p. 4; Sathiyapriya, K., Sadasivam, G.S., A survey on privacy preserving association rule mining (2013) International Journal of Data Mining &Knowledge Management Process, 3, p. 119; Soni, J., Ansari, U., Sharma, D., Soni, S., Predictive data mining for medical diagnosis: An overview of heart disease prediction (2011) International Journal of Computer Applications, 17, pp. 43-48; Concaro, S., Sacchi, L., Cerra, C., Fratino, P., Bellazzi, R., Mining health care administrative data with temporal association rules on hybrid events (2011) Methods Inf Med, 50, pp. 166-179; Dolce, G., Quintieri, M., Serra, S., Lagani, V., Pignolo, L., Clinical signs and early prognosis in vegetative state: A decisional tree, data-mining study (2008) Brain Injury, 22, pp. 617-623; McNally, M.R., Patton, C.L., Fremouw, W.J., Mining for murder-suicide: An approach to identifying cases of murder-suicide in the national violent death reporting system restricted access database (2015) Journal of Forensic Sciences; Srikant, R., Agrawal, R., (1996) Mining Sequential Patterns: Generalizations and Performance Improvements, , Springer; Wang, J., Han, J., Li, C., Frequent closed sequence mining without candidate maintenance (2007) Knowledge and Data Engineering, IEEE Transactions on, 19, pp. 1042-1056 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - One pressing need in the area of public health is timely, accurate, and complete reporting of deaths and the conditions leading up to them. Fast Healthcare Interoperability Resources (FHIR) is a new HL7 interoperability standard for electronic health record (EHR), while Sustainable Medical Applications and Reusable Technologies (SMART)-on-FHIR enables third-party app development that can work 'out of the box'. This research demonstrates the feasibility of developing SMART-on-FHIR applications to enable medical professionals to perform timely and accurate death reporting within multiple different jurisdictions of US. We explored how the information on a standard certificate of death can be mapped to resources defined in the FHIR standard (DSTU2). We also demonstrated analytics for potentially improving the accuracy and completeness of mortality reporting data. © 2017 IEEE. ER - TY - JOUR T1 - W2E-Wellness Warehouse Engine for Semantic Interoperability of Consumer Health Data A1 - Honko, H A1 - Andalibi, V A1 - Aaltonen, T A1 - Parak, J A1 - Saaranen, M A1 - Viik, J A1 - Korhonen, I Y1 - 2016/// KW - Adult KW - Advanced analysis KW - Algorithms KW - Application programming interfaces (API) KW - Bridges KW - Computer software reusability KW - Data unification KW - Data warehouses KW - Databases, Factual KW - Different services KW - Energy expenditure KW - Engines KW - Female KW - Fitness Trackers KW - Health KW - Health Status KW - Health monitoring devices KW - Humans KW - Information Storage and Retrieval KW - Input output programs KW - Interface states KW - Interoperability KW - Male KW - Metadata KW - Physical activity KW - Representational state transfer KW - Reusability KW - Semantic interoperability KW - Semantics KW - Warehouses KW - Young Adult KW - activity tracker KW - adult KW - algorithm KW - data warehousing KW - energy expenditure (EE) KW - factual database KW - female KW - human KW - information retrieval KW - male KW - physical activity KW - procedures KW - semantic interoperability KW - semantics KW - young adult JF - IEEE Journal of Biomedical and Health Informatics VL - 20 IS - 6 SP - 1632 EP - 1639 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027682504&doi=10.1109%2FJBHI.2015.2469718&partnerID=40&md5=e027149942c49fd804dc04596aa4595a N1 - Cited By :2 Export Date: 10 September 2018 References: Spivack, N., Consolidate this: Quantified self edition (2013) Gigaom.com, , http://gigaom.com/2013/10/13/consolidate-this-quantified-self-edition/, Oct. 13, [accessed: 09 Dec. 2013]; Comstock, J., 7 fitness apps with 16 million or more downloads (2013) Mobihealthnews.com, , http://mobihealthnews.com/24958/7-fitness-apps-with-16-millionor-more-downloads/, Aug. 26, [accessed: 09 Dec. 2013]; Mayo clinic announces development of mayo clinic healthy living population health offering (2013) Mayoclinic.org, , http://www.mayoclinic.org/news2013-rst/7540.html, Mayo Clinic. Jun. 14, [accessed: 22 Nov. 2013]; Pong, C., (2013) New Funding and More Accelerates Growth and Deepens Leadership Team, , http://keas.com/blog/keasaccelerates-growth/#ixzz2lI2koK8y, accessed: 22 Nov 2013; Comstock, J., Virgin HealthMiles adds Fitbit integration to employee wellness platform (2013) Mobihealthnews.com, , http://mobihealthnews.com/25380/virgin-healthmiles-addsfitbit-integration-to-employee-wellness-platform/, Sep. 11, [accessed: 22 Nov. 2013]; Validic API documentation 1.0 (2013) Validic.com, , https://validic.com/api/, Validic., Nov. 22; Health Informatic-Personal health device communication Part 10441: Device specialization-Cardiovascular fitness and activity monitor (2013) IEEE SA 11073-10441-2013, , http://standards.ieee.org/findstds/standard/11073-10441-2013.html, IEEE-SA Standards Board; Saaranen, M., Parak, J., Honko, J.H., Aaltonen, T., Korhonen, I., W2E-Wellness Warehouse Engine for semantic interoperability of consumer health data (2014) Proc. IEEE-EMBS Int. Conf. Biomed. Health Informat, , http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6864375, Jun. 1-4. Valencia, Spain. [accessed: 25 Jun 2015]; Human API-Integrate health data from anywhere (2015) Humanapi.co, , https://www.humanapi.co, HumanAPI. [accessed: 28 Jan. 2015]; (2015) Beddit.com, , http://www.beddit.com, Beddit. [accessed: 26 Jan. 2015]; Fitbit official site for activity trackers and more (2015) Fitbit.com, , http://fitbit.com, Fitbit. [accessed: 25 Jun. 2015]; (2015) Polar Flow, , https://flow.polar.com, Flow.polar.com. [accessed: 25 Jun. 2015]; Withings (2015) Withings.com, , http://www.withings.com, Withings. [accessed 25 June. 2015]; (2015) Runkeeper-Track Your Runs, Walks More with Your IPhone or Android Phone, , http://runkeeper.com, RunKeeper. [accessed: 24 Jan. 2015]; Moves-Activity diary for iPhone and Android (2015) Moves-app.com, , https://www.moves-app.com, Moves App. [accessed: 24 Jan. 2015]; UP by JawboneTM | A smarter activity tracker for a fitter you (2015) Jawbone.com, , https://jawbone.com/up, Jawbone. [accessed: 25 Jan. 2015]; Hardt, D., The OAuth 2.0 authorization framework (2011) RFC 6749, Internet Eng. Task Force, , http://www.rfceditor.org/info/rfc6749, Oct; Fielding, R.T., (2000) Architectural Styles and the Design of Network-based Software Architectures; (2014) Taltioni, , http://taltioni.fi/en/, Taltioni.fi. [accessed: 26 Jan. 2015]; (2014) 3. Getting started-W2E Beta API 0.1 Documentation, , https://w2e.fi/doc/getting_started.html#applicationcredentials, W2e.fi. [accessed: 25 Jun 2015]; (2015) MongoDB: A Document Oriented Database, , https://www.mongodb.org/about/, Mongodb.org; Inmon, W.H., (2005) Building the Data Warehouse, , http://www.amazon.com/Building-Data-Warehouse-W-Inmon/dp/0764599445, 4th ed., Wiley India Pvt. Limited; (2012) Whitepaper: An Energy Expenditure Estimation Method Based on Heart Rate Measurement, pp. 2-5. , http://www.firstbeat.com/userData/firstbeat/download/white_paper_energy_expenditure_estimation.pdf, Firstbeat Technologies. Mar. [accessed: 22nd Nov. 2013]; Enzo, R., Culiolo, A., (2012) ActiLife 6 Manual | ActiGraph, p. 48. , http://www.actigraphcorp.com/support/manuals/actilife-6-manual/, Actigraphcorp. Com. [accessed: 25 Jun. 2015]; Pober, D.M., Staudenmayer, J., Raphael, C., Freedson, P.S., Development of novel techniques to classify physical activity mode using accelerometers (2006) Med. Sci. Sports Exerc., 38 (9), pp. 1626-1634 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-EXCLUSION-REASONS: possibly useful methods? N2 - Novel health monitoring devices and applications allow consumers easy and ubiquitous ways to monitor their health status. However, technologies from different providers lack both technical and semantic interoperability and hence the resulting health data are often deeply tied to a specific service, which is limiting its reusability and utilization in different services. We have designed a Wellness Warehouse Engine (W2E) that bridges this gap and enables seamless exchange of data between different services. W2E provides interfaces to various data sources and makes data available via unified representational state transfer application programming interface to other services. Importantly, it includes Unifier-an engine that allows transforming input data into generic units reusable by other services, and Analyzer-an engine that allows advanced analysis of input data, such as combining different data sources into new output parameters. In this paper, we describe the architecture of W2E and demonstrate its applicability by using it for unifying data from four consumer activity trackers, using a test base of 20 subjects each carrying out three different tracking sessions. Finally, we discuss challenges of building a scalable Unifier engine for the ever-enlarging number of new devices. © 2013 IEEE. ER - TY - JOUR T1 - The hearing impairment ontology: A tool for unifying hearing impairment knowledge to enhance collaborative research A1 - Hotchkiss, J A1 - Manyisa, N A1 - Adadey, S M A1 - Oluwole, O G A1 - Wonkam, E A1 - Mnika, K A1 - Yalcouye, A A1 - Nembaware, V A1 - Haendel, M A1 - Vasilevsky, N A1 - Wonkam, A A1 - Mazandu, G K Y1 - 2019/// JF - Genes VL - 10 IS - 12 DO - 10.3390/genes10120960 N2 - ©2019 by the authors. Licensee MDPI, Basel, Switzerland. Hearing impairment (HI) is a common sensory disorder that is defined as the partial or complete inability to detect sound in one or both ears. This diverse pathology is associated with a myriad of phenotypic expressions and can be non‐syndromic or syndromic. HI can be caused by various genetic, environmental, and/or unknown factors. Some ontologies capture some HI forms, phenotypes, and syndromes, but there is no comprehensive knowledge portal which includes aspects specific to the HI disease state. This hampers inter‐study comparability, integration, and interoperability within and across disciplines. This work describes the HI Ontology (HIO) that was developed based on the Sickle Cell Disease Ontology (SCDO) model. This is a collaboratively developed resource built around the ʹHearing Impairmentʹ concept by a group of experts in different aspects of HI and ontologies. HIO is the first comprehensive, standardized, hierarchical, and logical representation of existing HI knowledge. HIO allows researchers and clinicians alike to readily access standardized HI‐related knowledge in a single location and promotes collaborations and HI information sharing, including epidemiological, socio‐environmental, biomedical, genetic, and phenotypic information. Furthermore, this ontology illustrates the adaptability of the SCDO framework for use in developing a disease‐specific ontology. ER - TY - JOUR T1 - Added Value from Secondary Use of Person Generated Health Data in Consumer Health Informatics A1 - Hsueh, P.-Y. A1 - Cheung, Y.-K. A1 - Dey, S A1 - Kim, K K A1 - Martin-Sanchez, F J A1 - Petersen, S K A1 - Wetter, T Y1 - 2017/// KW - Biomedical Research KW - Consumer Health Informatics KW - Humans KW - Informatics KW - Medical Informatics KW - Medical Informatics Applications KW - Privacy KW - consumer health informatics KW - human KW - medical informatics KW - medical research JF - Yearbook of medical informatics VL - 26 IS - 1 SP - 160 EP - 171 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041218318&doi=10.15265%2FIY-2017-009&partnerID=40&md5=57b95c5a9efc02d8337a102aa1fa45e5 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Hsueh et al. - 2017 - Added Value from Secondary Use of Person Generated Health Data in Consumer Health Informatics.pdf N1 - Cited By :3 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: Various health-related data, subsequently called Person Generated Health Data (PGHD), is being collected by patients or presumably healthy individuals as well as about them as much as they become available as measurable properties in their work, home, and other environments. Despite that such data was originally just collected and used for dedicated predefined purposes, more recently it is regarded as untapped resources that call for secondary use. Method: Since the secondary use of PGHD is still at its early evolving stage, we have chosen, in this paper, to produce an outline of best practices, as opposed to a systematic review. To this end, we identified key directions of secondary use and invited protagonists of each of these directions to present their takes on the primary and secondary use of PGHD in their sub-fields. We then put secondary use in a wider perspective of overarching themes such as privacy, interpretability, interoperability, utility, and ethics. Results: We present the primary and secondary use of PGHD in four focus areas: (1) making sense of PGHD in augmented Shared Care Plans for care coordination across multiple conditions; (2) making sense of PGHD from patient-held sensors to inform cancer care; (3) fitting situational use of PGHD to evaluate personal informatics tools in adaptive concurrent trials; (4) making sense of environment risk exposure data in an integrated context with clinical and omics-data for biomedical research. Discussion: Fast technological progress in all the four focus areas calls for a societal debate and decision-making process on a multitude of challenges: how emerging or foreseeable results transform privacy; how new data modalities can be interpreted in light of clinical data and vice versa; how the sheer mass and partially abstract mathematical properties of the achieved insights can be interpreted to a broad public and can consequently facilitate the development of patient-centered services; and how the remaining risks and uncertainties can be evaluated against new benefits. This paper is an initial summary of the status quo of the challenges and proposals that address these issues. The opportunities and barriers identified can serve as action items individuals can bring to their organizations when facing challenges to add value from the secondary use of patient-generated health data. Georg Thieme Verlag KG Stuttgart. ER - TY - JOUR T1 - Standardized terminological services enabling semantic interoperability between distributed and heterogeneous systems A1 - Ingenerf, Josef A1 - Reiner, Jörg A1 - Seik, Bettina Y1 - 2001/// KW - Vocabulary PB - Elsevier JF - International Journal of Medical Informatics VL - 64 IS - 2 SP - 223 EP - 240 CY - P. Amoah Barnie, University of Cape Coast, Cape Coast, Ghana UR - https://www.sciencedirect.com/science/article/pii/S1386505601002118?via%3Dihub N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The interconnection of heterogeneous computer applications in medicine raises the issue of semantic interoperability, going beyond traditional approaches of terminological standardization in basically three aspects. First, the variety of medical vocabularies that currently coexist in different domains is a major barrier for the integration of autonomously developed applications. Fortunately, with the Unified Medical Language System (UMLS) there are machine-readable terminological sources that cover and integrate most of the existing medical vocabularies. Second, the exchanged data need to be processed by a machine for different purposes like patient data integration, access to literature and knowledge bases as well as clinical audit and research. Medical vocabularies provided as passive dictionaries are no longer sufficient. Software system developers should take advantage of terminological services for refining user queries, for mapping the user's terms to appropriate medical vocabularies etc. Third, the services should be accessible uniformly and transparently. In the CORBAmed initiative a proposal for a standardized interface for querying and accessing computerized medical terminology resources was created. Based on the mentioned principles the MUSTANG system (Medical UMLS based Terminology Server for Authoring, Navigating and Guiding the Retrieval to Heterogeneous Knowledge Sources) has been developed. It is implemented on a Windows NT platform using the ORACLE database management and development software. The terminological services are accessible via multiple interfaces. The MUSTANG-System and the experiences with using terminological services in practice are described. Opposed to other levels of standardization like syntactical message standards there is much more a hesitation in the use of standardized terminology. ER - TY - JOUR T1 - A new data architecture for advancing life cycle assessment A1 - Ingwersen, W W A1 - Hawkins, T R A1 - Transue, T R A1 - Meyer, D E A1 - Moore, G A1 - Kahn, E A1 - Arbuckle, P A1 - Paulsen, H A1 - Norris, G A Y1 - 2015/// KW - Article KW - Data harmonization KW - Humanism KW - Humanities KW - Humans KW - Life cycle assessment KW - Life cycle impact assessment KW - Nomenclature KW - Ontology KW - Resource description framework KW - automation KW - conceptual framework KW - data analysis KW - data processing KW - health hazard KW - information processing KW - life cycle assessment KW - medical information KW - nomenclature KW - priority journal KW - statistical model JF - International Journal of Life Cycle Assessment VL - 20 IS - 4 SP - 520 EP - 526 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939415707&doi=10.1007%2Fs11367-015-0850-6&partnerID=40&md5=c85c6e816ad18fadcfca47eca52a0421 N1 - Cited By :12 Export Date: 10 September 2018 References: Allemang, D.H.J.A., (2011) Semantic web for the working ontologist: effective modeling in RDFS and OWL, , Morgan Kaufmann/Elsevier, Waltham; Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Davis, A.P., Eppig, J.T., Gene ontology: Tool for the unification of biology (2000) Nat Genet, 25 (1), pp. 25-29. , COI: 1:CAS:528:DC%2BD3cXjtFSlsbc%3D; Babaie, H.A., Oldow, J.S., Babaei, A., Lallemant, H.G.A., Watkinson, A.J., Designing a modular architecture for the structural geology ontology (2006) Geol S Am S Pap, 397, pp. 269-282; Berners-Lee, T.F.M., (1999) Weaving the web: the original design and ultimate destiny of the World Wide Web by its inventor, , Harper, San Francisco; Bertin, B., Scuturici, V.-M., Risler, E., Pinon J-M (2012) A semantic approach to life cycle assessment applied on energy environmental impact data management (2012) the, 2012, pp. 87-94. , Joint EDBT/ICDT Workshops: ACM; Bretz, R., SETAC LCA workgroup: Data availability and data quality (1998) Int J Life Cycle Assess, 3 (3), pp. 121-123; Carlson, R., Erixon, M., Erlandsson, M., Flemström, K., Häggström, S., Tivander, J., (2005) Establishing common primary data for environmental overview of product life cycles: users, perspectives, methods, data, and information systems, , Swedish Environmental Protection Agency, Stockholm; Davis, C., Nikolić, I., Dijkema, G.P., Integration of life cycle assessment into agent‐based modeling (2009) J Ind Ecol, 13 (2), pp. 306-325. , COI: 1:CAS:528:DC%2BD1MXmtVWitLk%3D; Derriere, S., Richard, A., Preite-Martinez, A., An ontology of astronomical object types for the Virtual Observatory (2006) Proc Int Astron Union, 2 (Highlights of Astronomy 14), p. 603; Fava, J., Baer, S., Cooper, J., Increasing demands for life cycle assessments in North America (2009) J Ind Ecol, 13 (4), pp. 491-494; Fox MS (2014) Foundation ontologies requirements for global city indicators; Geyer, R., Kuczenski, B., Henderson, A., Zink, T., Life cycle assessment of used oil management in California (2013) Prepared for State of California Department of Resources Recycling and Recovery, , Berkeley: CA; Glimm, B., Horrocks, I., Motik, B., Stoilos, G., Patel-Schneider, P.F., Pan, Y., Hitzler, P., Optimising ontology classification (2010) 9th International Semantic Web Conference, pp. 225-240. , Shanghai, China; Hawkins, T., Ingwersen, W., Srocka, M., Transue, T., Paulsen, H., Ciroth, A., A tools to support the widespread application of life cycle assessment: the LCA harmonization tool & OpenLCA (2013) In: International Symposium on Sustainable Systems & Technology, , ISSST, Cincinnati, OH; Hellweg, S., Demou, E., Bruzzi, R., Meijer, A., Rosenbaum, R.K., Huijbregts, M.A., McKone, T.E., Integrating human indoor air pollutant exposure within life cycle impact assessment (2009) Environ Sci Technol, 43 (6), pp. 1670-1679. , COI: 1:CAS:528:DC%2BD1MXhsFKitL0%3D; Hischier, R., Walser, T., Life cycle assessment of engineered nanomaterials: State of the art and strategies to overcome existing gaps (2012) Sci Total Environ, 425, pp. 271-282. , COI: 1:CAS:528:DC%2BC38XlvFejtLs%3D; Hischier, R., Hellweg, S., Capello, C., Primas, A., Establishing life cycle inventories of chemicals based on differing data availability (2005) Int J Life Cycle Assess, 10 (1), pp. 59-67. , COI: 1:CAS:528:DC%2BD2MXmsFersw%3D%3D; Hitzler, P., Janowicz, K., Semantic web (2014) Computing handbook, third edition: Computer science and software engineering, , Tucker A, Gonzalez T, Diaz-Herrera J, (eds), 1, Chapman and Hall/CRC, Boca Raton; Hitzler, P., Krötzsch, M., Parsia, B., Patel-Schneider, P.F., Rudolph, S., OWL 2 web ontology language primer (second edition) (2012) World Wide Web Consortium, , http://www.w3.org/TR/2012/REC-owl2-primer-20121211/; Jolliet, O., Ernstoff, A., Csiszar, S., (2013) High throughput exposure screening: addressing near field exposure and direct consumer exposure to products, , University of Michigan School of Public Health, Presentation to US EPA; Kounina, A., Margni, M., Bayart, J.-B., Boulay, A.-M., Berger, M., Bulle, C., Frischknecht, R., Humbert, S., Review of methods addressing freshwater use in life cycle inventory and impact assessment (2013) Int J Life Cycle Assess, 18 (3), pp. 707-721. , COI: 1:CAS:528:DC%2BC3sXisVanu74%3D; McBride, B., Norris, G., (2010) Earthster core ontology: description and rationale. Version 0.1-SNAPSHOT, , New Earth, Boston; McCarthy, S., Cooper, J., (2012) USDA’s digital commons: agricultural LCI Data, , Paper presented at the LCA XII, Tacoma, WA; Powers, S., (2009) Practical rdf, , O’Reilly, Cambridge; Rijgersberg, H., van Assem, M., Top, J., Ontology of units of measure and related concepts (2013) Semant Web, 4 (1), pp. 3-13; Takhom, A., Suntisrivaraporn, B., Supnithi, T., Ontology-enhanced life cycle assessment: a case study of application in oil refinery (2013) In: The Second Asian Conference on Information Systems (ACIS), , Phuket: Thailand; (2013) Executive order—making open and machine readable the new default for government information, , Office of the Press Secretary, Washington; Thiesen, J., Valdivia, S., Sonnemann, G., Fava, J., Swarr, T., Jensen, A., Price, E., Understanding challenges and needs: a stakeholder consul-tation on business’ applications of life cycle approaches (2007) CICLA, p. 2007. , San Jose, Costa Rica; UNEP/SETAC Life Cycle Initiative (2011) Global guidance principles for life cycle assessment databases (Shonan Guidance Principles); Vatant B, Wick M (2012) Geonames ontology; http://www.w3.org/RDF/, W3C (2004) Resource description framework; Walser, T., Juraske, R., Demou, E., Hellweg, S., Indoor exposure to toluene from printed matter matters: complementary views from life cycle assessment and risk assessment (2013) Environ Sci Technol, 48 (1), pp. 689-697; Zhang, Y., Luo, X., Buis, J.J., Sutherland, J.W., LCA-oriented semantic representation for the product life cycle (2015) J Clean Prod, 86, pp. 146-162 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: Life cycle assessment (LCA) has a technical architecture that limits data interoperability, transparency, and automated integration of external data. More advanced information technologies offer promise for increasing the ease with which information can be synthesized within an LCA framework. Vision: A new architecture is described that combines, stores, and annotates data for life cycle assessment. The Resource Description Framework is proposed for managing LCA data. To explore the capabilities of this approach, the LCA Harmonization Tool (LCA-HT) is being developed to map and store data from different sources and to clearly capture user-defined relationships between nomenclatures for easy use. It will enable increased interoperability of LCA data and more structured and automated incorporation of non-LCA data into LCA models. Moving forward: The LCA-HT is intended to be a core component of LCA data architecture (a data commons) used by US federal agencies and other data providers to make data representing US conditions more accessible for public use. It will also be used to bring together data from human health exposure models with traditional LCA for evaluating near-field human health risk in the life cycle context to demonstrate the practical advancements possible with this new architecture. The tool will remain open source and freely available. © 2015, Springer-Verlag Berlin Heidelberg. ER - TY - JOUR T1 - On the road to interoperability, public and private organizations work to connect health care data A1 - Jacob, J A Y1 - 2015/// KW - American Recovery and Reinvestment Act KW - Electronic Health Records KW - Health Information Exchange KW - Humans KW - Public-Private Sector Partnerships KW - Review KW - United States KW - certification KW - confidentiality KW - electronic medical record KW - electronics KW - financial management KW - health care access KW - health care cost KW - health care quality KW - health care system KW - health service KW - human KW - interoperability KW - law KW - legislation and jurisprudence KW - medicaid KW - medical history KW - medical informatics KW - medical information system KW - medicare KW - organization and management KW - patient care KW - patient information KW - priority journal KW - public health KW - public-private partnership KW - safety KW - social security KW - standard KW - treatment planning JF - JAMA - Journal of the American Medical Association VL - 314 IS - 12 SP - 1213 EP - 1215 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942279172&doi=10.1001%2Fjama.2015.5930&partnerID=40&md5=7e83c0b9e2da9d6b62b3fcc2f59fc7f8 N1 - Cited By :4 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} ER - TY - CONF T1 - Design considerations for an ontology in the domain of organ failure and transplantation A1 - Jacquelinet, C A1 - Burgun, A A1 - Delamarre, D A1 - Strang, N A1 - Boutin, B A1 - Le Beux, P Y1 - 2002/// KW - France KW - Humans KW - Information Systems KW - Organ Transplantation KW - Terminology KW - Tissue and Organ Procurement KW - article KW - human KW - information system KW - nomenclature KW - organ transplantation KW - transplantation VL - 90 SP - 611 EP - 615 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-7944230970&doi=10.3233%2F978-1-60750-934-9-611&partnerID=40&md5=58e4f2e1edbf5b077bf6470741e25d35 N1 - Cited By :2 Export Date: 10 September 2018 References: Sheth, A., Larson, J., Federated systems for managing distributed, heteregeneous and autonomous databases (1990) ACM Computing Surveys, 22, pp. 183-235; Stengel, B., Landais, P., Data Collection about the case management of end-stage renal insufficiency (1999) Nephrologie, 20, pp. 29-40; (1990) IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries, , IEEE; Hammond, W.E., The role of standards in creating a health information infrastructure (1994) Int J Biomed Comput, 34, pp. 29-44; Dudeck, J., Aspects of implementing and harmonising healthcare communication standards (1998) Int J Med Inf., 48, pp. 163-171; Mallick, N.P., Jones, E., Selwood, N., The european (european dialysis and transplantation association-european renal association) registry (1995) Am J Kidney Dis., 25 (1), pp. 176-187. , Jan; Sowa, J.F., (1984) Conceptual Structures: Information Processing in Mind and Machine, , Addison-Wesley, London; Sowa, J.F., (1992) Conceptual Graph Summary, in Conceptual Structures: Current Research and Practice -Rftxt Nagle, Nagle, Gerholz & Eklund Ed.; Ellis Horwood Workshops; Volot, F., Joubert, M., Fieschi, M., Review of biomedical knowledge and data representation with conceptual graphs (1998) Meth Inf Med., 37, pp. 86-96; Jacquelinet, C., Burgun, A., Building the ontological foundations of a terminology from natural language to conceptual graphs with ribosome, a knowledge extraction tool (2000) ICCS Proceedings, , In Working with Conceptual Structures. G Stumme Ed, Shaker Verlag, Aachen; Burgun, A., Bodenreider, O., Denier, P., Delamarre, D., Botti, G., Oberlin, P., Leveque, J.M., Le Beux, P., A collaborative approach to building a terminology for medical procedures using a Webbased application: From specifications to daily use (1998) MEDINFO, (PART 1), pp. 596-599; De Keizer, N.F., Abu-Anna, A., Jhm, Z., Understanding terminological systems I: Terminology and typology (2000) Meth Inform Med., 39, pp. 16-21; De Keizer, N.F., Abu-Anna, A., Understanding terminological systems II: Experience with conceptual and formal representation of structure (2000) Meth Inform Med., 39, pp. 22-29; Rossi Mori, A., Exploiting the terminological approach from CEN/TC251 and GALEN to support semantic interoperability of healthcare record systems (1998) Int J Med Inf., 48, pp. 111-124; Mc Donald, C.J., What is done, what is needed and what is realistic to expect from medical informatics standards (1998) Int J Med Inf., 48, pp. 5-12; Spackman, K., Campbell, K.E., Compositional concept representation using SNOMED: Toward further convergence of clinical terminologies (1998) Proc AMIA Symp, pp. 740-744 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Etablissement francais des Greffes (EfG) is a national agency dealing with Public Health issues related to organ, tissue and cell transplantation in France. The evaluation of organ retrieval and transplantation activities, one of its missions, is supported by a national information system (IS). In order to facilitate data recording, to improve the quality of information and to prepare semantic interoperability with other information systems, the existing thesaurus of the EfG was audited, leading to the design a new terminological module devoted to the support of the domain ontology. ER - TY - CONF T1 - A contextual coding system for transplantation and end stage diseases A1 - Jacquelinet, C A1 - Burgun, A A1 - Djabbour, S A1 - Delamarre, D A1 - Clerc, P A1 - Boutin, B A1 - Le Beux, P Y1 - 2003/// KW - EDI KW - Knowledge Representation KW - Ontology KW - Organ Failure KW - Semantic Interoperability KW - Terminological system KW - Thesaurus KW - Transplantation VL - 95 SP - 457 EP - 462 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-31544443886&doi=10.3233%2F978-1-60750-939-4-457&partnerID=40&md5=fbdd94fc86235237906ee5b210883a8a N1 - Cited By :5 Export Date: 10 September 2018 References: IEEE Standard Computer Dictionary : A compilation of IEEE Standard Computer Glossaries, IEEE (1990); Dudeck, J., Aspects of implementing and harmonising healthcare communication standards (1998) J Med Inf, 48, pp. 163-71; Hammond, W.E., The role of standards in creating a health information infrastructure (1994) J Biomed Comput, 34, pp. 29-44; Mallick, N.P., Jones, E., Selwood, N., The european (european dialysis and transplantation association-european renal association) registry (1995) Am J Kidney Dis., 25 (1), pp. 176-87. , Jan; Stengel, B., Landais, P., Data Collection about the case management of end-stage renal insufficiency (1999) Nephrologie, 20, pp. 29-40; Sheth, A., Larson, J., Federated systems for managing distributed, heteregeneous and autonomous databases (1990) ACM Computing Surveys, 22, pp. 183-235; Landais, P., Simonet, A., Guillon, D., Jacquelinet, C., Ben Said, M., Mugnier, C., Simonet, M., Un système d'information multi-sources pour le réseau épidémiologie et information en nephrologie : Le projet REIN (2002) Informatique et Santé Springer Verlag France, (13), pp. 131-138; Jacquelinet, C., Burgun, A., Building the ontological foundations of a terminology from natural language to conceptual graphs with Ribosome, a knowledge extraction tool (2000) ICCS Proceedings. in Working with Conceptual Structures, , G Stumme Ed, Shaker Verlag, Aache; Jacquelinet, C., Burgun, A., Delamarre, D., Strang, N., Boutin, B., Le Beux, P., Design considerations for an ontology in the domain of organ failure and transplantation (2002) MIE 2002, pp. 611-615. , G Sudan Ed, IOS Press; Sowa, J.F., (1984) Conceptual Structures: Information Processing in Mind and Machine, , Addison-Wesley, London; Volot, F., Joubert, M., Fieschi, M., Review of biomedical knowledge and data representation with Conceptual graphs (1998) Meth Inf Med, 37, pp. 86-96; De Keizer, N.F., Abu-Anna, A., Zwetsloot-Shonk, J.H.M., Understanding terminological systems i: Terminology and typology (2000) Meth Inform Med., 39, pp. 16-21; De Keizer, N.F., Abu-Anna, A., Understanding terminological systems ii: Experience with conceptual and formal representation of structure (2000) Meth Inform Med., 39, pp. 22-9; Rossi Mori, A., Exploiting the terminological approach from CEN/TC251 and GALEN to support semantic interoperability of healthcare record systems (1998) J Med Inf, 48, pp. 111-24; Mc Donald, C.J., What is done, what is needed and what is realistic to expect from medical informatics standards (1998) J Med Inf, 48, pp. 5-12; Bürkle, T., Prokosch, H.-U., Hussak, G., Dudeck, J., Knowledge based functions for routine use at a German university hospital setting: The issue of fine tuning (1997) Proc AMIA Annu Fall Symp., pp. 61-5; Mueller, M.L., Ganslandt, T., Frankewitsch, T., Krieglstein, C.F., Senninger, N., Prokosch, H.U., Workflow analysis and evidence-based medicine: Towards integration of knowledge-based functions in hospital information systems (1999) Proc AMIA Symp., pp. 330-4 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Etablissement frangais des Greffes (EfG) is a state agency dealing with Public Health issues related to organ, tissue and cell transplantation in France. EfG maintains a national information system (EfG-IS) for the evaluation of organ transplantation activities. The EfG-IS is moving toward a new n-tier architecture comprising a terminological server. Because this terminological server is shared by various kind of transplant teams and dialysis centers to record patients data at different time point, contextualisation of terms appeared as a functional requirement. We report in this paper various contexts for medical terms and how they have been taken into account. ER - TY - JOUR T1 - The digital earth as knowledge engine A1 - Janowicz, K A1 - Hitzler, P Y1 - 2012/// KW - Earth (Planet) KW - Geography JF - Semantic Web VL - 3 IS - 3 SP - 213 EP - 221 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84868326263&doi=10.3233%2FSW-2012-0070&partnerID=40&md5=bbe2003df6d822f618f020cbe79d4799 N1 - Cited By :35 Export Date: 10 September 2018 References: Anderson, C., Wolff, M., (2010) The Web Is Dead. Long Live the Internet. Wired Magazine, , September; Barsalou, L.W., Grounded cognition (2008) Annual Review of Psychology, 59 (1), pp. 617-645; Berners-Lee, T., Hendler, J., Lassila, O., The semantic web (2001) Scientific American, 284 (5), pp. 34-43. , May; Bizer, C., Heath, T., Berners-Lee, T., Linked data-The story so far (2009) International Journal on Semantic Web and Information Systems, 5 (3), pp. 1-22; Boley, H., Hallmark, G., Kifer, M., Paschke, A., Polleres, A., Reynolds, D., (2010) RIF Core Di-alect. W3C Recommendation 22, , http://www.w3.org/TR/rif-core/, June 2010; Bouquet, P., Giunchiglia, F., Van Harmelen, F., Serafini, L., Stuckenschmidt, H., Contextualizing ontologies (2004) Journal of Web Semantics, 1 (4), pp. 325-343; Brodaric, B., Gahegan, M., Ontology use for semantic e-science (2010) Semantic Web, 1 (1-2), pp. 149-153. , Apr; Craglia, M., Goodchild, M., Annoni, A., Camara, G., Gould, M., Kuhn, W., Mark, D., Parsons, E., Next-generation digital earth (2008) Int. J. Spatial Data Infrastructures Research, 3, pp. 146-167; Euzenat, J., Shvaiko, P., (2007) Ontology Matching, , Springer-Verlag, Heidelberg (DE); Ferrucci, D., Building watson: An overview of the DeepQA project AI Magazine, 31 (3), p. 2010; Goodchild, M., Citizens as sensors: The world of volunteered geography (2007) GeoJournal, 69 (4), pp. 211-221; Goodchild, M., Yuan, M., Cova, T., Towards a general theory of geographic representation in gis (2007) Inter-national Journal of Geographical Information Science, 21 (3), pp. 239-260; Gore, A., (1998) The Digital Earth: Understanding Our Planet in the 21st Century; Halpin, H., Hayes, P.J., McCusker, J.P., McGuinness, D.L., Thompson, H.S., When owl:sameas isn't the same: An analysis of identity in Linked Data (2010) The Se-mantic Web -ISWC 2010 -9th International Seman-tic Web Conference, ISWC 2010, pp. 305-320. , P. F. Patel-Schneider, Y. Pan, P. Hitzler, P. Mika, L. Zhang, J. Z. Pan, I. Horrocks, and B. Glimm, editors, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I volume 6496 of Lecture Notes in Computer Science, Springer, Heidelberg; Hawkins, J., Blakeslee, S., On intelligence (2004) Times Books; Hitzler, P., Krötzsch, M., Parsia, B., Patel-Schneider, P.F., Rudolph, S., (2009) OWL 2 Web Ontology Language: Primer, , http://www.w3.org/TR/owl2-primer/, W3C Recommendation, 27 October 2009; Hitzler, P., Krötzsch, M., Rudolph, S., (2009) Founda-tions of Semantic Web Technologies., , Chapman & Hall/CRC; Hitzler, P., Van Harmelen, F., A reasonable semantic web (2010) Semantic Web, 1 (1-2), pp. 39-44; Jain, P., Hitzler, P., Sheth, A.P., Verma, K., Yeh, P.Z., Ontology alignment for linked open data (2010) The Se-mantic Web -ISWC 2010 -9th International Seman-tic Web Conference, ISWC 2010, pp. 402-417. , P. F. Patel-Schneider, Y. Pan, P. Hitzler, P. Mika, L. Zhang, J. Z. Pan, I. Horrocks, and B. Glimm, editors, Shanghai, China, November 7-11, 2010, Revised Selected Papers, Part I volume 6496 of Lecture Notes in Computer Science, Springer, Heidelberg; Jain, P., Hitzler, P., Yeh, P.Z., Verma, K., Sheth, A.P., Linked data is merely more data (2010) AAAI Spring Symposium 'Linked Data Meets Artificial In-telligence', pp. 82-86. , AAAI Press; Jain, P., Yeh, P.Z., Verma, K., Vasquez, R.G., Damova, M., Hitzler, P., Sheth, A.P., Contextual ontology alignment of LOD with an upper ontology: A case study with Proton (2011) The Semantic Web: Re-search and Applications -8th Extended Semantic Web Conference, ESWC 2011, pp. 80-92. , G. Antoniou, M. Grobelnik, E. P. B. Simperl, B. Parsia, D. Plexousakis, P. D. Leenheer, and J. Z. Pan, editors, Heraklion, Crete, Greece, May 29-June 2, 2011, Proceedings, Part I volume 6643 of Lecture Notes in Computer Science, Springer, Heidelberg; Janowicz, K., The role of space and time for knowledge organization on the semantic web (2010) Semantic Web, 1 (1-2), pp. 25-32; Janowicz, K., Observation-driven geo-ontology engineering (2012) Transactions in GIS, 16 (3), pp. 351-374; Janowicz, K., Raubal, M., Kuhn, W., The semantics of similarity in geographic information retrieval (2011) Journal of Spatial Information Science, 2, pp. 29-57; Kuhn, W., Geospatial semantics: Why, of what, and how? (2005) Journal on Data Semantics III Volume 3534 of Lecture Notes in Computer Science, pp. 587-587. , S. Spaccapietra and E. Zimfianyi, editors, , Springer Berlin/Heidelberg; Lund, G., (2012) Definitions of Forest, Deforestation, Afforestation, and Reforestation. [Online] Gainesville, Va: Forest Information Services, , http://home.comcast.net/-gyde/DEFpaper.htm, available from the world wide web:, Technical report; Motik, B., Patel-Schneider, P.F., Cuenca Grau, B., (2009) OWL 2 Web Ontology Language: Direct Semantics, , http://www.w3.org/TR/owl2-direct-semantics/, W3C Recommendation 27 October; NASA. A.40 computational modeling algorithms and cyberinfrastructure (December 19, 2011). Technical report, National Aeronautics and Space Administration (NASA), 2012; Scheider, S., (2011) Grounding Geographic Information in Perceptual Operations, , PhD Thesis University of Münster Germany. Technical report; Schlieder, C., Digital heritage: Semantic challenges of long-term preservation (2010) Semantic Web, 1 (1-2), pp. 143-147; Von Glasersfeld, E., Reconstructing the concept of knowledge (1985) Archives de Psychologie, 53 (204), pp. 91-101 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Digital Earth [13] aims at developing a digital representation of the planet. It is motivated by the need for integrating and interlinking vast geo-referenced, multi-thematic, and multi-perspective knowledge archives that cut through domain boundaries. Complex scientific questions cannot be answered from within one domain alone but span over multiple scientific disciplines. For instance, studying disease dynamics for prediction and policy making requires data and models from a diverse body of science ranging from medical science and epidemiology over geography and economics to mining the social Web. The naïve assumption that such problems can simply be addressed by more data with a higher spatial, temporal, and thematic resolution fails as long as this more on data is not supported by more knowledge on how to combine and interpret the data. This makes semantic interoperability a core research topic of data-intensive science. While the Digital Earth vision includes processing services, it is, at its very core, a data archive and infrastructure. We propose to redefine the Digital Earth as a knowledge engine and discuss what the Semantic Web has to offer in this context and to Big Data in general. © 2010 - IOS Press and the authors. All rights reserved. ER - TY - JOUR T1 - A semantic proteomics dashboard (SemPoD) for data management in translational research A1 - Jayapandian, Catherine P A1 - Zhao, Meng A1 - Ewing, Rob M A1 - Zhang, Guo Qiang A1 - Sahoo, Satya S Y1 - 2012/// KW - Computational Biology KW - Proteome KW - Proteomics PB - BioMed Central Ltd JF - BMC Systems Biology VL - 6 SP - S20 EP - S20 UR - http://www.biomedcentral.com/1752-0509/6/S3/S20 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND: One of the primary challenges in translational research data management is breaking down the barriers between the multiple data silos and the integration of 'omics data with clinical information to complete the cycle from the bench to the bedside. The role of contextual metadata, also called provenance information, is a key factor ineffective data integration, reproducibility of results, correct attribution of original source, and answering research queries involving "What", "Where", "When", "Which", "Who", "How", and "Why" (also known as the W7 model). But, at present there is limited or no effective approach to managing and leveraging provenance information for integrating data across studies or projects. Hence, there is an urgent need for a paradigm shift in creating a "provenance-aware" informatics platform to address this challenge. We introduce an ontology-driven, intuitive Semantic Proteomics Dashboard (SemPoD) that uses provenance together with domain information (semantic provenance) to enable researchers to query, compare, and correlate different types of data across multiple projects, and allow integration with legacy data to support their ongoing research.\n\nRESULTS: The SemPoD platform, currently in use at the Case Center for Proteomics and Bioinformatics (CPB), consists of three components: (a) Ontology-driven Visual Query Composer, (b) Result Explorer, and (c) Query Manager. Currently, SemPoD allows provenance-aware querying of 1153 mass-spectrometry experiments from 20 different projects. SemPod uses the systems molecular biology provenance ontology (SysPro) to support a dynamic query composition interface, which automatically updates the components of the query interface based on previous user selections and efficiently prunes the result set usinga "smart filtering" approach. The SysPro ontology re-uses terms from the PROV-ontology (PROV-O) being developed by the World Wide Web Consortium (W3C) provenance working group, the minimum information required for reporting a molecular interaction experiment (MIMIx), and the minimum information about a proteomics experiment (MIAPE) guidelines. The SemPoD was evaluated both in terms of user feedback and as scalability of the system.\n\nCONCLUSIONS: SemPoD is an intuitive and powerful provenance ontology-driven data access and query platform that uses the MIAPE and MIMIx metadata guideline to create an integrated view over large-scale systems molecular biology datasets. SemPoD leverages the SysPro ontology to create an intuitive dashboard for biologists to compose queries, explore the results, and use a query manager for storing queries for later use. SemPoD can be deployed over many existing database applications storing 'omics data, including, as illustrated here, the LabKey data-management system. The initial user feedback evaluating the usability and functionality of SemPoD has been very positive and it is being considered for wider deployment beyond the proteomics domain, and in other 'omics' centers. ER - TY - JOUR T1 - A scalable cloud-based cyberinfrastructure platform for bridge monitoring A1 - Jeong, S A1 - Hou, R A1 - Lynch, J P A1 - Sohn, H A1 - Law, K H Y1 - 2019/// JF - Structure and Infrastructure Engineering VL - 15 IS - 1 SP - 82 EP - 102 DO - 10.1080/15732479.2018.1500617 N2 - ©2018, ©2018 Informa UK Limited, trading as Taylor & Francis Group. Cloud computing is a computing paradigm wherein computing resources, such as servers, storage and applications, can be provisioned and accessed in real time via advanced communication networks. In the era of Internet of Things (IoT) and big data, cloud computing has been widely developed in many industrial applications involving large volume of data. Appropriate use of cloud computing infrastructure can enhance the long-term deployment of a structural health monitoring (SHM) system which would incur significant amount of data of different types. This paper presents a cloud-based cyberinfrastructure platform designed to support bridge monitoring. The cyberinfrastructure platform enables scalable management of SHM data and facilitates effective information sharing and data utilisation. A cloud-based platform comprises of virtual machines, distributed database and web servers. The peer-to-peer distributed database architecture provides a scalable and fault-tolerant data management system. Platform-neutral web services designed in compliant with the Representational State Transfer (REST) standard enables easy access to the cloud resources and SHM data. For data interoperability, a bridge information model for bridge monitoring applications is adopted. For demonstration, the scalable cloud-based platform is implemented for the monitoring of bridges along the I-275 corridor in the State of Michigan. The results show that the cloud-based cyberinfrastructure platform can effectively manage the sensor data and bridge information and facilitate efficient access of the data as well as the bridge monitoring software services. ER - TY - JOUR T1 - Converting clinical document architecture documents to the common data model for incorporating health information exchange data in observational health studies: CDA to CDM A1 - Ji, H A1 - Kim, S A1 - Yi, S A1 - Hwang, H A1 - Kim, J.-W. A1 - Yoo, S Y1 - 2020/// JF - Journal of Biomedical Informatics VL - 107 DO - 10.1016/j.jbi.2020.103459 N2 - ©2020 Elsevier Inc. Background: Utilization of standard health information exchange (HIE) data is growing due to the high adoption rate and interoperability of electronic health record (EHR) systems. However, integration of HIE data into an EHR system is not yet fully adopted in clinical research. In addition, data quality should be verified for the secondary use of these data. Thus, the aims of this study were to convert referral documents in a Health Level 7 (HL7) clinical document architecture (CDA) to the common data model (CDM) to facilitate HIE data availability for longitudinal data analysis, and to identify data quality levels for application in future clinical studies. Methods: A total of 21,492 referral CDA documents accumulated for over 10 years in a tertiary general hospital in South Korea were analyzed. To convert CDA documents to the Observational Medical Outcomes Partnership (OMOP) CDM, processes such as CDA parsing, data cleaning, standard vocabulary mapping, CDA-to-CDM mapping, and CDM conversion were performed. The quality of CDM data was then evaluated using the Achilles Heel and visualized with the Achilles tool. Results: Mapping five CDA elements (document header, problem, medication, laboratory, and procedure) into an OMOP CDM table resulted in population of 9 CDM tables (person, visit_occurrence, condition_occurrence, drug_exposure, measurement, observation, procedure_occurrence, care_site, and provider). Three CDM tables (drug_era, condition_era, and observation_period) were derived from the converted table. From vocabulary mapping codes in CDA documents according to domain, 98.6% of conditions, 68.8% of drugs, 35.7% of measurements, 100% of observation, and 56.4% of procedures were mapped as standard concepts. The conversion rates of the CDA to the OMOP CDM were 96.3% for conditions, 97.2% for drug exposure, 98.1% for procedure occurrence, 55.1% for measurements, and 100% for observation. Conclusions: We examined the possibility of CDM conversion by defining mapping rules for CDA-to-CDM conversion using the referral CDA documents collected from clinics in actual medical practice. Although mapping standard vocabulary for CDM conversion requires further improvement, the conversion could facilitate further research on the usage patterns of medical resources and referral patterns. ER - TY - JOUR T1 - Health Data in Dentistry: An Attempt to Master the Digital Challenge A1 - Joda, T A1 - Waltimo, T A1 - Probst-Hensch, N A1 - Pauli-Magnus, C A1 - Zitzmann, N U Y1 - 2019/// JF - Public Health Genomics VL - 22 IS - 1-2 SP - 1 EP - 7 DO - 10.1159/000501643 N2 - ©2019 S. Karger AG, Basel. Copyright: All rights reserved. Background: Biomedical research has recently moved through three stages in digital healthcare: (1) data collection; (2) data sharing; and (3) data analytics. With the explosion of stored health data (HD), dental medicine is edging into its fourth stage of digitization using artificial intelligence (AI). This narrative literature review outlines the challenge of managing HD and anticipating the potential of AI in oral healthcare and dental research by summarizing the current literature. Summary: The basis of successful management of HD is the establishment of a generally accepted data standard that will guide its implementation within electronic health records (EHR) and health information technology ecosystems (HIT Eco). Thereby continuously adapted (self-) learning health systems (LHS) can be created. The HIT Eco of the future will combine (i) the front-end utilization of HD in clinical decision-making by providers using supportive diagnostic tools for patient-centered treatment planning, and (ii) back-end algorithms analyzing the standardized collected data to inform population-based policy decisions about resource allocations and research directions. Cryptographic methods in blockchain enable a safe, more efficient, and effective dental care within a global perspective. Key Message: The interoperability of HD with accessible digital health technologies is the key to deliver value-based dental care and exploit the tremendous potential of AI. ER - TY - JOUR T1 - Extending the DIDEO ontology to include entities from the natural product drug interaction domain of discourse A1 - Judkins, J A1 - Tay-Sontheimer, J A1 - Boyce, R D A1 - Brochhausen, M Y1 - 2018/// KW - Biomedical ontologies KW - Drug-drug interactions KW - Natural product-drug interactions KW - OWL KW - Pharmaceuticals KW - Pharmacokinetics JF - Journal of Biomedical Semantics VL - 9 IS - 1 CY - University of Arkansas for Medical Sciences, Department of Biomedical Informatics, Little Rock, AR, United States DO - 10.1186/s13326-018-0183-z UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046641861&doi=10.1186%2Fs13326-018-0183-z&partnerID=40&md5=328fee5fa595643df50e3fd2bba0e7fd L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Judkins et al. - 2018 - Extending the DIDEO ontology to include entities from the natural product drug interaction domain of discourse.pdf N1 - Export Date: 29 May 2018 N2 - Background: Prompted by the frequency of concomitant use of prescription drugs with natural products, and the lack of knowledge regarding the impact of pharmacokinetic-based natural product-drug interactions (PK-NPDIs), the United States National Center for Complementary and Integrative Health has established a center of excellence for PK-NPDI. The Center is creating a public database to help researchers (primarly pharmacologists and medicinal chemists) to share and access data, results, and methods from PK-NPDI studies. In order to represent the semantics of the data and foster interoperability, we are extending the Drug-Drug Interaction and Evidence Ontology (DIDEO) to include definitions for terms used by the data repository. This is feasible due to a number of similarities between pharmacokinetic drug-drug interactions and PK-NPDIs. Methods: To achieve this, we set up an iterative domain analysis in the following steps. In Step 1 PK-NPDI domain experts produce a list of terms and definitions based on data from PK-NPDI studies, in Step 2 an ontology expert creates ontologically appropriate classes and definitions from the list along with class axioms, in Step 3 there is an iterative editing process during which the domain experts and the ontology experts review, assess, and amend class labels and definitions and in Step 4 the ontology expert implements the new classes in the DIDEO development branch. This workflow often results in different labels and definitions for the new classes in DIDEO than the domain experts initially provided; the latter are preserved in DIDEO as separate annotations. Results: Step 1 resulted in a list of 344 terms. During Step 2 we found that 9 of these terms already existed in DIDEO, and 6 existed in other OBO Foundry ontologies. These 6 were imported into DIDEO; additional terms from multiple OBO Foundry ontologies were also imported, either to serve as superclasses for new terms in the initial list or to build axioms for these terms. At the time of writing, 7 terms have definitions ready for review (Step 2), 64 are ready for implementation (Step 3) and 112 have been pushed to DIDEO (Step 4). Step 2 also suggested that 26 terms of the original list were redundant and did not need implementation; the domain experts agreed to remove them. Step 4 resulted in many terms being added to DIDEO that help to provide an additional layer of granularity in describing experimental conditions and results, e.g. transfected cultured cells used in metabolism studies and chemical reactions used in measuring enzyme activity. These terms also were integrated into the NaPDI repository. Conclusion: We found DIDEO to provide a sound foundation for semantic representation of PK-NPDI terms, and we have shown the novelty of the project in that DIDEO is the only ontology in which NPDI terms are formally defined. © 2018 The Author(s). ER - TY - JOUR T1 - Blockchain Technologies: Opportunities for Solving Real-World Problems in Healthcare and Biomedical Sciences A1 - Justinia, Taghreed Y1 - 2019/// JF - Acta Informatica Medica VL - 27 IS - 4 SP - 284 EP - 284 DO - 10.5455/aim.2019.27.284-291 UR - https://www.ejmanager.com/fulltextpdf.php?mno=302645059 N2 - ©2019 Taghreed Justinia Introduction: Blockchain technology is associated with the financial industry, but it can be applied to other industries. The supporting architecture of blockchain has the immense potential to transform the delivery of healthcare, medical, clinical, and life sciences, due to the extended functionality and distinct features of its distributed ledger. The potential scale of impact is comparable to that seen with the introduction of TCP/IP. Blockchain technology has captured the interest of healthcare providers and biomedical scientists within various healthcare domains such as longitudinal healthcare records, automated claims, drug development, interoperability in population health, consumer health, patient portals, medical research, data security, and reducing costs with supply chain management. It is not yet clear if blockchain is going to disrupt healthcare, but healthcare organizations are monitoring its potential closely for prospective concepts like secure patient IDs. Realistically, the adoption and implementation of blockchains will be a gradual evolution over time, but now is the time to take a fresh look at its possibilities in healthcare and biomedical sciences. Blockchain technology revolutionary solutions are bringing us closer to the possibility of every patient record being able to send updates to an open-source, community-wide trusted ledger that is accessible and understood across organizations with guaranteed integrity. Aim and Methods: This paper discusses as a review some potential areas of opportunity for blockchain in the health and biomedical sciences fields. Results and Conclusions: This paper describes and synthesizes 20 examples of real-world use-case scenarios for blockchains in healthcare and biomedical practice. ER - TY - CONF T1 - Spatial data cube concept to support data analysis in environmental epidemiology A1 - Kamp, V A1 - Sitzmann, L A1 - Wietek, F Y1 - 1997/// KW - Data reduction KW - Data structures KW - Database systems KW - Decision support systems KW - Epidemiological and statistical data exploration s KW - Epidemiology KW - Medical applications KW - Multidimensional analysis KW - Registries KW - Statistical methods KW - Statistics as Topic SP - 100 EP - 103 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-0030693046&partnerID=40&md5=d0a656982edcc28d4a6f3b5a15b815b8 N1 - Cited By :3 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The project CARLOS (Cancer Registry Lower-Saxony) developed the Epidemiological and Statistical Data Exploration System (CARESS) to support multidimensional analysis of health data. The system is based on an architecture that focuses on extensive interoperability between a database management system and several analysis and visualization tools. As spatial and statistical aspects of the data play an important role, CARESS provides special support for the integration of both. ER - TY - CONF T1 - A framework for the consistent management of eHealth interoperability in Greece A1 - Katehakis, D G A1 - Kouroubali, A Y1 - 2019/// JF - ICEIS 2019 - Proceedings of the 21st International Conference on Enterprise Information Systems VL - 2 SP - 689 EP - 695 SN - 9789897583728 N2 - Copyright ©2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved. This work presents an approach for the organized development of a countrywide framework to address the ever-growing demand for acquiring, exchanging and exploiting patient information to support high quality and cost-effective healthcare delivery. The national electronic health (eHealth) landscape in Greece is examined within the context of the recent recommendation on a European electronic health record (EHR) exchange format. Improving quality of life and well-being, in a secure and safe manner that respects the patients' privacy, is the key challenge. Interoperability of information and communication technology (ICT) systems is central for reliable and efficient collaboration between the involved stakeholders, including the patient and associated caretakers. In order to accelerate transformation towards citizen empowerment and a more sustainable health system, national authorities need to address issues relevant to mutually beneficial goals in a coherent manner. Practical implications are related to the sustainability of the underlying national infrastructure required to support reliable and secure exchange of meaningful EHR data, for both primary and secondary use, and by defining technical specifications for well-defined use cases, in a legitimate and standardized manner, under a highly regulated environment. ER - TY - CONF T1 - Towards the development of a national ehealth interoperability framework to address public health challenges in Greece A1 - Katehakis, D G A1 - Kouroubali, A A1 - Fundulaki, I Y1 - 2018/// KW - Developed Countries KW - Developing Countries KW - Electronic Health Record KW - Electronic health record KW - General practitioners KW - Greece KW - Information and Communication Technologies KW - Information management KW - Interoperability KW - Interoperability framework KW - National Health System KW - National health system KW - Public Health KW - Public and private sector KW - Public health KW - Records management KW - Semantic Web KW - Technical specifications KW - Telemedicine KW - eHealth VL - 2164 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051959182&partnerID=40&md5=93b9f6d5bfc9e51c2fd07d38523a4dfa L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Katehakis, Kouroubali, Fundulaki - 2018 - Towards the development of a national ehealth interoperability framework to address public hea.pdf N1 - Export Date: 10 September 2018 References: Kierkegaard, P., Electronic health record: Wiring Europe’s healthcare (2011) Computer Law & Security Review, 27 (5), pp. 503-515; Beerenwinkel, N., Fröhlich, H., Murphy, S., Addressing the Computational Challenges of Personalized Medicine (Dagstuhl Seminar 17472) (2018) Dagstuhl Reports, 7 (11). , Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik; Barbabella, F., Melchiorre, M.G., Quattrini, S., Papa, R., Lamura, G., (2017) How Can eHealth Improve Care for People with Multimorbidity in Europe?, , World Health Organization, Regional Office for Europe; Lamine, E., Guédria, W., Rius Soler, A., Ayza Graells, J., Fontanili, F., Janer‐García, L., Pingaud, H., An inventory of interoperability in healthcare ecosystems: Characterization and challenges (2017) Enterprise Interoperability: INTEROP‐PGSO Vision, 1, pp. 167-198; Hellenic National ePrescription Homepage, , https://www.e-prescription.gr/, last accessed 2018/07/05; Hellenic Unified Insurance Register – Insurance Status Verification Homepage, , https://www.atlas.gov.gr/ATLAS/Pages/Home.aspx, last accessed 2018/07/05; http://www.eopyy.gov.gr, last accessed 2018/07/03; eAppointments Homepage for Citizens, , https://www.e-syntagografisi.gr/p-rv/p, last accessed 2018/07/05; Business Intelligence System of The National Health System (Bi-Health) Homepage, , http://portal.bi.moh.gov.gr/, Ministry of Health: last accessed 2018/07/03; Katehakis, D., Halkiotis, S., Kouroubali, A., Materialization of regional health information networks in Greece: Electronic health record barriers & enablers (2012) Advances in Electronic Health Records, pp. 285-299. , Ming Chyu editor Multi-Science Publishing Company, Texas Tech University, Lubbock, Texas, USA; Katehakis, D., Electronic medical record implementation challenges for the national health system in Greece (2018) International Journal of Reliable and Quality E-Healthcare (IJRQEH), 7 (1), pp. 16-30; Aanestad, M., Grisot, M., Hanseth, O., Vassilakopoulou, P., Information infrastructures for ehealth Information Infrastructures Within European Health Care, , https://doi.org/10.1007/978-3-319-51020-0_2, Aanestad M., Grisot M., Hanseth O., Vassilakopoulou eds Health Informatics. Springer, Cham, last accessed 2018/07/01 2017; The New European Interoperability Framework Homepage, , https://ec.europa.eu/isa2/eif_en, last accessed 2018/06/03; Antilope Homepage, , https://www.antilope-project.eu/, last accessed 2018/06/06; Refined eHealth European Interoperability Framework, , https://ec.europa.eu/health/sites/health/files/ehealth/docs/ev_20151123_co03_en.pdf, last accessed 2018/06/06; eStandards Homepage, , http://www.estandards-project.eu/, last accessed 2018/06/03; Integrating The Healthcare Enterprise Homepage, , http://www.ihe.net/, last accessed 2018/06/03; Health Level Seven International Homepage, , http://www.hl7.org/, last accessed 2018/06/03; Personal Connected Health Alliance Homepage, , http://www.pchalliance.org/, last accessed 2018/06/03; EURO-CAS Homepage, , https://www.euro-cas.eu/, last accessed 2018/06/03; McDonald, K.M., Sundaram, V., Bravata, D., Definitions of care coordination and related terms (2007) Closing The Quality Gap: A Critical Analysis of Quality Improvement Strategies (Vol., 7. , https://www.ncbi.nlm.nih.gov/books/NBK44012/, Care Coordination). Rockville (MD): Agency for Healthcare Research and Quality (US; Jun. (Technical Reviews, 9.7.) 3,: last accessed 2018/07/03; (2012) Report of Hellenic Ministry of Health and Social Solidarity and National Health System Unit Results for 2011 (in Greek), , http://www.moh.gov.gr/articles/hlektronikes-efarmoges-e-sy/1332-ethsia-ekthesh-2011?fdl=4415, Hellenic Ministry of Health and Social Solidarity: Athens last accessed 2018/07/03; http://www.idika.gr/, Homepage, last accessed 2018/07/03; http://www.moh.gov.gr/, Hellenic Ministry of Health Homepage, last accessed 2018/07/03; (2017) The Personal Health Connected Alliance: We Are All in This Together: Advancing eHealth Interoperability, , http://www.cocir.org/fileadmin/Publications_2017/17022_COC_Interoperability_web.pdf, IHE-Europe, May last accessed 2018/07/13 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Modern health systems depend on interaction between several cooperating actors. These include - amongst others - patients, caretakers, general practitioners, health specialists, pharmacies, laboratories, hospitals, clinics, insurance organizations, and research centers, from both public and private sectors. Interoperability of information and communication technology (ICT) systems is central for reliable and efficient collaboration between the involved actors. The purpose of the paper is to present the vision for the development of a national domain interoperability framework (DIF) for eHealth in Greece, within the context of the new European interoperability framework (EIF). The framework must be able to support current and future challenges, as the classical healthcare system is shifting towards early detection and home care monitoring to support personalized care. The objective is for public health in the country to benefit from its application, by setting the ground for making available comparable, clinically significant electronic health record (EHR) data (for both primary and secondary use), and by defining technical specifications for well-defined use cases, in a legitimate and standardized manner. Some relevant research limitations relate to consent management and semantic issues. Practical implications relate to European and country level compatibility, sustainability, as well as the readiness to address the continuously evolving interoperability. It becomes evident that in order to provide services for better citizen care and control over costs, the country has to make certain steps towards applying a national interoperability framework to accelerate transformation for a more sustainable health system. © 2018 CEUR-WS. All rights reserved. ER - TY - JOUR T1 - From scientific discovery to treatments for rare diseases - The view from the National Center for Advancing Translational Sciences - Office of Rare Diseases Research A1 - Kaufmann, P A1 - Pariser, A R A1 - Austin, C Y1 - 2018/// JF - Orphanet Journal of Rare Diseases VL - 13 IS - 1 DO - 10.1186/s13023-018-0936-x N2 - ©2018 The Author(s). We now live in a time of unprecedented opportunities to turn scientific discoveries into better treatments for the estimated 30 million people in the US living with rare diseases. Despite these scientific advances, more than 90% of rare diseases still lack an effective treatment. New data and genetics technologies have resulted in the first transformational new treatments for a handful of rare diseases. This challenges us as a society to accelerate progress so that no disease and no patient is, ultimately, left behind in getting access to safe and effective therapeutics. This article reviews initiatives of the National Center for Advancing Translational Sciences (NCATS) Office of Rare Diseases Research (ORDR) that are aimed at catalyzing rare diseases research. These initiatives fall into two groups: Promoting information sharing; and building multi-disciplinary multi-stakeholder collaborations. Among ORDR's information sharing initiatives are GARD (The Genetics and Rare Diseases Information Center), RaDaR (The Rare Diseases Registries Program) and the NCATS Toolkit for Patient-Focused Therapy Development (Toolkit). Among the collaboration initiatives are the RDCRN (Rare Diseases Clinical Research Network), and the NCATS ORDR support for conferences and workshops. Despite the success of these programs, there remains substantial work to be done to build enhanced collaborations, clinical harmonization and interoperability, and stakeholder engagement so that the recent scientific advances can benefit all patients on the long list of rare diseases waiting for help. ER - TY - CONF T1 - Semantic knowledge for histopathological image analysis: From ontologies to processing portals and deep learning A1 - Kergosien, Y L A1 - Racoceanu, D Y1 - 2017/// KW - Algorithms KW - Artificial intelligence KW - Bioinformatics KW - Challenges KW - Computational/Digital Pathology KW - Convolutional neural network KW - Data handling KW - Deep Learning KW - Deep learning KW - Diagnosis KW - Feedback KW - Grading KW - Histopathological image analysis KW - Humanism KW - Humanities KW - Humans KW - Image Processing Module KW - Image enhancement KW - Image processing KW - Knowledge based systems KW - Knowledge management KW - Learning algorithms KW - Learning systems KW - Medical imaging KW - Multitask learning KW - Network architecture KW - Neural networks KW - Ontology KW - Pathology KW - Semantic Web KW - Semantic Web technology KW - Semantic repository KW - Semantics KW - Semantics/Ontology KW - Sophisticated machines KW - Web services KW - Web-Services KW - Websites VL - 10572 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038428283&doi=10.1117%2F12.2285916&partnerID=40&md5=cf7993dbd67b8a0bfb90957756cd7490 N1 - Cited By :1 Export Date: 10 September 2018 References: Traore, L., A sustainable visual representation of available histopathological digital knowledge for breast cancer grading (2016) Diagnostic Pathology, 2 (1); Traore, L., Kergosien, Y.L., Racoceanu, D., Bridging the semantic gap between diagnostic histopathol-ogy and image analysis (2017) Stud Health Technol Inform., 235, pp. 436-440; Buchanan, B.G., (1984) Rule-based Expert Systems, 3. , Addison-Wesley Reading, MA; Bartels, P., Hiessl, H., Expert systems in histopathology. II. Knowledge representation and rule-based systems (1989) Analytical and Quantitative Cytology and Histology, 11 (3), pp. 147-153; Baader, F., (2003) The Description Logic Handbook: Theory, Implementation and Applications, , Cambridge univ. press; Gruber, T.R., A translation approach to portable ontology specifications (1993) Knowledge Acquisition, 5 (2), pp. 199-220; Guarino, N., What is an ontology? (2009) Handbook on Ontologies, pp. 1-17. , Springer; Studer, R., Benjamins, V.R., Fensel, D., Knowledge engineering: Principles and methods (1998) Data & Knowledge Engineering, 25 (1-2), pp. 161-197; Racoceanu, D., Capron, F., Towards semantic-driven high-content image analysis. An operational in-stantiation for mitosis detection (2015) Computerized Medical Imaging and Graphics, 2, pp. 2-15; Racoceanu, D., Towards efficient collaborative digital pathology: A pioneer initiative of the exmim project (2016) Diagnostic Pathology, 1 (8); Racoceanu, D., Capron, F., Semantic integrative digital pathology: Insights into microsemiological semantics and image analysis scalability (2016) Pathobiology, 83 (2-3), pp. 148-155; Deserno, T.M., Antani, S., Long, R., Ontology of gaps in content-based image retrieval (2009) Journal of Digital Imaging, 22 (2), pp. 202-215; Tutac, A., De Timisoara, U.P., (2010) Formal Representation and Reasoning for Microscopic Medical Image-based Prognosis; Suddarth, S.C., Kergosien, Y.L., (1990) Rule-injection Hints As A Means of Improving Network Performance and Learning Time, pp. 120-129. , Springer Berlin Heidelberg, Berlin, Heidelberg; Caruana, R., (1998) Multitask Learning, pp. 95-133. , Springer US, Boston, MA; Silver, D.L., Mercer, R.E., Hurwitz, G.A., The functional transfer of knowledge for coronary artery disease diagnosis (1997) Tech. Rep., Comput. Sci; Collobert, R., Weston, J., A unified architecture for natural language processing: Deep neural networks with multitask learning (2008) Proceedings of the 25th International Conference on Machine Learning, pp. 160-167. , ICML '08, ACM, New York, NY, USA; Vezhnevets, A., Buhmann, J.M., Towards weakly supervised semantic segmentation by means of multiple instance and multitask learning (2010) 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3249-3256. , IEEE Computer Society RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This article presents our vision about the next generation of challenges in computational/digital pathology. The key role of the domain ontology, developed in a sustainable manner (i.e. using reference checklists and protocols, as the living semantic repositories), opens the way to effective/sustainable traceability and relevance feedback concerning the use of existing machine learning algorithms, proven to be very performant in the latest digital pathology challenges (i.e. convolutional neural networks). Being able to work in an accessible web-service environment, with strictly controlled issues regarding intellectual property (image and data processing/analysis algorithms) and medical data/image confidentiality is essential for the future. Among the web-services involved in the proposed approach, the living yellow pages in the area of computational pathology seems to be very important in order to reach an operational awareness, validation, and feasibility. This represents a very promising way to go to the next generation of tools, able to bring more guidance to the computer scientists and confidence to the pathologists, towards an effective/efficient daily use. Besides, a consistent feedback and insights will be more likely to emerge in the near future - from these sophisticated machine learning tools - back to the pathologists - , strengthening, therefore, the interaction between the different actors of a sustainable biomedical ecosystem (patients, clinicians, biologists, engineers, scientists etc.). Beside going digital/computational - with virtual slide technology demanding new workflows - , Pathology must prepare for another coming revolution: semantic web technologies now enable the knowledge of experts to be stored in databases, shared through the Internet, and accessible by machines. Traceability, disambiguation of reports, quality monitoring, interoperability between health centers are some of the associated benefits that pathologists were seeking. However, major changes are also to be expected for the relation of human diagnosis to machine based procedures. Improving on a former imaging platform which used a local knowledge base and a reasoning engine to combine image processing modules into higher level tasks, we propose a framework where different actors of the histopathology imaging world can cooperate using web services - exchanging knowledge as well as imaging services - and where the results of such collaborations on diagnostic related tasks can be evaluated in international challenges such as those recently organized for mitosis detection, nuclear atypia, or tissue architecture in the context of cancer grading. This framework is likely to offer an effective context-guidance and traceability to Deep Learning approaches, with an interesting promising perspective given by the multi-task learning (MTL) paradigm, distinguished by its applicability to several different learning algorithms, its non- reliance on specialized architectures and the promising results demonstrated, in particular towards the problem of weak supervision - , an issue found when direct links from pathology terms in reports to corresponding regions within images are missing. © 2017 SPIE. ER - TY - CONF T1 - An FHIR-based framework for consolidation of augmented EHR from hospitals for public health analysis A1 - Khalique, F A1 - Khan, S A Y1 - 2019/// JF - 11th IEEE International Conference on Application of Information and Communication Technologies, AICT 2017 - Proceedings SN - 9781538605011 DO - 10.1109/ICAICT.2017.8687289 N2 - ©2017 IEEE. Health Information Exchanges (HIEs) are the infrastructures for sharing health data between providers, patients, health agencies, researchers and other stakeholders. One of the important stakeholders are the public health policy makers or departments that can base their valuable decisions on real time Electronic Health record (EHR) data in addition to traditional surveillance data. Our proposed framework provides support to public health data systems to integrate data from a heterogeneous EHR and other sources, and consolidate them for public health analysis or mining. Models are created for both hospital EHR and FHIR formats and automated transformations are created to convert EHR to Public Health Record (PHR). This framework provides staff in public health departments a consolidated picture of a population's health based on individual EHR and contextual information such as social, economic, environmental and epidemiology elements. Unlike existing frameworks, this research proposes an infrastructure that sends complete longitudinal story of health record of public health interest instead of aggregated information. The framework also obviates the need for a single EHR format to be followed at every participating healthcare facility. This is done through an adapter at each site. This framework provides a comprehensive means of support for public health agencies to identify the determinants of health based on ground truth when considering priority populations and using EHR data and contextual information to focus public health action. ER - TY - JOUR T1 - Personalized-detailed clinical model for data interoperability among clinical standards A1 - Khan, W A A1 - Hussain, M A1 - Afzal, M A1 - Amin, M B A1 - Saleem, M A A1 - Lee, S Y1 - 2013/// KW - Algorithms KW - Alzheimer Disease KW - Alzheimer disease KW - Data-level interoperability KW - Diabetes Mellitus, Type 2 KW - E health KW - Effective utilization of resources KW - Electronic Health Records KW - Electronic health record KW - Health KW - Health Level Seven KW - Health care KW - Health information exchanges KW - Healthcare organizations KW - Humans KW - Information dissemination KW - Information management KW - Interoperability KW - Mapping KW - Medical Record Linkage KW - Medical record KW - Medical records KW - Models, Organizational KW - Neurodegenerative diseases KW - Republic of Korea KW - Semantics KW - Software Design KW - South Korea KW - Standards KW - Systems Integration KW - Technology KW - Type 2 diabetes mellitus KW - algorithm KW - computer program KW - e-health KW - electronic medical record KW - health level 7 KW - human KW - medical record KW - non insulin dependent diabetes mellitus KW - nonbiological model KW - procedures KW - semantics KW - standards KW - system analysis JF - Telemedicine and e-Health VL - 19 IS - 8 SP - 632 EP - 642 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899778383&doi=10.1089%2Ftmj.2012.0189&partnerID=40&md5=49724da5c5ca9c4016593afc7b4c4177 N1 - Cited By :6 Export Date: 10 September 2018 References: Offit, K., Personalized medicine: New genomics, old lessons (2011) Hum Genet, 130, pp. 3-14; (2012) Health information exchange, , http://en.wikipedia.org/wiki/Health_information_exchange, Available at (last accessed March 10; (2012) Health Information Exchange Definition -Defined By Experts, , www.medical-record-coding.com/2011/12/healthinformation-exchange- definition/, Available at last accessed September 14; (2012) Detailed Clinical Model, , www.detailedclinicalmodelsnl/dcm-en, Available at (last accessed September 14; Goossen, W.T., Using detailed clinical models to bridge the gap between clinicians and HIT (2008) Stud Health Technol Inform, 141, pp. 3-10; Parker, C.G., Detailed clinical models for sharable, executable guidelines (2004) Medinfo, 11, pp. 145-148; (2012) Clinical Information Modeling Initiative Goes With Archetypes & UML Profile, , www.openehr.org/news_events/industry_news/20111214, CIMI [Clinical Information Modeling Initiative Available at (last accessed March 2; (2012) CIMI details, , http://wiki.hl7.org/images/9/99/CIMISeeking-Clarity-20120108.pdf, Available at last accessed March 16; (2012) Architecture Overview, , www.openehr.org/releases/1.0.1/, Available at last accessed October 5; Beale, T., Heard, S., Open ehr archetype model (2007) Template Object Model (Tom, , www.openehr.org/releases/1.0.1/architecture/am/tom.pdf, March 13, Available at last accessed March 2 2011; Beale, T., Heard, S., The openEHR archetype model (2007) Archetype definition language ADL, 2. , www.openehr.org/releases/1.0.2/architecture/am/adl2.pdf, March 3, Available at (last accessed March 2 2011; (2009) Draft Standard For Trial Use, , www.cdc.gov/nhsn/PDFs/CDA/CDAR2L3_IG_HAIRPT_R2_D2_2009FEB.pdf, HL7 implementation guide for CDA release 2: NHSN healthcare associated infection (HAI) reports, release 2 (U.S. realm February Available at last accessed October 20 2012; Beeler, G., (2004) HL7 Reference Information Model, , www.interopsante.org/offres/file_inline_src/412/412_P_15660_92.pdf, Available at last accessed October 1 2012; Khan, W.A., Achieving interoperability among healthcare standards: Building semantic mappings at models level (2012) Proceedings Of The 6th International Conference On Ubiquitous Information Management And Communication, p. 101. , New York ACM; Khan, W.A., Hussain, M., Afzal, M., Amin, M.B., Lee, S., Healthcare standards based sensory data exchange for home healthcare monitoring system (2012) Conf Proc IEEE Eng Med Biol Soc, pp. 1274-1277; Freriks, G., Semantic interoperability artefact modelling standard: Clinical information models (2012) Electronic Record Services BV, , www.en13606.org/wiki/images/1/1c/ERS_SIAMS_%28most_recent_version%29.pdf, July 29 Available at (last accessed November 25, 2012; Bosca, D., Maldonado, J.A., Moner, D., Robles, M., Detailed clinical models to facilitate interstandard interoperability of data types (2011) 23rd International Conference of the European Federation for Medical Informatics, , Oslo, Norway: European Federation for Medical Informatics; Dogac, A., Artemis: Deploying semantically enriched web services in the healthcare domain (2006) Inf Systems, 31, pp. 321-339; Sahay, R., A methodological approach for ontologising and aligning health level seven (hl7) applications (2011) Availability Reliability And Security For Business Enterprise And Health Information Systems, pp. 102-117. , Berlin Springer; Maldonado, J.A., Linkehr-ed: A multi-reference model archetype editor based on formal semantics (2009) Int J Med Inform, 78, pp. 559-570; Kilic, O., Dogac, A., Achieving clinical statement interoperability using R-MIM and archetype-based semantic transformations (2009) IEEE Trans Inf Technol Biomed, 13, pp. 467-477; Martínez Costa, C., Menárguez-Tortosa, M., Fernández- Breis, J.T., Clinical data interoperability based on archetype transformation (2011) J Biomed Inform, 44, pp. 869-880; (2012) Poseacle Converter, , http://miuras.inf.um.es9080/PoseacleConverter, Available at (last accessed March 2; Khan, W.A., Hussain, M., Latif, K., Afzal, M., Ahmad, F., Lee, S., Process interoperability in healthcare systems with dynamic semantic web services (2013) Computing, pp. 1-26. , http://link.springer.com/article/10.1007/s00607-012-0239-3/fulltext.html, Available at (last accessed February 25 2013; Galarraga, M., Serrano, L., Martinez, I., De Toledo, P., Reynolds, M., Telemonitoring systems interoperability challenge: An updated review of the applicability of iso/ieee 11073 standards for interoperability in telemonitoring (2007) Engineering in Medicine and Biology Society 2007. EMBS 2007. 29th Annual International Conference of the IEEE, pp. 6161-6165. , Piscataway, NJ: IEEE; Lee, M., Gatton, T.M., Wireless health data exchange for home healthcare monitoring systems (2010) Sensors, 10, pp. 3243-3260; Khattak, A.M., Truc, P.T.H., Hung, L.X., Dang, V.-H., Guan, D., Pervez, Z., Han, M., Lee, Y.-K., Towards smart homes using low level sensory data (2011) Sensors, 11, pp. 11581-11604 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalized-detailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems. Materials and Methods: We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards. Results: For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts. Conclusions: The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems. © Mary Ann Liebert, Inc. ER - TY - JOUR T1 - A proposed national research and development agenda for population health informatics: Summary recommendations from a national expert workshop A1 - Kharrazi, H A1 - Lasser, E C A1 - AYasnoff, W A1 - Loonsk, J A1 - Advani, A A1 - P Lehmann, Harold A1 - Chin, D C A1 - Weiner, J P Y1 - 2017/// KW - Developing Countries KW - Health Policy KW - Health Services Research KW - Humans KW - Informatics KW - Informatics agenda KW - Medical Informatics KW - Population Health KW - Population health informatics KW - Public health informatics KW - United States KW - brainstorming KW - consensus KW - health care management KW - health care policy KW - health services research KW - human KW - instrument validation KW - knowledge base KW - medical informatics KW - monitoring KW - population health KW - privacy KW - procedures KW - publication KW - standards JF - Journal of the American Medical Informatics Association VL - 24 IS - 1 SP - 2 EP - 12 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Kharrazi et al. - 2017 - A proposed national research and development agenda for population health informatics Summary recommendations f.pdf N1 - Cited By :6 Export Date: 10 September 2018 References: Charles, D., Gabriel, M., Furukawa, M., Adoption of Electronic Health Record Systems among U.S. Non-federal Acute Care Hospitals: 2008-2013 (2014) Office of National Coordinator for Health Information Technology, , https://www.healthit.gov/sites/default/files/oncdatabrief16.pdf, Accessed March 4, 2013; Charles, D., King, J., Furukawa, M.F., Patel, V., Hospital adoption of electronic health record technology to meet meaningful use objectives: 2008-2012 (2013) Office of the National Coordinator for Health Information Technology, , http://www.healthit.gov/sites/default/files/oncdatabrief10final.pdf, Accessed March 2, 2013; Jha, A., Burke, M., DesRoches, C., Progress toward meaningful use: hospitals' adoption of electronic health records (2011) Am J Managed Care., 17 (12), pp. SP117-SP124. , Spec No; Hsiao, C.J., Hing, E., Ashman, J., Trends in Electronic Health Record system use among office-based physicians: United States, 2007-2012 (2014) National Center for Health Statistics, , http://www.cdc.gov/nchs/data/nhsr/nhsr075.pdf, Accessed September 20, 2014; Friedman, D.G., Parrish, G.R., The population health record: concepts, definition, design, and implementation (2010) J Am Med Inform Assoc., 17, pp. 359-366; Kharrazi, H., Weiner, J., IT-enabled community health interventions: challenges, opportunities, and future directions (2014) eGEMs., 2 (3), pp. 1-8; McKethan, A., Brammer, C., Fatemi, P., An early status report on the Beacon Communities' plans for transformation via health information technology (2011) Health Affairs., 30 (4), pp. 782-788; Schachter, A., Rein, A., Sabharwal, R., Beacon policy brief: building a foundation of electronic data to measure and drive improvement (2013) Office Natl Coordinator, , http://www.healthit.gov/sites/default/files/beacon_quality_measurement_brief_final_14aug13.pdf, Accessed September 20, 2014; (2013) About CPHIT, , http://www.jhsph.edu/research/centers-and-institutes/johns-hopkins-center-forpopulation-health-information-technology/about-us.html, Accessed January 2; Setting a National RandD Agenda for Population Health Informatics: An Invited Expert Symposium (2014), http://www.jhsph.edu/research/centersand-institutes/johns-hopkins-center-for-population-health-informationtechnology/_documents/JHU-Pop-Health-Info-RD-32714-Symposium-Program.pdf, Mar. Accessed January 10, 2015; Kindig, D.A., Asada, Y., Booske, B., A Population Health Framework for Setting National and State Health Goals (2008) J Am Med Assoc., 299 (17), pp. 2081-2083; Stoto, M., Population Health Measurement: applying performance measurement concepts in population health settings (2014) eGEMs., 2 (4), pp. 1-27; (2009) The Patient Protection and Affordable Care Act, , http://www.gpo.gov/fdsys/pkg/BILLS-111hr3590enr/pdf/BILLS-111hr3590enr.pdf, Accessed January 12, 2013; Act Title XIII of Division A and Title IV of Division B of the American Recovery and Reinvestment Act of (2009), https://www.gpo.gov/fdsys/pkg/PLAW-111publ5/pdf/PLAW-111publ5.pdf, ARRA Washington DC: 111th Congress; 2009; (2015) H.R.2 -Medicare Access and CHIP Reauthorization Act of 2015, , Washington DC: 114th Congress; Kindig, D., Stoddart, G., What is population health? (2003) Am J Public Health., 93 (3), pp. 380-383; Kukafka, R., Ancker, J.S., Chan, C., Redesigning electronic health record systems to support public health (2007) J Biomed Inform., 40, pp. 389-409; Montero, J.T., Terrillion, A., Reintegrating health care and public health: a population health imperative (2013) J PublicHealth Manag Pract., 19 (5), pp. 493-496; (1994) Institute ofMedicine. Defining Primary Care, , An Interim Report. Washington:National Academy Press; Turoff, M., HALinstone, MTuroff The Delphi Method: Techniques and Applications (2002) The Policy Delphi, pp. 80-96. , Newark: New Jersey Institute of Technology; Rayens, M.K., Hahn, E.J., Building consensus using the Policy Delphi method (2000) Policy, Polit Nurs Pract., 1 (4), pp. 308-315; Osborn, A.F., (1963) Applied Imagination: Principles and Procedures of Creative Problem Solving, , New York: Charles Scribner's Sons; Egan, M.T., Grounded theory research and theory building (2002) Adv Dev Hum Resour., 4 (3), pp. 277-295; Goulding, C., Grounded Theory: A Practical Guide for Management (2005) Business and Market Researchers, , 2nd edn. London: SAGE publications; Moreno, L., Peikes, D., Krilla, A., Necessary but not sufficient: The HITECH act and health information technology's potential to build medical homes (2010), http://pcmh.ahrq.gov/portal/server.pt/gateway/PTARGS_0_11787_950288_0_0_18/HITECHWhitePaper-8.10.2010withnewcover.pdf, Accessed July 2, 2013; Massoudi, B.L., Goodman, K.W., Gotham, I.J., An informatics agenda for public health: summarized recommendations from the 2011 AMIA PHI Conference (2012) J Am Med Inform Assoc., 19, pp. 688-695; Yasnoff, W.A., O'Carroll, P.W., Koo, D., Linkins, R.W., Kilbourne, E.M., Public Health Informatics: Improving and Transforming Public Health in the Information Age (2000) J Public Health Manag Practice., 6 (6), pp. 67-75; Yasnoff, W.A., Overhage, J.M., Humphreys, B.L., Laventure, M., A National Agenda for Public Health Informatics: Summarized Recommendations from the 2001 AMIA Spring Congress (2001) J Am Med Inform Assoc., 8 (6), pp. 535-545; McCarthy, D., Klein, S., The triple aim journey: improving population health and patients' experience of care, while reducing costs (2010) The Commonwealth Fund, , http://www.commonwealthfund.org/Publications/Case-Studies/2010/Jul/Triple-Aim-Improving-Population-Health.aspx, Accessed July 2, 2013; Fisher, E., Shortell, S., Kreindler, S., Van Citters, A., Larson, B., A framework for evaluating the formation, implementation, and performance of Accountable CareOrganizations (2012) Health Affairs., 31 (11), pp. 2368-2378; Fisher, E., Staiger, D., Bynum, J., Gottlieb, D., Creating accountable care organizations: the extended hospital medical staff (2007) Health Affairs., 26 (1), pp. w44-w57; (2012) Defining the PCMH, , http://www.pcmh.ahrq.gov/portal/server.pt/community/pcmh__home/1483/pcmh_defining_the_pcmh_v2, Accessed July 2, 2013; Hospital Adoption of Electronic Health Record Technology to Meet Meaningful Use Objectives: 2008-2012 (2013), http://www.healthit.gov/sites/default/files/oncdatabrief10final.pdf, Accessed March 10, 2013; Health information technology: Standards, implementation specifications, and certification criteria for electronic health record technology, 2014 edition (2012) Fed Regist., 77 (171), pp. 53968-54162; http://www.hl7.org/about/index.cfm, Accessed February 9, 2015; CDISC Vision and Mission, , http://www.cdisc.org/CDISC-Vision-and-Mission, Accessed February 9, 2015; (2015) What is the SandI Framework?, , http://www.siframework.org/whatis.html, Accessed January 14; (2015) About PCORnet, , http://www.pcornet.org/about-pcornet/, Accessed February 12; (2014) The Basics of All-Payer Claims Databases: A Primer for States, , http://apcdcouncil.org/sites/apcdcouncil.org/files/The%20Basics%20of%20All-Payer%20Claims%20Databases.pdf, Accessed January 22, 2015; Barrett, M.A., Humblet, O., Hiatt, R.A., Adler, N.E., Big Data and disease prevention: From quantified self to quantified communities (2013) J Big Data., 1 (3), pp. 168-175; Feldman, B., Martin, E.M., Skotnes, T., (2012) Big Data in Healthcare Hype and Hope, , http://www.west-info.eu/files/big-data-in-healthcare.pdf2013, August 13, 2013; Public Health Informatics Workgroup. Public Health Informatics, , https://www.amia.org/programs/working-groups/public-health-informatics, Accessed March 19, 2015; Information Technology Professionals in Health Care: Workforce Training to Educate Health Care Professionals in Health Information Technology http://healthit.gov/sites/default/files/workforcefoa1292015.pdf, Accessed March 20, 2015UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85014761330&doi=10.1093%2fjamia%2focv210&partnerID=40&md5=38d1996f162a76074f4d5b8934c819fc RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: The Johns Hopkins Center for Population Health IT hosted a 1-day symposium sponsored by the National Library of Medicine to help develop a national research and development (R and D) agenda for the emerging field of population health informatics (PopHI). Material and Methods: The symposium provided a venue for national experts to brainstorm, identify, discuss, and prioritize the top challenges and opportunities in the PopHI field, as well as R and D areas to address these. Results: This manuscript summarizes the findings of the PopHI symposium. The symposium participants' recommendations have been categorized into 13 overarching themes, including policy alignment, data governance, sustainability and incentives, and standards/interoperability. Discussion: The proposed consensus-based national agenda for PopHI consisted of 18 priority recommendations grouped into 4 broad goals: (1) Developing a standardized collaborative framework and infrastructure, (2) Advancing technical tools and methods, (3) Developing a scientific evidence and knowledge base, and (4) Developing an appropriate framework for policy, privacy, and sustainability. There was a substantial amount of agreement between all the participants on the challenges and opportunities for PopHI as well as on the actions that needed to be taken to address these. Conclusion: PopHI is a rapidly growing field that has emerged to address the population dimension of the Triple Aim. The proposed PopHI R and D agenda is comprehensive and timely, but should be considered only a startingpoint, given that ongoing developments in health policy, population health management, and informatics are very dynamic, suggesting that the agenda will require constant monitoring and updating. © The Author 2016. ER - TY - JOUR T1 - Interoperability after deployment: Persistent challenges and regional strategies in Denmark A1 - Kierkegaard, P Y1 - 2015/// KW - Article KW - Denmark KW - Electronic health records KW - European Union KW - Federal Government KW - Health information exchange KW - Hospital Information Systems KW - Hospital care KW - Humans KW - Implementation governance KW - Interoperability KW - Regional Medical Programs KW - electronic medical record KW - health care organization KW - health care personnel KW - health care planning KW - health care quality KW - health service KW - hospital information system KW - hospital management KW - hospital planning KW - human KW - medical information system KW - organization and management KW - priority journal KW - standards KW - telemedicine JF - International Journal for Quality in Health Care VL - 27 LA - English IS - 2 SP - 147 EP - 153 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929751107&doi=10.1093%2Fintqhc%2Fmzv009&partnerID=40&md5=4dcfa43159df35de92e8cfd4f1f64183 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Kierkegaard - 2015 - Interoperability after deployment Persistent challenges and regional strategies in Denmark.pdf N1 - Ehealth AND governance Cited By :6 Export Date: 10 September 2018 References: Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: eHealth Action Plan 2012-2020-Innovative healthcare for the 21st century (2012), Brussels: European Commission; eHealth>Key documents: Directorate General Health & Consumers (2014), http://ec.europa.eu/health/ehealth/key_documents/index_en.htm?Page=1, 27 October, date last accessed; Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: A Digital Agenda for Europe (2010), Brussels: European Commission; Buntin, M.B., Burke, M.F., Hoaglin, M.C., The benefits of health information technology: a review of the recent literature shows predominantly positive results (2011) Health Affairs, 30, pp. 464-471; Goldzweig, C.L., Towfigh, A., Maglione, M., Costs and benefits of health information technology: new trends from the literature (2009) Health Affairs, 28, pp. w282-w293; Zlabek, J.A., Wickus, J.W., Mathiason, M.A., Early cost and safety benefits of an inpatient electronic health record (2011) J Am Med Inform Assoc, 18, pp. 169-172; Dobrev, A., Jones, T., Stroetmann, V., Interoperable eHealth is worth it: securing benefits from electronic health records and ePrescribing (2010), Bonn/Brussels: European Commission; Action 77: Foster EU-wide standards, interoperability testing and certification of eHealth: Digital Agenda for Europe (2014), http://ec.europa.eu/digital-agenda/en/pillar-vii-ict-enabled-benefits-eu-society/action-77-foster-eu-wide-standardsinteroperability, 1 November, date last accessed; Mur-Veeman, I., Van Raak, A., Paulus, A., Comparing integrated care policy in Europe: does policy matter? (2008) Health Policy, 85, pp. 172-183; Adler-Milstein, J., Ronchi, E., Cohen, G.R., Benchmarking health IT among OECD countries: better data for better policy (2014) J Am Med Inform Assoc, 21, pp. 111-116; Overview of the national laws on electronic health records in the EU Member States and their interaction with the provision of cross-border eHealth services: final report and recommendations Brussels: 2013 Contract 2013 63 02; (2010) Atlas EHealth Country Pro, , http://www.who.int/goe/publications/ehealth_series_vol1/en/, Geneva: World Health Organization; eHealth Task Force Report -Redesigning health in Europe for 2020 (2012), Luxembourg: Publications Office of the European Union: European Commission; Deidda, M., Lupiáñez-Villanueva, F., Maghiros, I., European Hospital Survey: Benchmarking Deployment of e-Health Services (2012-2013) (2013), European Commission-Joint Research Centre Institute for Prospective Technological Studies; Protti, D., Johansen, I., Widespread adoption of information technology in primary care physician offices in Denmark: a case study (2010) Issue Brief (Commonwealth Fund), 80, pp. 1-14; Villalba, E., Casas, I., Abadie, F., Integrated personal health and care services deployment: experiences in eight European countries (2013) Int J Med Inform, 82, pp. 626-635; Lluch, M., Abadie, F., Exploring the role of ICT in the provision of integrated care-evidence from eight countries (2013) Health Policy, 111, pp. 1-13; Coogan, S., (2013) Læger: It-fejl bringer syge i fare, , Politiken., 29 December, 2013; Ny undersøgelse: Sygehusenes it-løsninger er for dårlige (2012), http://www.laeger.dk/portal/page/portal/LAEGERDK/Laegerdk/Nyheder?public_visningsType=1&public_nyhedsId=78942, Copenhagen: Lægeforeningen, updated 27. April 2012; cited 29 October; Tornbjerg, K., Nøhr, C., Undersøgelse af klinisk anvendelse af sundheds-it-systemer 2013 (2013), Virtuelt Center for Sundhedsinformatik; Olejaz, M., Juul, A., Rudkjøbing, A., Denmark: Health system review: health systems in transition (2012), WHO, on behalf of the European Observatory for Health Systems and policies; Kierkegaard, P., eHealth in Denmark: a case study (2013) J Med Syst, 37, pp. 1-10; Beretning til Statsrevisorerne om elektroniske patientjournaler på sygehusene (2011), Copenhagen: Rigsrevisionen; Statens ansvar for epj (2011), http://www.regioner.dk/aktuelt/temaer/fakta+om+regionernes+effektivitet+og+%C3%B8konomi/statens+ansvar+for+epj, Danske Regioner, 27 October, date last accessed; Kierkegaard, P., Governance structures impact on eHealth (2015) Health Policy Technol, 4, pp. 39-46; Rahbek, N.J., E-record-access to all Danish Public Health records (2012) Stud Health Technol Inform, 192, p. 1121; Notat til Statsrevisorerne om beretning om elektroniske patientjournaler på sygehusene (2014), http://www.rigsrevisionen.dk/media/2010103/411-14.pdf, Copenhagen: Rigsrevisionen; Beretning til Statsrevisorerne om problemerne med at udvikle og implementere Fælles Medicinkort (2014), Copenhagen: Rigsrevisionen; Greenhalgh, T., Morris, L., Wyatt, J.C., Introducing a nationally shared electronic patient record: Case study comparison of Scotland, England, Wales and Northern Ireland (2013) Int J Med Inform, 82, pp. e125-e138; Adler-Milstein, J., Bates, D.W., Jha, A.K., A survey of health information exchange organizations in the United States: implications for meaningful use (2011) Ann Int Med, 154, pp. 666-671; Kellermann, A.L., Jones, S.S., What it will take to achieve the as-yet-unfulfilled promises of health information technology (2013) Health Affairs, 32, pp. 63-68; Ellig, J., (2001) Dynamic Competition and Public Policy: Technology, Innovation, and Antitrust Issues, , UK: Cambridge University Press; eHealth European Interoperability Framework 2013 14/02/2013 Report No.: Specific contract No 60, Framework contract No DI/06691-00; Guidelines on minimum/nonexhaustive patient summary dataset for electronic exchange in accordance with the cross-border Directive 2011/24/eu (2013), 1.0 ed: eHealth Network; Bowden, T., Coiera, E., Comparing New Zealand's 'Middle Out' health information technology strategy with other OECD nations (2013) Int J Med Inform, 82, pp. e87-95 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: EHR N2 - Quality problem or issue: The European Union has identified Denmark as one of the countries who have the potential to provide leadership and inspiration for other countries in eHealth implementation and adoption. However, Denmark has historically struggled to facilitate data exchange between their public hospitals' electronic health records (EHRs). Furthermore, state-led projects failed to adequately address the challenges of interoperability after deployment. Choice of solution: Changes in the organizational setup and division of responsibilities concerning the future of eHealth implementations in hospitals took place, which granted the Danish regions the full responsibility for all hospital systems, specifically the consolidation of EHRs to one system per region. Implementation: The regions reduced the number of different EHRs to six systems by 2014. Additionally, the first version of the National Health Record was launched to provide health care practitioners with an overview of a patient's data stored in all EHRs across the regions and within the various health sectors. Evaluation: The governance of national eHealth implementation plays a crucial role in the development and diffusion of interoperable technologies. Changes in the organizational setup and redistribution of responsibilities between the Danish regions and the state play a pivotal role in producing viable and coherent solutions in a timely manner. Lessons learned: Interoperability initiatives are best managed on a regional level or by the authorities responsible for the provision of local health care services. Cross-regional communication is essential during the initial phases of planning in order to set a common goal for countrywide harmonization, coherence and collaboration. © The Author 2015. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved. ER - TY - JOUR T1 - A sustainable solution for the activities of the European network for surveillance of congenital anomalies: EUROCAT as part of the EU Platform on Rare Diseases Registration A1 - Kinsner-Ovaskainen, A A1 - Lanzoni, M A1 - Garne, E A1 - Loane, M A1 - Morris, J A1 - Neville, A A1 - Nicholl, C A1 - Rankin, J A1 - Rissmann, A A1 - Tucker, D A1 - Tucker, D A1 - Martin, S Y1 - 2018/// JF - European Journal of Medical Genetics VL - 61 IS - 9 SP - 513 EP - 517 DO - 10.1016/j.ejmg.2018.03.008 N2 - ©2018 The Authors The European Commission through its Directorates-General Joint Research Centre (DG JRC) and Health and Food Safety (DG SANTE) is developing the European Platform on Rare Diseases Registration (EU RD Platform) with the objective to set European-level standards for data collection and data sharing. In the field of rare diseases the EU RD Platform will be a source of information on available rare disease patient data with large transnational European coverage. One main function of the EU RD Platform is to enable interoperability for the >600 existing RD registries in Europe. The second function is to offer a sustainable solution for two large European surveillance networks: European Surveillance of Congenital Anomalies (EUROCAT) and Surveillance of Cerebral Palsy in Europe (SCPE). EUROCAT is European network of population-based registries for the epidemiological surveillance of congenital anomalies. It covers about one third of the European birth population. The Central Database contains about 800,000 cases with congenital anomalies among livebirths, stillbirths and terminations of pregnancy, reported using the same standardised classification and coding. These high quality data enables epidemiological surveillance of congenital anomalies, which includes estimating prevalence, prenatal diagnosis and perinatal mortality rates and the detection of teratogenic exposures among others. The network also develops recommendations for primary prevention in the Rare Diseases National Plans for medicinal drugs, food/nutrition, lifestyle, health services, and environmental pollution. The network has received the European Commission's support since its inception. In order to offer a sustainable solution for the continuation of EUROCAT activities, it was agreed that EUROCAT would become part of the EU RD Platform. In 2015, the European level-coordination activities and the Central Database were transferred to the DG JRC, where the JRC-EUROCAT Central Registry is now located. This paper describes the functioning of EUROCAT in the new setting, and gives an overview of the activities and the organisation of the JRC-EUROCAT Central Registry. ER - TY - SER T1 - Matching Ontologies to HL7 FHIR Towards Their Syntactic and Semantic Similarity A1 - Kiourtis, A A1 - Mavrogiorgou, A A1 - Kyriazis, D Y1 - 2018/// KW - HL7 FHIR KW - Healthcare interoperability KW - adult KW - article KW - human KW - medical terminology KW - ontologies KW - ontology KW - ontology matching KW - patient care JF - Studies in Health Technology and Informatics VL - 251 SP - 51 EP - 54 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049584848&doi=10.3233%2F978-1-61499-880-8-51&partnerID=40&md5=7fc1212609875f52ccf909979bf544b8 N1 - Export Date: 10 September 2018 References: Big Data Will Make A Big Difference in Saving Lives, , https://www.linkedin.com/pulse/big-data-makedifference-saving-lives-pete-ianace; Iroju, O., Soriyan, A., Gambo, I., Ontology matching: An ultimate solution for semantic interoperability in healthcare (2012) International Journal of Computer Applications, 51 (21), pp. 7-14; How Big Data and Ontology Will Improve Healthcare, , https://www.nomagic.com/news/insights/howbig-data-and-ontology-will-improve-healthcare; Koshti, M., Ganorkar, S., Chiari, L., IoT based health monitoring system by using raspberry pi and ECG signal (2016) Journal of Innovative Research in Science, Engineering and Technology, 5 (5), pp. 8977-8985; Kalra, M., Lal, N., Data mining of heterogeneous data with research challenges (2016) IEEE Colossal Data Analysis and Networking, pp. 1-6; FHIR Linked Data Module, , https://www.hl7.org/fhir/linked-data-module.html; Andrea, R., Egenhofer, M., Determining semantic similarity among entity classes from different ontologies (2003) IEEE Transactions on Knowledge and Data Engineering, 15 (2), pp. 442-456; BioAssist-Technology Assisted Intendent Living, , https://bioassist.gr RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Current medical systems need to be able to communicate complex and detailed medical data securely and efficiently. However, the quantity of available healthcare data is rising rapidly, far exceeding the capacity to deliver personal or public health benefits from analyzing this data. Thus, a substantial overhaul of methodology is required to address the real complexity of health. This can be achieved by constructing medical domain ontologies for representing medical terminologies, considered to be a difficult task, requiring a profound analysis of the structure and the concepts of medical terminologies. In this paper, a mechanism is presented for constructing healthcare ontologies, while matching them to HL7 FHIR Resources ontologies both in terms of syntactic and semantic similarity, in order to understand their nature and translate them into a common standard to improve the quality of patient care, research, and health service management. © 2018 The authors and IOS Press. All rights reserved. ER - TY - JOUR T1 - Supporting Multi-sourced Medication Information in i2b2 A1 - Klann, J G A1 - Pfiffner, P B A1 - Natter, M D A1 - Conner, E A1 - Blazejewski, P A1 - Murphy, S N A1 - Mandl, K D Y1 - 2015/// KW - Biomedical Research KW - Electronic Health Records KW - Health Information Interoperability KW - Humans KW - Information Storage and Retrieval KW - Pharmacies KW - Product Surveillance, Postmarketing KW - Programming Languages KW - Research Design KW - Software KW - computer language KW - data interoperability KW - electronic health record KW - human KW - information retrieval KW - medical research KW - pharmacy KW - postmarketing surveillance KW - procedures KW - software JF - AMIA ... Annual Symposium proceedings. AMIA Symposium VL - 2015 SP - 747 EP - 755 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041000219&partnerID=40&md5=5ef3a409880acd4997a980e0b7b9858e N1 - Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Postmarketing drug surveillance is critical to assessing adverse events associated with medications, because prelaunch clinical trials frequently miss negative drug effects. The Informatics for Integrating Biology and the Bedside platform (i2b2) has been used effectively for this. However, previous work suffers from incomplete medical data present in electronic health record (EHR) systems. Here, we develop a system to integrate non-traditional data sources with EHR data: pharmacy dispensing information and patient-reported data. We implement and validate a toolset to gather medication data from a Pharmacy Benefit Manager network, import it into an i2b2 EHR repository using a standard data format, merge it with the EHR data, and present it to for annotation with results returned to i2b2. This toolkit is enabling studies on medication list data quality, adherence, and adverse event detection. ER - TY - JOUR T1 - Query Health: standards-based, cross-platform population health surveillance A1 - Klann, J. G. A1 - Buck, M. D. A1 - Brown, J. A1 - Hadley, M. A1 - Elmore, R. A1 - Weber, G. M. A1 - Murphy, S. N. Y1 - 2014/07// PB - Oxford University Press JF - Journal of the American Medical Informatics Association VL - 21 IS - 4 SP - 650 EP - 656 DO - 10.1136/amiajnl-2014-002707 UR - https://academic.oup.com/jamia/article-lookup/doi/10.1136/amiajnl-2014-002707 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Klann et al. - 2014 - Query Health standards-based, cross-platform population health surveillance.pdf ER - TY - JOUR T1 - A standards-based solution for public health reporting and surveillance. A1 - Knoop, S E A1 - Ram, R A1 - Renly, S R Y1 - 2007/// KW - Humans KW - Population Surveillance KW - Public Health Informatics KW - Regional Health Planning KW - Systems Integration KW - article KW - health care planning KW - health survey KW - human KW - medical informatics KW - methodology KW - standard KW - system analysis JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium SP - 1014 EP - 1014 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-56149103308&partnerID=40&md5=2a1e3828d42d2ab8df314afcc50c45ff N1 - Export Date: 5 April 2018 N2 - Our team built a standards-based prototype system for multi-national public health reporting and surveillance. It uses interoperability specifications from Integrating the Healthcare Enterprise (IHE) and open source technologies from Eclipse OHF. Public health organizations leveraging interoperability standards implemented within the clinical domain will have the most standardized data ever achieved; allowing them to focus attention on creating new tools to better visualize population health, detect outbreaks, determine policy effectiveness, and perform forecast modeling. ER - TY - CONF T1 - A semantically-aided architecture for a web-based monitoring system for carotid atherosclerosis A1 - Kolias, V D A1 - Stamou, G A1 - Golemati, S A1 - Stoitsis, G A1 - Gkekas, C D A1 - Liapis, C D A1 - Nikita, K S Y1 - 2015/// KW - Acquired Immunodeficiency Syndrome KW - Architecture KW - Carotid Artery Diseases KW - Humans KW - Information Storage and Retrieval KW - Internet KW - Semantics KW - architecture KW - carotid artery disease KW - human KW - information retrieval KW - semantics VL - 2015 SP - 1373 EP - 1376 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953264151&doi=10.1109%2FEMBC.2015.7318624&partnerID=40&md5=fae0f5139cb06e846c8fed851b2df34c N1 - Export Date: 10 September 2018 References: Stoitsis, J., Golemati, S., Nikita, K.S., A modular software system to assist interpretation of medical images&application to vascular ultrasound images (2006) IEEE Trans. Instrum. Meas, 55, pp. 1944-1952; Ioakim, G., Kyriacou, E., Sofokleous, A.A., Chistodoulou, C., Pattichis, C.S., An MPEG-7 image retrieval system of atherosclerotic carotid plaque images (2012) Bioinformatics & Bioengineering (BIBE), 2012 IEEE 12th International Conference on, pp. 512-516; Kyriazos, G., Gerostathopoulos, I., Kolias, V., Stoitsis, J., Nikita, K., A semantically-aided approach for online annotation and retrieval of medical images (2011) Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pp. 2372-2375; Möller, M., Regel, S., Sintek, M., Radsem: Semantic annotation and retrieval for medical images (2009) The Semantic Web: Research and Applications, pp. 21-35. , ed: Springer; Gastounioti, A., Kolias, V., Golemati, S., Tsiaparas, N.N., Matsakou, A., Stoitsis, J.S., CAROTID-A web-based platform for optimal personalized management of atherosclerotic patients (2014) Comput Meth Prog Bio, 114, pp. 183-193; Doulaverakis, C., Papadogiorgaki, M., Mezaris, V., Billis, A., Parissi, E., Kompatsiaris, I., IVUS image processing and semantic analysis for Cardiovascular Diseases risk prediction (2010) Int J Biomed Eng Technol, 3, pp. 349-374; Chortaras, A., Trivela, D., Stamou, G., Optimized query rewriting for OWL 2 QL (2011) Automated Deduction-CADE-23, pp. 192-206. , ed: Springer; Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C., Owl 2 web ontology language: Profiles (2009) W3C Recommendation, 27, p. 61; Gruber, T.R., A translation approach to portable ontology specifications (1993) Knowledge Acquisition, 5, pp. 199-220; Hare, J.S., Lewis, P.H., Enser, P.G.B., Sandom, C.J., Mind the gap: Another look at the problem of the semantic gap in image retrieval (2006) Electronic Imaging 2006, pp. 607309-60730912 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Carotid atherosclerosis is a multifactorial disease and its clinical diagnosis depends on the evaluation of heterogeneous clinical data, such as imaging exams, biochemical tests and the patient's clinical history. The lack of interoperability between Health Information Systems (HIS) does not allow the physicians to acquire all the necessary data for the diagnostic process. In this paper, a semantically-aided architecture is proposed for a web-based monitoring system for carotid atherosclerosis that is able to gather and unify heterogeneous data with the use of an ontology and to create a common interface for data access enhancing the interoperability of HIS. The architecture is based on an application ontology of carotid atherosclerosis that is used to (a) integrate heterogeneous data sources on the basis of semantic representation and ontological reasoning and (b) access the critical information using SPARQL query rewriting and ontology-based data access services. The architecture was tested over a carotid atherosclerosis dataset consisting of the imaging exams and the clinical profile of 233 patients, using a set of complex queries, constructed by the physicians. The proposed architecture was evaluated with respect to the complexity of the queries that the physicians could make and the retrieval speed. The proposed architecture gave promising results in terms of interoperability, data integration of heterogeneous sources with an ontological way and expanded capabilities of query and retrieval in HIS. © 2015 IEEE. ER - TY - BOOK T1 - Preliminary assessment of the interoperability maturity of healthcare digital services vs public services of other sectors A1 - Kouroubali, A A1 - Papastilianou, A A1 - Katehakis, D G Y1 - 2019/// JF - Studies in Health Technology and Informatics VL - 264 SP - 654 EP - 658 SN - 9781643680026 DO - 10.3233/SHTI190304 N2 - ©2019 International Medical Informatics Association (IMIA) and IOS Press. The development of electronic services for healthcare presents challenges related to the effective cooperation of systems and stakeholders in a highly regulated environment. Assessing the interoperability maturity of the provided services helps to identify interoperability issues in public administration. This paper presents a typical healthcare digital service: the inpatient admission in a public hospital in Greece. The Interoperability Maturity Model (IMM) is applied to assess its maturity, identify improvement priorities, and compare it with digital services of the healthcare sector. An analysis is also performed to compare a group of fourteen healthcare digital public services with sixty-seven public services of other sectors in the country. The IMM is a useful tool to facilitate awareness raising and priority setting concerning interoperability in public administration. What is discovered, through this preliminary assessment, is that healthcare digital services seem to have higher overall interoperability maturity than those of other sectors in Greece. ER - TY - CONF T1 - Leveraging post-marketing drug safety research through semantic technologies: The pharmacovigilance signal detectors ontology A1 - Koutkias, V A1 - Jaulent, M.-C. Y1 - 2014/// KW - Commerce KW - Computation theory KW - Computational signal detection KW - Data integration KW - Detection methods KW - Drug Monitoring KW - Drug products KW - Health risks KW - Heterogeneous data sources KW - Information sources KW - Knowledge based systems KW - Marketing KW - Ontologies KW - Ontology KW - Patient monitoring KW - Pharmacovigilance KW - Public health issues KW - Public risks KW - Semantic Web KW - Semantic integration KW - Semantic technologies KW - Semantics KW - Signal detection KW - Timely identification VL - 1320 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920019902&partnerID=40&md5=a8ac24d893e8c6f936cd9ab7093d1c2c N1 - Cited By :1 Export Date: 5 April 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Accurate and timely identification of post-marketing drug safety risks (the so-called "signals" in pharmacovigilance) is an important public health issue. While various computational methods have been proposed to analyze the diverse data sources employed for signal detection, still the challenge of effective drug monitoring and surveillance remains. On the other hand, there is an emerging belief that the synthesis of all possible information sources is necessary to achieve further advancements. Aiming to facilitate integrated signal detection by concurrently exploring various data sources via respective analysis methods in a systematic way, we propose the PharmacoVigilance Signal Detectors Ontology (PV-SDO). PV-SDO constitutes the backbone of a semantically-enriched platform for this integration and aims to: (a) semantically harmonize heterogeneous data sources and analysis methods in the field, (b) facilitate their joint exploitation through mappings between reference terminologies that the data sources rely on, and (c) provide an exploitable knowledge base of signal analysis methods, experiments and their outcomes including provenance information. PV-SDO has been populated with a significant number of individuals using data from open-source signal detection method implementations, and assessed via data-driven and logic-based techniques, while an evaluation with experts is currently being conducted with well-promising results. ER - TY - JOUR T1 - Enabling GeneHunter as a grid service A1 - Krikov, S A1 - Price, R C A1 - Matney, S A A1 - Allen-Brady, K A1 - Facelli, J C Y1 - 2011/// KW - Algorithms KW - CaBIG KW - Computer Simulation KW - Data modeling KW - Database Management Systems KW - Efficiency KW - Epidemiologic Methods KW - Feasibility Studies KW - Genetics KW - Grid computing KW - Humans KW - Information Dissemination KW - Legacy applications KW - Linkage analysis KW - Medical Informatics KW - Semantic integration KW - User-Computer Interface KW - algorithm KW - article KW - computer interface KW - computer simulation KW - data base KW - epidemiology KW - feasibility study KW - genetics KW - human KW - information dissemination KW - medical informatics KW - methodology KW - organization and management KW - productivity JF - Methods of Information in Medicine VL - 50 IS - 4 SP - 364 EP - 371 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-83455195771&doi=10.3414%2FME10-01-0005&partnerID=40&md5=19210ae83b1bb47cf0fa49e729833f6b N1 - Export Date: 10 September 2018 References: Foster, I., Service-Oriented Science (2005) Science, 308, pp. 814-817; Foster, I., Kesselman, C., Scaling System-Level Science: Scientific Exploration and IT Implications (2006) Computer, pp. 31-53; Facelli, J.C., (2008) The Impact of Grid Computing in Biomedical Informatics, , editor, INFOLAC2008-AAIM; Buenos Aires, Argentina; Langella, S., Hasting, S., Oster, S., Pan, T., Sharma, A., Permar, J., Sharing Data and Analytical Resources Securely in a Biomedical Research Grid Environment (2008) J Am Med Inform Assoc, 15 (3), pp. 363-373; Hastings, S., Oster, S., Langella, S., Ervin, D., Kurc, T., Saltz, J., Introduce: An Open Source Toolkit for Rapid Development of Strongly Typed Grid Services (2007) J Grid Computing, 5, pp. 407-427; Saltz, J., Oster, S., Hastings, S., Langella, S., Kurc, T., Sanchez, W., CaGrid: Design and implementation of the core architecture of the cancer biomedical informatics grid (2006) Bioinformatics, 22, pp. 1910-1916; Jithesh, P.V., Donachy, P., Harmer, T., Kelly, N., Perrott, R., Wasnik, S., Johnston, J., McKee, S., GeneGrid: Architecture, Implementation and Application (2006) J Grid Computing, 4, pp. 209-222; Drake, T.A., Braun, J., Marchevsky, A., Kohane, I.S., Fletcher, C., Chueh, H., A system for sharing routine surgical pathology specimens across institutions: The Shared Pathology (2007) Informatics Network, 38 (8), p. 1212; Sinnott, R.O., Stell, A.J., Ajayi, O., Supporting grid-based clinical trials in Scotland (2008) Health Informatics Journal, 14 (2), pp. 79-93; Corcho, O., Alper, P., Kotsiopoulos, I., Missier, P., Bechhofer, S., Goble, C., An overview of S-OGSA: A Reference Semantic Grid Architecture. Web Semantics: Science (2006) Services and Agents on the World Wide Web, 4 (2), pp. 102-115; Friedrich, C.M., Dach, H., Gattermayer, T., Engelbrecht, G., Benkner, S., Hofmann-Apitius, M., (2008), @neu-Link: A Service-oriented Application for Biomedical Knowledge Discovery, HealthGrid, editors, Chicago: IOS Press; Breton, V., Solomonides, A.E., McClatchey, R.H., A perspective on the Healthgrid initiative. Second International Workshop on Biomedical Computations on the Grid (2004) 4th IEEE/ACM International Symposium on Cluster Computing and the Grid, , http://arxiv.org/abs/cs.DB/0402025, at the, April, Chicago 2004, available from; Erverich, S.G., Silverstein, J.C., Chervenak, A., Schuler, R., Nelson, M.D., Kesselman, C., Globus MEDICUS-federation of DICOM medical imaging devices into healthcare Grids (2007) Stud Health Technol Inform, 126, pp. 269-278; Pierson, J.M., Gossa, J., Wehrle, P., Cardenas, Y., Cahon, S., El Samad, M., GGM: Efficient Navigation and Mining in Distributed Genomedical Data (2007) IEEE Transactions on Nanobioscience, 6 (2), p. 110; Mirto, M., Cafaro, M., Fiore, S.L., Tartarini, D., Aloisio, G., A Grid-Enabled Protein Secondary Structure Predictor (2007) IEEE Transactions on Nanobioscience, 6 (2), p. 124; Sun, Y., Zhao, S., Yu, H., Gao, G., Luo, J., ABCGrid: Application for Bioinformatics Computing Grid (2007) Bioinformatics Applications Note, 23 (9), pp. 1175-1177; Delaitre, T., Kiss, T., Goyeneche, A., Terstyanszky, G., Winter, S., Kacsuk, P., GEMLCA: Running Legacy Code Applications as Grid Services (2005) Journal of Grid Computing, 3, pp. 75-90; Huang, Y., Taylor, I., Walker, D.M., Davies, R., Wrapping Legacy Codes for Grid-Based Applications (2003) 17th International Parallel and Distributed Processing Symposium: IPDPS. IEEE Computer Society, p. 139. , In; Kruglyak, L., Daly, M.J., Reeve-Daly, M.P., Lander, E.S., Parametric and nonparametric linkage analysis: A unified multipoint approach (1996) Am J Hum Genet, 58 (6), pp. 1347-1363; Phillips, J., Chilukuri, R., Fragoso, G., Warzel, D., Covitz, P.A., The caCORE Software Development Kit: Streamlining construction of interoperable biomedical information services (2006) BMC Med Inform Decis Mak, 6, p. 2; Patel, S., caCORE Software Developer Kit (SDK) V 4.1 Programmer's Guide (2008) Informatics NCICfB, Technology aI, , editors. 4.1 ed, In; Komatsoulis, G.A., Warzel, D.B., Hartel, F.W., Shanbhag, K., Chilukuri, R., Fragoso, G., caCORE version 3: Implementation of a model driven, serviceoriented architecture for semantic interoperability (2008) J Biomed Inform, 41 (1), pp. 106-123 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: A cursory analysis of the biomedical grid literature shows that most projects emphasize data sharing and the development of new applications for the grid environment. Much less is known about the best practices for the migration of existing analytical tools into the grid environment. Objectives: To make GeneHunter available as a grid service and to evaluate the effort and best practices needed to enable a legacy application as a grid service when addressing semantic integration and using the caBIG tools. Methods: We used the tools available in the caBIG environment because these tools are quite general and they may be used to deploy services in similar biomedical grids that are OGSA-compliant. Results: We achieved semantic integration of GeneHunter within the caBIG by creating a new UML model, LinkageX, for the LINKAGE data format. The LinkageX UML model has been published in the caDSR and it is publically available for usage with GeneHunter or any other program using this data format. Conclusions: While achieving semantic interoperability is still a time-consuming task, the tools available in caBIG can greatly enhance productivity and decrease errors. © Schattauer 2011. ER - TY - JOUR T1 - The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature A1 - Kruse, C S A1 - Stein, A A1 - Thomas, H A1 - Kaur, H Y1 - 2018/// JF - Journal of Medical Systems VL - 42 IS - 11 DO - 10.1007/s10916-018-1075-6 N2 - ©2018, The Author(s). Electronic health records (EHRs) have emerged among health information technology as “meaningful use” to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012–10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities. ER - TY - JOUR T1 - Health and clinical management: from patient care to national public health increasing the integration of all health care participants and systems interoperability for better care management. A1 - Kubias, D Y1 - 2009/// KW - Awards and Prizes KW - Delivery of Health Care KW - Humans KW - Managed Care Programs KW - Medical Informatics KW - Public Health KW - awards and prizes KW - editorial KW - health care delivery KW - human KW - medical informatics KW - public health JF - Yearbook of medical informatics SP - 44 EP - 47 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84856170839&partnerID=40&md5=6a9743814cca03f53091aee29e0cb34b N1 - Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - To present some of last year's best papers in the field of health and clinical management. Synopsis of the best articles selected for the IMIA Yearbook 2009. The selected articles illustrate how IT is enlarging its role in heath care management. By getting closer to patients allowing them feeding systems with there health data, IT can improve patient health management directly at patients' home. With data being documented in increasingly more structured and standardized way, health information systems can better integrated and reuse that data and offer more decision support to physicians and other health professionals. Furthermore, as more data is available in electronic format in real-time, entire populations' health status can be monitored by public health authorities allowing for better public health management. Although the selected articles are only a few bricks in global health management, they are promising examples of how IT improves the integration and collaboration between all participants in health care and offers support at all levels. Tying all these separate bricks together will still require work, as well as developing all the remain bricks, but systems interoperability allowing for data sharing and health participants collaboration are continuously getting more real. ER - TY - JOUR T1 - Redesigning electronic health record systems to support public health A1 - Kukafka, Rita A1 - Ancker, Jessica S A1 - Chan, Connie A1 - Chelico, John A1 - Khan, Sharib A1 - Mortoti, Selasie A1 - Natarajan, Karthik A1 - Presley, Kempton A1 - Stephens, Kayann Y1 - 2007/// KW - Assessment KW - Assurance KW - Decision support KW - Patient-centered health records KW - Policy development KW - Public health KW - Surveillance JF - Journal of Biomedical Informatics VL - 40 IS - 4 SP - 398 EP - 409 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Current electronic health record systems are primarily clinical in focus, designed to provide patient-level data and provider-level decision support. Adapting EHR systems to serve public health needs provides the possibility of enormous advances for public health practice and policy. In this review, we evaluate EHR functionality and map it to the three core functions of public health: assessment, policy development, and assurance. In doing so, we identify and discuss important design, implementation, and methodological issues with current systems. For example, in order to support public health's traditional focus on preventive health and socio-behavioral factors, EHR data models would need to be expanded to incorporate environmental, psychosocial, and other non-medical data elements, and workflow would have to be examined to determine the optimal way of collecting these data. We also argue that redesigning EHR systems to support public health offers benefits not only to the public health system but also to consumers, health-care institutions, and individual providers. © 2007. ER - TY - JOUR T1 - Research evidence on strategies enabling integration of electronic health records in the health care systems of low- and middle-income countries: A literature review A1 - Kumar, M A1 - Mostafa, J Y1 - 2019/// JF - International Journal of Health Planning and Management VL - 34 IS - 2 SP - e1016 EP - -e1025 DO - 10.1002/hpm.2754 N2 - ©2019 John Wiley & Sons, Ltd. Integration of electronic health records (EHRs) in the national health care systems of low- and middle-income countries (LMICs) is vital for achieving the United Nations Sustainable Development Goal of ensuring healthy lives and promoting well-being for all people of all ages. National EHR systems are increasing, but mostly in developed countries. Besides, there is limited research evidence on successful strategies for ensuring integration of national EHRs in the health care systems of LMICs. To fill this evidence gap, a comprehensive survey of literature was conducted using scientific electronic databases—PubMed, SCOPUS, Web of Science, and Global Health—and consultations with international experts. The review highlights the lack of evidence on strategies for integrating EHR systems, although there was ample evidence on implementation challenges and relevance of EHRs to vertical disease programs such as HIV. The findings describe the narrow focus of EHR implementation, the prominence of vertical disease programs in EHR adoption, testing of theoretical and conceptual models for EHR implementation and success, and strategies for EHR implementation. The review findings are further amplified through examples of EHR implementation in Sierra Leone, Malawi, and India. Unless evidence-based strategies are identified and applied, integration of national EHRs in the health care systems of LMICs is difficult. ER - TY - CONF T1 - National strategies for health data interoperability A1 - Kuo, M.-H. A1 - Kushniruk, A W A1 - Borycki, E M A1 - Hsu, C.-Y. A1 - Lai, C.-L. Y1 - 2011/// KW - Canada KW - Data interoperability KW - Denmark KW - E-health KW - Electronic Health Records KW - Electronic health records KW - Federal Government KW - Geography KW - Health Status KW - Systems Integration KW - Taiwan KW - comparative study KW - conference paper KW - electronic medical record KW - organization and management KW - system analysis VL - 164 SP - 238 EP - 242 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-79953046519&doi=10.3233%2F978-1-60750-709-3-238&partnerID=40&md5=0c6d3afd96187f13f3ac9f5ea1e99ec5 N1 - Cited By :1 Export Date: 10 September 2018 References: (2008) Electronic Health Records: A Global Perspective, , http://www.himss.org/content/files/ 200808_EHRGlobalPerspective_whitepaper.pdf, Healthcare Information and Management Systems Society (HIMSS),. Retrieved June 20, 2010 from; Jian, W.-S., Hsu, C.-Y., Hao, T.-H., Wen, H.-C., Hsu, M.-H., Lee, Y.-L., Li, Y.-C., Chang, P., Building a portable data and information interoperability infrastructure-framework for a standard Taiwan Electronic Medical Record Template (2007) Computer Methods and Programs in Biomedicine, 88 (2), pp. 102-111. , DOI 10.1016/j.cmpb.2007.07.014, PII S0169260707001848; Protti, D., A Comparison of How Canada, England, and Denmark are Managing their Electronic Health Record Journeys (2008) Human, Social, and Organizational Aspects of Health Information Systems, pp. 203-218. , A. W. Kushniruk & E. M. Borycki (Eds.), Hershey, Pennsylvania, USA: Medical Information Science Reference; Bernstein, K., Bruun-Rasmussen, M., Vingtoft, S., Andersen, S.K., Nohr, C., Modelling and implementing electronic health records in Denmark (2005) International Journal of Medical Informatics, 74 (2-4), pp. 213-220. , DOI 10.1016/j.ijmedinf.2004.07.007, PII S1386505604001510, MIE 2003; Giokas, D., EHRS Blueprint: An interoperable framework (2008) Canada Health Infoway, , http://www.omg.org/news/meetings/workshops/HC-2008/15-06_Giokas.pdf, Retrieved June 24, 2010 from; Schrader, D., Mackie, K., Somlai, M., Sheaff, T., EHR data interoperability mechanisms - A comparison of canada, Denmark and Taiwan's strategies (2009) HINF310 Group Project Report, School of Health Information Science, , University of Victoria, BC, Canada; Giokas, D., EHRS blueprint: An interoperable framework (2008) Canada Health Infoway, , http://www.omg.org/news/meetings/workshops/HC-2008/15-06_Giokas.pdf, Retrieved June 24, 2010 from; (2009) National IT strategies - Denmark, England and Canada, , http://www.socialstyrelsen.se/Lists/Artikelkatalog/Attachments/8374/ 2009-126-,152_2009126152.pdf, Retrieved June 25, 2010 from; Kuo, M.H., (2010) HINF310 Lecture Note-week 5, , http://web.uvic.ca/~h310/ RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This paper compares the interoperability approaches of three countries: Taiwan, Denmark and Canada. The work maps out how various countries have addressed the interoperability problems as well as what factors affect decisions and the result, and in what manner. The key findings are as follows: (1) The federal government's ability to mandate standards affects choice of interoperability strategy; (2) E-Health status influences choice of interoperability strategy; (3) Differences in geography, population, and demographics affect the selection of national strategies towards interoperability. © 2011 ITCH 2011 Steering Committee and IOS Press. ER - TY - JOUR T1 - Clinical Data Interchange Standards Consortium - Goals, mission, accomplishments A1 - Kush, R D A1 - Siegmann, U Y1 - 2004/// KW - Clinical Data Interchange Standards Consortium KW - Clinical data management KW - Health Status KW - article KW - clinical study KW - clinical trial KW - drug industry KW - food and drug administration KW - information processing KW - model KW - standard JF - Pharmazeutische Industrie VL - 66 IS - 5 SP - 654 EP - 656 N1 - Cited By :1 Export Date: 10 September 2018 References: Kush, R., White Paper, , www.cdisc.org; CDSIC Operating Process (COP-001), , www.cdisc.org; Kubick, W., Christiansen, D., (2001) SDS, pp. U1. , www.cdisc.org; www.hl7.orgUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-3042641297&partnerID=40&md5=f46eea35a905ce4ce9a244bac102cc1e RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Clinical Data Interchange Standards Consortium (CDISC) is developing industry-wide standards to facilitate the acquisition, exchange, submission and archive of electronic clinical data for the biopharmaceutical product development industry. Long-term desired outcomes of CDISC are: A holistic approach to standards, facflitating data interchange from sites through regulatory submission, utilizing XML; Standards for data acquisition supporting the population of cross-trial warehouses and standard review tools; HL7-(Health Level 7) CDISC models harmonized to yield value for both clinical research and healthcare, thus supporting the electronic sharing of information between health records and clinical trials; Global adoption of CDISC data standards. Four CDISC standards are now available: Operational Data Model (ODM) Version 1.2; Laboratory Data Standards (LAB) Version 1.0.1; Submission Data Standard (SDS) Version 3; and a set of Analysis Dataset Models. The first two are focused on data acquisition and the last two on data submission and review. The primary activities of the CDISC volunteer modeling teams, at this point, are directed towards stabilizing and ensuring interoperability among these CDISC standards, themselves, and with the healthcare data standard (Reference Information Model) developed through HL7. CDISC has a formal relationship with HL7 and collaborates directly with HL7 and FDA and other interested groups through the Regulated Clinical Research Information Management (RCRIM) Technical Committee. There are additional standards being developed and accredited through the RCRIM, including Submission Data Standards for animal data, product stability data, clinical trial protocol representation standards, ECG waveform standards. A key opportunity recognized for CDISC and HL7 is to be able to develop common informatics platforms for the improved sharing of clinical research data and healthcare data. Such standards would improve processes for all involved with clinical research - clinicians and investigators, biopharmaceutical industry stakeholders and regulatory reviewers. ER - TY - JOUR T1 - The CrowdHEALTH project and the hollistic health records: Collective wisdom driving public health policies A1 - Kyriazis, D A1 - Autexier, S A1 - Boniface, M A1 - Engen, V A1 - Jimenez-Peris, R A1 - Jordan, B A1 - Jurak, G A1 - Kiourtis, A A1 - Kosmidis, T A1 - Lustrek, M A1 - Magdalinou, A A1 - Wajid, U Y1 - 2019/// JF - Acta Informatica Medica VL - 27 IS - 5 SP - 369 EP - 373 DO - 10.5455/aim.2019.27.369-373 N2 - ©2019 Article Authors Introduction: With the expansion of available Information and Communication Technology (ICT) services, a plethora of data sources provide structured and unstructured data used to detect certain health conditions or indicators of disease. Data is spread across various settings, stored and managed in different systems. Due to the lack of technology interoperability and the large amounts of health-related data, data exploitation has not reached its full potential yet. Aim: The aim of the CrowdHEALTH approach, is to introduce a new paradigm of Holistic Health Records (HHRs) that include all health determinants defining health status by using big data management mechanisms. Methods: HHRs are transformed into HHRs clusters capturing the clinical, social and human context with the aim to benefit from the collective knowledge. The presented approach integrates big data technologies, providing Data as a Service (DaaS) to healthcare professionals and policy makers towards a “health in all policies” approach. A toolkit, on top of the DaaS, providing mechanisms for causal and risk analysis, and for the compilation of predictions is developed. Results: CrowdHEALTH platform is based on three main pillars: Data & structures, Health analytics, and Policies. Conclusions: A holistic approach for capturing all health determinants in the proposed HHRs, while creating clusters of them to exploit collective knowledge with the aim of the provision of insight for different population segments according to different factors (e.g. location, occupation, medication status, emerging risks, etc) was presented. The aforementioned approach is under evaluation through different scenarios with heterogeneous data from multiple sources. ER - TY - JOUR T1 - SOA-BD: Service oriented architecture for biomedical devices A1 - Lacerda, J M T A1 - de Paiva, J C A1 - de Carvalho, D R A1 - de Morais, P S G A1 - Fernandes, Y.Y.M.P. A1 - Valentim, R A M Y1 - 2017/// KW - Access protocols KW - Biomedical devices KW - Biomedical devices communication KW - Computer programming KW - Design Patterns KW - Development teams KW - Embedded systems KW - Functional requirement KW - HL7 KW - Information Systems KW - Information services KW - Intensive care unit KW - Intensive care units KW - Java programming language KW - Medical computing KW - Monitoring applications KW - Network architecture KW - SOA-BD KW - Service Oriented Architecture KW - Service oriented architecture (SOA) KW - Software engineering KW - Telehealth KW - Web services JF - Research on Biomedical Engineering VL - 33 IS - 2 SP - 166 EP - 172 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025139193&doi=10.1590%2F2446-4740.09716&partnerID=40&md5=59ca479ecc943bf2d3f853bd63bff022 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lacerda et al. - 2017 - SOA-BD Service oriented architecture for biomedical devices.pdf N1 - Export Date: 10 September 2018 References: OASIS UDDI Specification TC [Internet], , https://www.oasis-open.org/committees/uddi-spec/faq.php, Burlington: OASIS; 2017. [cited 2017 Mar 3]; (2016) Welcome to Apache Axis2/Java [Internet], , https://axis.apache.org/axis2/java/core/, Wakefield: Apache Software Foundation, cited 2016 Nov 22; (2016) Apache Tomcat® - Welcome! [Internet], , http://tomcat.apache.org/, Wakefield: Apache Software Foundation, cited 2016 Nov 22; Degaspari, J., Device connectivity. Virtua links disparate biomedical devices to its enterprise-wide EMRs (2012) Healthcare Informatics: The Business Magazine for Information and Communication Systems, 29 (5), pp. 43-44. , 22655446; Deugd, S., Carroll, R., Kelly, K., Millett, B., Ricker, J.S.O.D.A., Service Oriented Device Architecture (2006) IEEE Pervasive Computing, 5 (3), pp. 94-96. , http://dx.doi.org/10.1109/MPRV.2006.59; (2016) DICOM Homepage [Internet], , http://dicom.nema.org/, Rosslyn: DICOM, cited 2016 Nov 8; Gamma, E., Helm, R., Johnson, R., Vlissides, J., (1995) Design Patterns: Elements of Reusable Object-Oriented Software, , Boston: Addison-Wesley; Gregorczyk, D., Bußhaus, T., Fischer, S., A proof of concept for medical device integration using web services (2012) Proceedings of the 9Th International Multi-Conference on Systems, Signals Devices; 2012 Mar, pp. 20-23. , http://dx.doi.org/10.1109/SSD.2012.6198124, Chemnitz, Germany. New York: IEEE; (2016) Health Level Seven International – Homepage [Internet], , http://www.hl7.org, Ann Arbor: HL7, cited 2016 Nov 8; (2016) Interfaces, , https://docs.oracle.com/javase/tutorial/java/IandI/createinterface.html, InternetRedwood City: Oracle Corporation, [cited 2016 Nov 08]; Schall, D., Aiello, M., Dustdar, S., Web services on embedded devices (2006) International Journal of Web Information Systems, 1 (2), pp. 45-50. , http://dx.doi.org/10.1108/17440080680000100; Thelen, S., Czaplik, M., Meisen, P., Schilberg, D., Jeschke, S., Using off-the-shelf medical devices for biomedical signal monitoring in a telemedicine system for emergency medical services (2015) IEEE Journal of Biomedical and Health Informatics, 19 (1), pp. 117-123. , http://dx.doi.org/10.1109/JBHI.2014.2361775, 25312967; Hospital Universitário Onofre Lopes. Laboratório De Inovação Tecnológica Em Saúde. Projeto SOA-BD, , http://www.lais.huol.ufrn.br/index.php/component/k2/item/162?show=show, Natal: LAIS; 2016. [cited 2017 Mar 10]; Valentim, R.A.M., Morais, A.H.F., Brandão, G.B., Guerreiro, A.M.G., Xavier, M.A., Araújo, C.A.P.M.P.-H.A., Multicycles Protocol for Hospital Automation over multicast with IEEE 802.3 (2008) Proceedings of the IEEE 6Th International Conference on Industrial Informatics, pp. 979-984. , 13-16 July 2008; Daejeon, Korea. New York: IEEE RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: The communication of information systems with biomedical devices has become complex not only due to the existence of several private communication protocols, but also to the immutable way that software is embedded into these devices. In this sense, this paper proposes a service-oriented architecture to access biomedical devices as a way to abstract the mechanisms of writing and reading data from these devices, thus contributing to enable the focus of the development team of biomedical software to be intended for its functional requirements, i.e. business rules relevant to the problem domain. Methods: The SOA-BD architecture consists of five main components: A Web Service for transport and conversion of the device data, Communication Protocols to access the devices, Data Parsers to preprocess data, a Device Repository to store data and transmitted information and Error handling, for error handling of these information. For the development of SOA-BD, technologies such as the XML language and the Java programming language were used. Besides, Software Engineering concepts such as Design Patterns were also used. For the validation of this work, data has been collected from vital sign monitors in an Intensive Care Unit using HL7 standards. Results: The tests obtained a difference of about only 1 second in terms of response time with the use of SOA-BD. Conclusion: SOA-BD achieves important results such as the reduction on the access protocol complexity, the opportunity for treating patients over long distances, allowing easier development of monitoring applications and interoperability with biomedical devices from diverse manufacturers. © 2017, Brazilian Society of Biomedical Engineering. All rights reserved. ER - TY - JOUR T1 - Towards the integration and development of a cross-European research network and infrastructure: the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub A1 - Lakerveld, Jeroen A1 - van der Ploeg, Hidde P A1 - Kroeze, Willemieke A1 - Ahrens, Wolfgang A1 - Allais, Oliver A1 - Andersen, Lene Frost A1 - Cardon, Greet A1 - Capranica, Laura A1 - Chastin, Sebastien A1 - Donnelly, Alan A1 - Ekelund, Ulf A1 - Finglas, Paul A1 - Flechtner-Mors, Marion A1 - Hebestreit, Antje A1 - Hendriksen, Ingrid A1 - Kubiak, Thomas A1 - Lanza, Massimo A1 - Loyen, Anne A1 - MacDonncha, Ciaran A1 - Mazzocchi, Mario A1 - Monsivais, Pablo A1 - Murphy, Marie A1 - Nöthlings, Ute A1 - O’Gorman, Donal J A1 - Renner, Britta A1 - Roos, Gun A1 - Schuit, Abertine J A1 - Schulze, Matthias A1 - Steinacker, Jürgen A1 - Stronks, Karien A1 - Volkert, Dorothee A1 - van’t Veer, Pieter A1 - Lien, Nanna A1 - De Bourdeaudhuij, Ilse A1 - Brug, Johannes Y1 - 2014/12// KW - Behavioral Sciences KW - Health Promotion and Disease Prevention KW - Nutrition PB - BioMed Central JF - International Journal of Behavioral Nutrition and Physical Activity VL - 11 IS - 1 SP - 143 EP - 143 DO - 10.1186/s12966-014-0143-7 UR - http://ijbnpa.biomedcentral.com/articles/10.1186/s12966-014-0143-7 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lakerveld et al. - 2014 - Towards the integration and development of a cross-European research network and infrastructure the DEterminan.pdf N2 - To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated `joint programming’. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI `A Healthy Diet for a Healthy Life’. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such interventions. ER - TY - BOOK T1 - An iconic approach to the browsing of medical terminologies A1 - Lamy, J.-B. A1 - Thuy, V B A1 - Louët, A.L.-L. A1 - Bousquet, C Y1 - 2019/// JF - Studies in Health Technology and Informatics VL - 264 SP - 213 EP - 217 SN - 9781643680026 DO - 10.3233/SHTI190214 N2 - ©2019 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). Medical terminologies are the basis of interoperability in medicine. They allow connecting the various systems and data and facilitate searches in databases. An example is the MedDRA terminology, used in particular for coding drug adverse events. However, these terminologies are often complex and involve a huge number of terms. Consequently, it is difficult to browse them or find the desired terms. Traditional approaches consist of lexical search, with the problems of synonymy and polysemy, or tree-based navigation, but the user often gets “lost” in the tree. Here, we propose a new approach for browsing medical terminologies: the use of pictograms and icons, for formulating the query in complement to a textual search box, and for displaying the search results. We applied this approach to the MedDRA terminology. We present both the methods and search algorithms and the resulting browsing interface, as well as the qualitative opinions of two pharmacovigilance experts. ER - TY - JOUR T1 - A three stage ontology-driven solution to provide personalized care to chronic patients at home A1 - Lasierra, N A1 - Alesanco, A A1 - Guillén, S A1 - García, J Y1 - 2013/// KW - Biomedical equipment KW - Chronic Disease KW - Chronic patients KW - Conceptual modelling KW - Home Care Services KW - Home-based telemonitoring scenarios KW - Humans KW - Individualized Medicine KW - Knowledge management KW - Knowledge management application KW - Knowledge management applications KW - Monitoring, Physiologic KW - Ontologies KW - Ontology KW - Patient monitoring KW - Personalized care KW - Software prototyping KW - Solutions KW - Tele-monitoring KW - application service provider KW - article KW - chronic patient KW - health care planning KW - health status KW - home care KW - human KW - knowledge management KW - medical care KW - medical information system KW - patient information KW - personalized medicine KW - priority journal KW - telemonitoring JF - Journal of Biomedical Informatics VL - 46 IS - 3 SP - 516 EP - 529 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878307896&doi=10.1016%2Fj.jbi.2013.03.006&partnerID=40&md5=6cc6fb7d98a235849d1f472ae13d5741 N1 - Cited By :27 Export Date: 10 September 2018 References: Maglaveras, N., Chouvarda, I., Koutkias, V.G., Gogou, G., Lekka, I., Goulis, D., The citizen health system (CHS): a modular medical contact center providing quality telemedicine services (2005) IEEE Trans Inf Technol Biomed, 9 (3), pp. 353-362; Basilakis, J., Lovell, N.H., Celler, B.G., A decision support architecture for telecare patient management of chronic and complex disease (2007) Proc in engineering in medicine and biology society conference, EMBS, pp. 4335-4338; http://www.idf.org/webdata/docs/idf-europe/Chronic-disease-alliance-Fina l.pdf, European chronic disease alliance policy report: a unified prevention approach; http://www.un.org/esa/population/, United Nations. World population prospects: the 2010 revision; Monteagudo, J.L., Moreno, O., (2009), http://www.epractice.eu/files/media/media2499.pdf, e-Health for patient empowerment in Europe. World Wide Web electronic publication; Brito, M., Vale, L., Carvalho, P., Henriques, J., A sensor middleware for integration of heterogeneous medical device (2010) Proc in engineering in medicine and biology society conference, EMBS; (2009), http://standards.ieee.org/, ISO/IEEE11073. Personal health devices standard (X73-PHD). Health informatics (P11073 - 104xx. Device specializations) (P11073-20601. Application profile - optimized exchange protocol); Zhang, D., Yu, Z., Chin, C.-Y., Context-aware infrastructure for personalized healthcare (2005) Stud Health Technol Inform, 117, pp. 154-163; Saranummi, N., IT applications for pervasive, personal, and personalized health (2008) IEEE Trans Inf Technol Biomed, 12 (1), pp. 1-4; Fortin, M., Bravo, G., Hudon, C., Vanasse, A., Lapointe, L., Prevalence of multimorbidity among adults seen in family practice (2005) Ann Fam Med, 3 (3), pp. 223-228; Gijsen, R., Hoeymans, N., Schellevis, F.G., Ruwaard, D., Satariano, W.A., Van den Bos, G.A., Causes and consequences of comorbidity: a review (2001) J Clin Epidemiol, 54, pp. 661-674; Studer, R., Benjamins, V.R., Fensel, D., Knowledge engineering: principles and methods (1998) Data Knowledge Eng, 25, pp. 161-197; http://www.obofoundry.org/, OBO Foundry repository; http://bioportal.bioontology.org/, BioPortal repository, NCBO; http://code.google.com/p/ogms/, OMGS ontology; Latfi, F., Lefebvre, B., Descheneaux, C., Ontology-based management of the telehealth smart home, dedicated to elderly in loss of cognitive autonomy (2007) Third int workshop on OWL: experiences and directions, OWLED; Fook, V.F.S., Tay, S.C., Jayachandran, M., Biswas, J., Zhang, D., An ontology-based context model in monitoring and handling agitation behavior for persons with dementia (2006) Proc of the fourth annual IEEE int conference on pervasive computing and communications workshops (PERCOMW'06); Campana, F., Moreno, A., Riaño, D., Varga, L., K4Care: knowledge-based homecare e-services for an ageing Europe (2008) Agent Technology and e-Health, pp. 95-115; Gibert, K., Valls, A., Riaño, D., (2008) Knowledge engineering as a support for building an actor profile ontology for integrating home-care systems, , Proc MIE, Gteborg, Sweden; Riaño, D., Real, F., Albert López-Vallverdú, J., Campana, F., Ercolani, S., Mecocci, P., An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients (2012) J Biomed Inform, 45 (3), pp. 429-446; Paganelli, F., Giuli, D., An ontology-based system for context-aware and configurable services to support home-based continuous care (2011) IEEE Trans Inf Technol Biomed, 15 (2), pp. 324-333; Tablado, A., Illarramendi, A., Bagüés, M.I., Bermúdez, J., Goñi, A., An intelligent system for assisting elderly people (2005), pp. 466-74. , Hacid M-S, Murray NV, Ras ZW, Tsumoto S, editors. Proc. of. 15th international symposium foundations of intelligent systems, ISMIS; Batet, M., Isern, D., Marin, L., Martínez, S., Moreno, A., Sánchez, D., Knowledge-driven delivery of home care services (2012) J Intell Inform Syst, 38 (1), pp. 95-130; Isern, D., Sánchez, D., Moreno, A., Agents applied in health care: a review (2010) Int J Med Inform, 79 (3), pp. 145-166; Sampalli, T., Shepherd, M., Duffy, J., A patient profile ontology in the heterogeneous domain of complex and chronic health conditions (2011) Proc of the 44th int conf on system sciences (HICSS '11), , Hawaii; Kuziemsky, C.E., Lau, F., A four stage approach for ontology-based health information system design (2010) Artif Intell Med, 50, pp. 133-148; Uschold, M., Jasper, R., A framework for understanding and classifying ontology applications (1999) Proc of the IJCAI99 workshop on ontologies, pp. 16-21; Lasierra, N., Alesanco, A., García, J., O'Sullivan, D., Data management in home scenarios using an autonomic ontology-based approach (2012) Proc of the 9th IEEE workshop on managing ubiquitous communications and services (MUCS); Martíez, I., Escayola, J., Martínez-Espronceda, M., Muñoz, P., Trigo, J.D., Muñoz, A., Seamless integration of ISO/IEEE11073 personal health devices and ISO/EN13606 electronic health records into an end-to-end interoperable solution (2010) Telemed J E Health, 16 (10), pp. 993-1004; Scherr, D., Kastner, P., Kollmann, A., Hallas, A., Auer, J., Krappinger, H., MOBITEL investigators, effect of home-based telemonitoring using mobile phone technology on the outcome of heart failure patients after an episode of acute decompensation: randomized controlled trial (2009) J Med Internet Res, 11 (3), pp. e34; Predrag, K., Wanda, P., Healthcare in the pocket: mapping the space of mobile-phone health interventions (2012) J Biomed Inform, 45 (1), pp. 184-198; Pinto, S.F., Martins, J.P., Ontologies: how can they be built? (2004) Knowledge Inform Syst, 6, pp. 441-464; Noy, N.F., McGuinness, D.L., Ontology development 101: a guide to creating your first ontology (2001), Technical report SMI-2001-0880. Stanford Medical Informatics; Smith, M.K., Welthy, C., McGuiness, D.L., (2004), http://www.w3.org/TR/owl-guide/, OWL web ontology language guide, W3C recommendation; Lasilla, O., Swick, R., (2004), http://www.w3.org/TR/REC-rdf-syntax, Resource description framework (RDF) model and syntax specification, W3C recommendation; http://protege.stanford.edu, Protégé-OWL editor; López de Vergara, J.E., Villagra, V.A., Fadon, C., Gonzalez, J.M., Lozano, J.A., Alvarez-Campana, M., An autonomic approach to offer services in OSGi-based home gateways (2008) Comput Commun, 31 (13), pp. 3049-3058; (2008), SPARQL query language for RDF. W3C recommendation; 15 January; Kephart, J.O., Chess, D.M., The vision of autonomic computing (2003) Computer, 36 (1), pp. 41-50; (2011), http://www.ihtsdo.org/snomed-ct, IHTSDO: SNOMED CT; Brank, J., Grobelnik, M., Mladenic, D., A survey of ontology evaluation techniques (2005) Proc of the conf on data mining and data warehouses, SiKDD; Vrandecic, D., Ontology evaluation (2010), PhD dissertation. KIT, Fakultät für Wirtschaftswissenschaften, Karlsruhe; (2011), The global initiative for chronic obstructive lung disease (GOLD) pocket guide to COPD diagnosis, management, and prevention. Revised; Tsigos, C., Hainer, V., Basdevant, A., Finer, N., Fried, M., Mathus-Vliegen, E., Management of obesity in adults: European clinical practice guidelines (2008) Obesity management task force of the European association for the study of obesity, pp. 106-16. , Obesity management task force of the European association for the study of obesity, Obesity facts; http://www.endotext.org/guidelines.htm, Guidelines for management of clinical endocrine disease; http://www.secardiologia.es/practica-clinica-investigacion/guias-practic a-clinica-cardiologia/cardiopatia-isquemica, Spanish society of cardiology. Clinical guidelines for ischemic heart disease; http://www.nhlbi.nih.gov/guidelines/asthma/, Guidelines for the diagnosis and management of asthma (EPR-3); http://guidance.nice.org.uk/CG127/NICEGuidance, CG127 hypertension: NICE guideline; ICSI health care guideline: diagnosis and treatment of osteoporosis (2011); http://www.secardiologia.es/practica-clinica-investigacion/guias-practic a-clinica-cardiologia/insuficiencia-cardiaca-y-miocardiopatia, Spanish society of cardiology. Clinical guidelines for heart failure; (2011), American diabetes association. Executive summary: standards of medical care in diabetes; Genest, J., Canadian cardiovascular society/Canadian guidelines for the diagnosis and treatment of dyslipidemia and prevention of cardiovascular disease in the adult - 2009 recommendations (2009) Can J Cardiol, 25, pp. 567-579; (2008), NICE clinical guideline 59. Osteoarthritis: the care and management of osteoarthritis in adults; Grando, A., Peleg, M., Glasspool, D., A goal-oriented framework for specifying clinical guidelines and handling medical errors (2010) J Biomed Inform, 43 (2), pp. 287-299; http://www.who.int/gho/ncd/en/index.html, WHO (World Health Organization) non-communicable diseases (NCD); https://apps.who.int/infobase/Indicators.aspx, WHO (World Health Organization) global infoBase; Miravitlles, M., Soriano, J.B., García-Río, F., Muñoz, L., Duran-Tauleria, E., Sanchez, G., Prevalence of COPD in Spain: impact of undiagnosed COPD on quality of life and daily life activities (2009) Thorax, 64 (10), pp. 863-868; Loza, E., Abásolo, L., Jover, J.A., Carmona, L., EPISER study group, Burden of disease across chronic diseases: a health survey that measured prevalence, function, and quality of life (2008) J Rheumatol, 35 (1), pp. 159-165; Reginster, J.Y., Burlet, N., Osteoporosis: a still increasing prevalence (2006) Bone, 38 (2 SUPPL. 1), pp. S4-S9; http://jena.sourceforge.net/, Jena framework; http://openjena.org/TDB/, TDB triple-store; Otero, A., Félix, P., Barro, S., Palacios, F., Addressing the flaws of current critical alarms: a fuzzy constraint satisfaction approach (2009) Artif Intell Med, 47 (3), pp. 219-238; Hasan, A., Paul, V., Telemonitoring in chronic heart failure (2011) J Eur Heart, 32, pp. 1457-1464 L52545800 2013-04-23 2013-06-07 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Purpose: The goal of this work is to contribute to personalized clinical management in home-based telemonitoring scenarios by developing an ontology-driven solution that enables a wide range of remote chronic patients to be monitored at home. Methods: Through three stages, the challenges of integration and management were met through the ontology development and evaluation. The first stage dealt with the ontology design and implementation. The second stage dealt with the ontology application study in order to specifically address personalization issues. For both stages, interviews and working sessions were planned with clinicians. Clinical guidelines and MDs (medical device) interoperability were taken into account as well during these stages. Finally the third stage dealt with a software prototype implementation. Results: An ontology was developed as an outcome of the first stage. The structure, based on the autonomic computing paradigm, provides a clear and simple manner to automate and integrate the data management procedure. During the second stage, the application of the ontology was studied to monitor patients with different and multiple morbidities. After this task, the ontology design was successfully adjusted to provide useful personalized medical care. In the third and final stage, a proof-of-concept on the software required to remote monitor patients by means of the ontology-based solution was developed and evaluated. Conclusions: Our proposed ontology provides an understandable and simple solution to address integration and personalized care challenges in home-based telemonitoring scenarios. Furthermore, our three-stage approach contributes to enhance the understanding, re-usability and transferability of our solution. © 2013 Elsevier Inc. ER - TY - JOUR T1 - The APHL/CDC Public Health Laboratory Interoperability Project Portal: a web-based collaborative tool to establish a national harmonized vocabulary for public health data exchange. A1 - Lazo, R A1 - Li, W A1 - Meigs, M A1 - Abner, S A1 - Carroll, J A1 - Miller, C A1 - Zarcone, P A1 - Hinrichs, S A1 - Nordenberg, D Y1 - 2006/// KW - Centers for Disease Control and Prevention (U.S.) KW - Computer Communication Networks KW - Cooperative Behavior KW - Internet KW - Laboratories KW - Public Health Informatics KW - United States KW - Vocabulary KW - Vocabulary, Controlled KW - article KW - computer network KW - cooperation KW - laboratory KW - linguistics KW - medical informatics KW - methodology KW - organization and management KW - public health service KW - standard JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium SP - 999 EP - 999 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-34748877163&partnerID=40&md5=e20122323be9c2bf39cd9c4845f4c005 N1 - Cited By :1 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public health laboratories at all capacity levels are facing challenges in exchanging electronic data among themselves and with their partners. In response to this the Association of Public Health Laboratories working collaboratively with CDC launched an innovative portal development project in January 2006. This portal will enable public health laboratories to collaborate in a web-based environment to establish a standardized vocabulary for test identifications and test results, a cornerstone for creating interoperable information systems. ER - TY - JOUR T1 - Modernizing Centers for Disease Control and Prevention Informatics Using Surveillance Data Platform Shared Services A1 - Lee, Brian A1 - Martin, Tonya A1 - Khan, Agha A1 - Fullerton, Kathleen A1 - Duck, Wil A1 - Kinley, Teresa A1 - Stoutenburg, Suzette A1 - Hall, Jason A1 - Crum, Melvin A1 - Garcia, Macarena C. A1 - Iademarco, Michael F. A1 - Richards, Chesley L. Y1 - 2018/03// KW - change management KW - interoperability KW - public health informatics KW - public health surveillance PB - SAGE PublicationsSage CA: Los Angeles, CA JF - Public Health Reports VL - 133 IS - 2 SP - 130 EP - 135 DO - 10.1177/0033354917751130 UR - http://journals.sagepub.com/doi/10.1177/0033354917751130 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Lee et al. - 2018 - Modernizing Centers for Disease Control and Prevention Informatics Using Surveillance Data Platform Shared Services.pdf ER - TY - JOUR T1 - Data, staff, and money: Leadership reflections on the future of public health informatics A1 - Leider, J P A1 - Shah, G H A1 - Williams, K S A1 - Gupta, A A1 - Castrucci, B C Y1 - 2017/// KW - Data Accuracy KW - Data Collection KW - Delivery of Health Care KW - Electronic Health Records KW - Health departments KW - Humanism KW - Humanities KW - Humans KW - Informatics KW - Leadership KW - Local Government KW - Medical Informatics KW - Public Health KW - Public Health Informatics KW - Public health informatics KW - Public health systems research (PHSSR) KW - Qualitative Research KW - Technology KW - United States KW - devices KW - economics KW - electronic health record KW - government KW - health care delivery KW - human KW - information processing KW - leadership KW - manpower KW - measurement accuracy KW - medical informatics KW - organization and management KW - public health KW - qualitative research KW - standards KW - trends JF - Journal of Public Health Management and Practice VL - 23 IS - 3 SP - 302 EP - 310 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017338910&doi=10.1097%2FPHH.0000000000000580&partnerID=40&md5=fb62c997aa8bfee828d460d1740de6f2 N1 - Cited By :2 Export Date: 10 September 2018 References: Eysenbach, G., Infodemiology and infoveillance: Framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet (2009) J Med Internet Res., 11 (1), p. e11; Kun, L.G., Telehealth and the global health network in the 21st century. From homecare to public health informatics (2001) Comput Methods Programs Biomed., 64 (3), pp. 155-167; LaVenture, M., Ross, D.A., Yasnoff, W.A., Public health informatics (2014) Biomedical Informatics, pp. 503-516. , New York, NY: Springer; Lombardo, J.S., Buckeridge, D.L., (2012) Disease Surveillance: A Public Health Informatics Approach, , Hoboken, NJ: John Wiley & Sons; Yasnoff, W.A., Overhage, J.M., Humphreys, B.L., LaVenture, M., A national agenda for public health informatics (2001) J Am Med Inform Assoc., 8 (6), pp. 535-545; O'Carroll, P.W., Defining public health informatics (2003) Introduction to Public Health Informatics, pp. 3-15. , Yasnoff WA, Ward ME, Ripp LH, Martin EL, eds. New York, NY: Springer; (2014) Informatics Areas: Public Health Informatics, , https://www.amia.org/applications-informatics/public-health-informatics, AMIA. Published. Accessed April 1, 2014; Magruder, C., Burke, M., Hann, N.E., Ludovic, J.A., Using information technology to improve the public health system (2005) J Public Health Manag Pract., 11 (2), pp. 123-130; Friede, A., Blum, H.L., McDonald, M., Public health informatics: How information-age technology can strengthen public health (1995) Annu Rev Public Health, 16, pp. 239-252; Richardson, J.E., Abramson, E.L., Pfoh, E.R., Kaushal, R., Howcommunities are leveraging the health information technology workforce to implement electronic health records (2011) AMIA Annual Symposium Proceedings, , Paper presented at: Washington, DC; Heisey-Grove, D., Church, D.R., Haney, G.A., Demaria, A., Jr., Enhancing surveillance for hepatitis C through public health informatics (2011) Public Health Rep., 126 (1), pp. 13-18; Kirkwood, J., Jarris, P.E., Aligning health informatics across the public health enterprise (2012) J Public Health Manag Pract., 18 (3), pp. 288-290; Aragón, T.J., (2013) The New Population Health Division Transforming Public Health in San Francisco, , San Francisco, CA: San Francisco Department of Public Health; Van Wave, T.W., Scutchfield, F.D., Honore, P.A., Recent advances in public health systems research in the United States (2010) Annu Rev Public Health, 31, pp. 283-295; LaVenture, M., Brand, B., Ross, D.A., Baker, E.L., Building an informaticssavvy health department: Part I, vision and core strategies (2014) J Public Health Manag Pract., 20 (6), pp. 667-669; LaVenture, M., Brand, B., Ross, D.A., Baker, E.L., Building an informaticssavvy health department II: Operations and tactics (2015) J Public Health Manag Pract., 21 (1), pp. 96-99; Massoudi, B.L., Goodman, K.W., Gotham, I.J., An informatics agenda for public health: Summarized recommendations from the 2011 AMIA PHI Conference (2012) J Am Med Inform Assoc., 19 (5), pp. 688-695; Ostrovsky, A., Katz, M.H., The San Francisco community vital signs: Using web-based tools to facilitate the mobilizing for action through planning and partnerships process (2011) J Public Health Manag Pract., 17 (5), pp. 457-471; Wolf, L., Harvell, J., Jha, A.K., Hospitals ineligible for federal meaningful-use incentives have dismally low rates of adoption of electronic health records (2012) Health Aff (Millwood), 31 (3), pp. 505-513; Lenert, L., Sundwall, D.N., Public health surveillance and meaningful use regulations: A crisis of opportunity (2012) Am J Public Health, 102 (3), pp. e1-e7; Moiduddin, A., (2013) Assessing the Status and Prospects of State and Local Health Department Information Technology Infrastructure, , Washington, DC: Assistant Secretary for Planning and Evaluation; Shah, G., Rogers, V., Lovelace, K., (2011) Local Public Health Agencies' Involvement in Electronic Health Records and Syndromic Surveillance Systems, , Presented at: American Public Health Association (APHA) Annual Meeting; Washington, DC; Savel, T.G., Foldy, S., The role of public health informatics in enhancing public health surveillance (2012) MMWR Surveill Summ., 61, pp. 20-24; Shah, G.H., Williams, K., Shah, B.G., Implementation of electronic disease reporting systems by local health departments (2015) Front Public Health Serv Syst Res., 4 (4), pp. 13-20; Buehler, J.W., Sonricker, A., Paladini, M., Soper, P., Mostashari, F., Syndromic surveillance practice in the United States: Findings from a survey of state, territorial, and selected local health departments (2008) Adv Dis Surveill., 6 (3), pp. 1-20; Castrucci, B.C., Rhoades, E.K., Leider, J.P., Hearne, S., What gets measured gets done: An assessment of local data uses and needs in large urban health departments (2015) J Public Health Manag Pract., 21, pp. S38-S48; Leider, J.P., Shah, G.H., Castrucci, B.C., Leep, C.J., Sellers, K., Sprague, J.B., Changes in public health workforce composition: Proportion of part-time workforce and its correlates, 2008-2013 (2014) Am J Prev Med., 47 (5), pp. S331-S336; Lin, F., Lasry, A., Sansom, S.L., Wolitski, R.J., Estimating the impact of state budget cuts and redirection of prevention resources on the HIV epidemic in 59 California local health departments (2013) PLoS One., 8 (3), p. e55713; (2012) Budget Cuts Continue to Affect the Health of Americans: Update March 2012, , Arlington, VA: Association of State and Territorial Health Officials; Johnson, N., Oliff, P., Williams, E., (2011) An Update on State Budget Cuts, p. 9. , Washington, DC: Center on Budget and Policy Priorities; Erwin, P.C., Shah, G.H., Mays, G.P., Local health departments and the 2008 recession: Characteristics of resiliency (2014) Am J Prev Med., 46 (6), pp. 559-568; Willard, R., Shah, G.H., Leep, C., Ku, L., Impact of the 2008-2010 economic recession on local health departments (2012) J Public Health Manag Pract., 18 (2), pp. 106-114; Sellers, K., Leider, J.P., Harper, M., Highlights from the public health workforce interests and needs survey: The first nationally representative survey of state health agency employee (2015) J Public Health Manage Pract., 21, pp. S13-S27; Liss-Levinson, R., Bharthapudi, K., Leider, J.P., Sellers, K., Loving and leaving public health: Predictors of intentions to quit among state health agency workers (2015) J Public Health Manag Pract., 21, pp. S91-S101; Porshaban, D., Basurto-Davila, R., Shih, M., Building and sustaining strong public health agencies: Determinants of workforce turnover (2015) J Public Health Manag Pract., 21, pp. S80-S90; Dixon, B.E., McFarlane, T.D., Dearth, S., Grannis, S.J., Gibson, P.J., Characterizing informatics roles and needs of public health workers: Results from the public health workforce interests and needs survey (2015) J Public Health Manag Pract., 21, pp. S130-S140; Sellers, K., Leider, J.P., Harper, E., The public health workforce interests and needs survey: The first national survey of state health agency employees (2015) J Public Health Manag Pract., 21, pp. S13-S27; Leep, C.J., Shah, G.H., NACCHO's national profile of local health departments study: The premier source of data on local health departments for surveillance, research, and policymaking (2012) J Public Health Manag Pract., 18 (2), pp. 186-189; Matheson, A., Shah, G., What do local health departments know about how they know? Results from NACCHO's informatics assessment survey (2010) National Association of County and City Health Officials, , Paper presented at: Memphis, TN; Shah, G.H., Leider, J.P., Castrucci, B.C., Williams, K.S., Luo, H., Characteristics of local health departments associated with implementation of electronic health records and other informatics systems (2016) Public Health Rep., 131 (2), pp. 272-282; McCullough, J.M., Zimmerman, F.J., Bell, D.S., Rodriguez, H.P., Local public health department adoption and use of electronic health records (2015) J Public Health Manag Pract., 21 (1), pp. E20-E28; McCullough, J.M., Goodin, K., Patterns and correlates of public health informatics capacity among local health departments: An empirical typology (2014) Online J Public Health Inform., 6 (3), p. e199 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Context: Health informatics can play a critical role in supporting local health departments' (LHDs') delivery of certain essential public health services and improving evidence base for decision support. However, LHDs' informatics capacities are below an optimum level. Efforts to build such capacities face ongoing challenges. Moreover, little is known about LHD leaders' desires for the future of public health informatics. Objectives: Conduct a qualitative analysis of LHDs' future informatics plans, perceived barriers to accomplishing those plans, and potential impact of future advances in public health informatics on the work of the public health enterprise. Methods: This research presents findings from 49 in-depth key informant interviews with public health leaders and informatics professionals from LHDs, representing insights from across the United States. Interviewees were selected on the basis of the size of the population their LHD serves, as well as level of informatics capacity. Interviews were transcribed, verified, and double coded. Results: Major barriers to doing more with informatics included staff capacity and training, financial constraints, dependency on state health agency, and small LHD size/lack of regionalization. When asked about the role of leadership in expanding informatics, interviewees said that leaders could make it a priority through (1) learning more about informatics and (2) creating appropriate budgets for integrated information systems. Local health department leaders said that they desired data that were timely and geographically specific. In addition, LHD leaders said that they desired greater access to clinical data, especially around chronic disease indicators. Conclusions: Local health department leadership desires to have timely or even real-time data. Local health departments have a great potential to benefit from informatics, particularly electronic health records in advancing their administrative practices and service delivery, but financial and human capital represents the largest barrier. Interoperability of public health systems is highly desirable but hardly achievable in the presence of such barriers. © 2017 Wolters Kluwer Health, Inc. ER - TY - CONF T1 - A deployment and research roadmap for semantic interoperability: The EU semanticHEALTH project A1 - Lewalle, P A1 - Rodrigues, J M A1 - Zanstra, P A1 - Ustun, B A1 - Kalra, D A1 - Surjan, G A1 - Rector, A A1 - Stroetmann, V A1 - Virtanen, M Y1 - 2008/// KW - Computer Communication Networks KW - Delivery of Health Care KW - Diffusion of Innovation KW - Education KW - Electronic Health Record KW - Europe KW - European Union KW - Humans KW - Medical Records Systems, Computerized KW - Multilingualism KW - Natural Language Processing KW - Needs Assessment KW - Ontology KW - Public Health KW - Public Health Informatics KW - Research KW - Semantic Interoperability KW - Semantics KW - Social Change KW - Software Design KW - Systems Integration KW - computer network KW - computer program KW - conference paper KW - education KW - health care delivery KW - human KW - language KW - mass communication KW - medical informatics KW - medical record KW - natural language processing KW - needs assessment KW - organization and management KW - research KW - semantics KW - social change KW - system analysis JF - Studies in Health Technology and Informatics VL - 136 SP - 635 EP - 640 N1 - Cited By :6 Export Date: 10 September 2018 References: http://en.wikipedia.org/wiki/Technology_roadmap, WIKIPEDIA Technology roadmap; Galvin, R., (1998) Science roadmaps in Science, 280, p. 803. , May 8; Garcia M L and Bray O H. Fundamentals of technology roadmapping. Sandia Nat. Labs., Albuquerque, NM, SAND97-0665, March 1998; SemanticHEALTH Deliverable D1.1. Conceptual Framework for e-Health Interoperability. European Union Commission; Brussels 2006; SemanticHEALTH Deliverable D1.2. Interoperability: inventory of key relevant member states and international experiences. European Union Commission; Brussels 2007; SemanticHEALTH Deliverable D2.1. Towards a semantic interoperability roadmap: technological issues. European Union Commission; Brussels 2007; SemanticHEALTH Deliverable D5.1. Towards a semantic interoperability roadmap: public health and secondary uses. European Union Commission; Brussels 2007; SemanticHEALTH Deliverable D7.0. Methodology for a roadmap; European Union Commission; Brussels 2007; SemanticHEALTH Deliverable D3.1. Comparative analysis and socio-economic recommendations for improving semantic interoperability. European Union Commission; Brussels 2007; RIDE Deliverable D4.1.1. European Union Commission; Brussels 2006; SemanticHEALTH Deliverable D7.1. Semantic interoperability deployment and research roadmap European Union Commission; Brussels 2008; SemanticHEALTH Deliverable D4.1. Barriers, approaches and research priorities for semantic interoperability in support of of clinical care delivery European Union Commission; Brussels 2008; SemanticHEALTH Deliverable D6.1. Barriers, approaches and research priorities for integrating biomedical ontologies European Union Commission; Brussels 2008UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-44349149890&partnerID=40&md5=db6345e0c5832ba1b15b255ec60a5aac RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The purpose of this EU funded project is to describe a short and medium term Research and Deployment Roadmap for Semantic Interoperability in e-health. It started by defining 4 levels and 3 dimensions for Semantic Interoperability. The vision is to reconcile the needs for the direct patient care safety, biomedical and clinical research and for public health by the reuse of direct care data: from gene to individuals and populations. The methodology is presented and preliminary results and milestones for the short and the long term are set. We conclude by statements on the main characteristics and needs of the roadmap to sustain better health for individual and populations in the changing EU health care systems. © Organizing Committee of MIE 2008. All rights reserved. ER - TY - JOUR T1 - Development of an openEHR Template for COVID-19 Based on Clinical Guidelines A1 - Li, M A1 - Leslie, H A1 - Qi, B A1 - Nan, S A1 - Feng, H A1 - Cai, H A1 - Lu, X A1 - Duan, H Y1 - 2020/// JF - Journal of medical Internet research VL - 22 IS - 6 SP - e20239 EP - e20239 DO - 10.2196/20239 N2 - ©Mengyang Li, Heather Leslie, Bin Qi, Shan Nan, Hongshuo Feng, Hailing Cai, Xudong Lu, Huilong Duan. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 10.06.2020. BACKGROUND: The coronavirus disease (COVID-19) was discovered in China in December 2019. It has developed into a threatening international public health emergency. With the exception of China, the number of cases continues to increase worldwide. A number of studies about disease diagnosis and treatment have been carried out, and many clinically proven effective results have been achieved. Although information technology can improve the transferring of such knowledge to clinical practice rapidly, data interoperability is still a challenge due to the heterogeneous nature of hospital information systems. This issue becomes even more serious if the knowledge for diagnosis and treatment is updated rapidly as is the case for COVID-19. An open, semantic-sharing, and collaborative-information modeling framework is needed to rapidly develop a shared data model for exchanging data among systems. openEHR is such a framework and is supported by many open software packages that help to promote information sharing and interoperability. OBJECTIVE: This study aims to develop a shared data model based on the openEHR modeling approach to improve the interoperability among systems for the diagnosis and treatment of COVID-19. METHODS: The latest Guideline of COVID-19 Diagnosis and Treatment in China was selected as the knowledge source for modeling. First, the guideline was analyzed and the data items used for diagnosis and treatment, and management were extracted. Second, the data items were classified and further organized into domain concepts with a mind map. Third, searching was executed in the international openEHR Clinical Knowledge Manager (CKM) to find the existing archetypes that could represent the concepts. New archetypes were developed for those concepts that could not be found. Fourth, these archetypes were further organized into a template using Ocean Template Editor. Fifth, a test case of data exchanging between the clinical data repository and clinical decision support system based on the template was conducted to verify the feasibility of the study. RESULTS: A total of 203 data items were extracted from the guideline in China, and 16 domain concepts (16 leaf nodes in the mind map) were organized. There were 22 archetypes used to develop the template for all data items extracted from the guideline. All of them could be found in the CKM and reused directly. The archetypes and templates were reviewed and finally released in a public project within the CKM. The test case showed that the template can facilitate the data exchange and meet the requirements of decision support. CONCLUSIONS: This study has developed the openEHR template for COVID-19 based on the latest guideline from China using openEHR modeling methodology. It represented the capability of the methodology for rapidly modeling and sharing knowledge through reusing the existing archetypes, which is especially useful in a new and fast-changing area such as with COVID-19. ER - TY - JOUR T1 - Semi automated transformation to owl formatted files as an approach to data integration: A feasibility study using environmental, Disease register and primary care clinical data A1 - Liang, S F A1 - Taweel, A A1 - Miles, S A1 - Kovalchuk, Y A1 - Spiridou, A A1 - Barratt, B A1 - Hoang, U A1 - Crichton, S A1 - Delaney, B C A1 - Wolfe, C Y1 - 2015/// KW - Data linkage KW - Databases, Factual KW - Electronic Health Records KW - Feasibility Studies KW - Female KW - Humans KW - Informatics KW - Information Storage and Retrieval KW - Knowledge KW - Male KW - OWL ontology KW - Primary Health Care KW - Product Surveillance, Postmarketing KW - Registries KW - Semantics KW - Strigiformes KW - Systems Integration KW - Terminology as Topic KW - electronic health record KW - evaluation study KW - factual database KW - feasibility study KW - female KW - human KW - information retrieval KW - male KW - nomenclature KW - postmarketing surveillance KW - primary health care KW - register KW - semantics KW - system analysis JF - Methods of Information in Medicine VL - 54 IS - 1 SP - 32 EP - 40 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921308160&doi=10.3414%2FME13-02-0029&partnerID=40&md5=a9e9bde5cf8554e904c09643322604f5 N1 - Cited By :4 Export Date: 10 September 2018 References: Rinner, C., Janzek-Hawlat, S., Sibinovic, S., Duft - Schmid, G., Semantic Validation of Standard-based Electronic Health Record Documents with W3C XML Schema (2010) Methods Inf Med, 49 (3), pp. 271-280; Sachdeva, S., Bhalla, S., Semantic interoperability in standardized electronic health record databases (2012) Journal of Data and Information Quality, 3 (1), pp. 1-37; Taweel, A., Speedie, S., Tyson, G., Tawil, A.R.H., Peterson, K., Delaney, B.C., Service and Modeldriven Dynamic Integration of Health Data (2011) The first international workshop on Managing interoperability and complexity in health systems, , Glasgow; Budgen, D., Rigby, M., Brereton, P., Turner, M., A data Integration Broker for healthcare ststems (2007) IEEE Computer, 40940, pp. 34-41; Tao, C., Pathak, J., Welch, S.R., Bouamrane, M.-M., Huff, S.M., Chute, C.G., Toward Semantic Web based Knowledge Representation and Extraction from Electronic Health Records (2011) Managing Interoperability and Complexity in Health Systems (MIXHS’11), , Glasgow, Scotland, UK: October 28; Barbarito, F., Pinciroli, F., Mason, J., Marceglia, S., Mazzola, L., Bonacina, S., Implementing standards for the interoperability among healthcare providers in the public regionalized Healthcare Information System of the Lombardy Region (2012) Journal of biomedical informatics, 45 (4), pp. 736-745. , PubMed PMID: 22285983; Bouamrane, M.-M., Rector, A., Hurrell, M., Semiautomatic Generation of a Patient Preoperative Knowledge-Base from a Legacy Clinical Database (2009) OnTheMove (OTM), pp. 1224-1237. , Berlin Heidelberg: Springer- Verlag. LNCS 5871; Rector, A., Qamar, R., Marley, T., Binding Ontologies & Coding systems to Electronic Health Records and Messages (2009) Journal of Applied Ontology, 1, pp. 51-69; Atkinson, R.W., Anderson, H.R., Strachan, D.P., Bland, J.M., Bremner, S.A., Ponce De Leon, A., Short-term associations between outdoor air pollution and visits to accident and emergency departments in London for respiratory complaints (1999) Eur Respir J, 13 (2), pp. 257-265; Hansell, A.L., Blangiardo, M., Fortunato, L., Floud, S., Kd, H., Fecht, D., Aircraft noise and cardiovascular disease near Heathrow airport in London: Small area study BMJ 2013, 347, pp. 1-10. , f5432; Stewart, J.A., Dundas, R., Howard, R.S., Rudd, A.G., Wolfe, D.A., Ethnic differences in incidence of stroke: Prospective study with stroke register (1999) BMJ, 318 (7189), pp. 967-971; Addo, J., Bhalla, A., Crichton, S., Rudd, A.G., McKevitt, C., Wolfe, D.A., Provision of acute stroke care and associated factors in a multiethnic population: Prospective study with the South London Stroke Register (2011) BMJ, 342, p. d744; Kelly, F.J., Anderson, H.R., Armstrong, B., Atkinson, R., Barratt, B., Beevers, S., The Impact of the Congestion Charging Scheme on Air Quality in London. Part 1. Emissions modelling and analysis of air pollution measurements (2011) Res Rep Health Eff Inst, 155, pp. 5-71; Alexandropoulou, K., Jv, V., Reid, F., Poullis, A., Kang, J., Temporal trends of Barrett’s oesophagus and gastro-oesophageal reflux and related oesophageal cancer over a 10-year period in England and Wales and associated proton pump inhibitor and H2RA prescriptions: A GPRD study (2013) Eur J Gastroenterol Hepatol, 25 (1), pp. 15-21; Read, J.D., Benson, J.R., Comprehensive coding (1986) Br J Healthcare Computing, 3, pp. 622-625; Allemang, D., Polikoff, I., TopBraid, a multiuser environment for distributed authoring of ontologies (2004) 3rd International Semantic Web Conference (ISWC 2004), , editors, Hiroshima, Japan, Springer Verlag; Kalyanpur, A., Parsia, B., Sirin, E., Grau, B.C., Hendler, J., Swoop: A web ontology editing browser (2006) Journal of Web Semantics, 2 (4), pp. 144-153; Erdman, M., Ontology engineering and plugin development with the NeOn Toolkit (2008) 5th Annual European Semantic Web Conference (ESWC 2008); Noy, N.F., Sintek, M., Decker, S., Crubézy, M., Fergerson, R.W., Musen, M.A., (2001) Creating Semantic Web Contents with Protégé-2000, pp. 60-71. , IEEE INTELLIGENT SYSTEMS: The Semantic Web; Baader, F., Horrocks, I., Sattler, U., Description logics as ontology languages for the semantic web (2605) Lecture Notes in Artificial Intelligence 2005, pp. 228-248; Motik, B., Shearer, R., Horrocks, I., Hypertableau Reasoning for Description Logics (2009) Journal of Artificial Intelligence Research, 36, pp. 165-228 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Conclusions: Our approach generated a resultant set of transformed OWL formatted files, which are in a query-able format to run individual queries, or can be easily converted into other more suitable formats for further analysis, and the transformation was faithful with no loss or anomalies. Our results have shown that the proposed method provides a promising general approach to address data heterogeneity. Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Managing Interoperability and Complexity in Health Systems”. Background: Data heterogeneity is one of the critical problems in analysing, reusing, sharing or linking datasets. Metadata, whilst adding semantic description to data, adds an additional layer of complexity in the heterogeneity of metadata descriptors themselves. This can be managed by using a predefined model to extract the metadata, but this can reduce the richness of the data extracted. Objectives: to link the South London Stroke Register (SLSR), the London Air Pollution toolkit (LAP) and the Clinical Practice Research Datalink (CPRD) while transforming data into the Web Ontology Language (OWL) format. Methods: We used a four-step transformation approach to prepare meta-descriptions, convert data, generate and update meta-classes and generate OWL files. We validated the correctness of the transformed OWL files by issuing queries and assessing results against the original source data. Results: We have transformed SLSR LAP and CPRD into OWL format. The linked SLSR and CPRD OWL file contains 3644 male and 3551 female patients. The linked SLSR and LAP OWL file shows that there are 17 out of 35 outward postcode areas, where no overlapping data can support further analysis between SLSR and LAP. © Schattauer 2015. ER - TY - JOUR T1 - Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature A1 - Liaw, S T A1 - Rahimi, A A1 - Ray, P A1 - Taggart, J A1 - Dennis, S A1 - de Lusignan, S A1 - Jalaludin, B A1 - Yeo, A E T A1 - Talaei-Khoei, A Y1 - 2013/// KW - Abstracting KW - Automated process KW - Automation KW - Chronic Disease KW - Chronic disease KW - Chronic disease management KW - Cochrane Library KW - Conceptual frameworks KW - Cross systems KW - Data Collection KW - Data quality KW - Data reduction KW - Decision support systems KW - Decision supports KW - Design KW - Disease Management KW - Diseases KW - English as a second language KW - English languages KW - Health KW - Health outcomes KW - Humans KW - Information Management KW - Information management KW - Information models KW - Information system KW - Information systems KW - Information theory KW - Interoperability KW - Medical Record Linkage KW - Medline KW - Ontological approach KW - Ontology KW - Ontology-based KW - Population health KW - Population statistics KW - Potential solutions KW - Realist KW - Research KW - Research Design KW - Research design KW - Research designs KW - Rigorous evaluation KW - Semantic interoperability KW - Semantics KW - Tool designs KW - accuracy KW - autism KW - breast cancer KW - central nervous system disease KW - chronic disease KW - chronic obstructive lung disease KW - decision support system KW - descriptive research KW - documentation KW - health KW - health care planning KW - human KW - hypertension KW - information processing KW - medical information KW - medical information system KW - medical literature KW - medical research KW - non insulin dependent diabetes mellitus KW - obesity KW - outcome assessment KW - priority journal KW - prostate cancer KW - quality control KW - review KW - semantics JF - International Journal of Medical Informatics VL - 82 LA - English IS - 1 SP - 10 EP - 24 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84870523868&doi=10.1016%2Fj.ijmedinf.2012.10.001&partnerID=40&md5=d1dfcc8de6326d6c932f38d2b74c00a0 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Liaw et al. - 2013 - Towards an ontology for data quality in integrated chronic disease management A realist review of the literature.pdf N1 - Cited By :32 Export Date: 15 March 2017 CODEN: IJMIF Correspondence Address: Liaw, S.T.; General Practice Unit, Fairfield Hospital, PO Box 5, Fairfield, NSW 1860, Australia; email: siaw@unsw.edu.au Cited By :52 Export Date: 10 September 2018 References: (2008) 2008-2013 Action Plan For The Global Strategy For The Prevention and Control of Noncommunicable Diseases: Prevent and Control Cardiovascular Diseases, Cancers, Chronic Respiratory Diseases and Diabetes, , WHO, World Health Organization, Geneva, (Report No.: 978 92 4 159741 8); Esselens, G., Westhovens, R., Verschueren, P., Effectiveness of an integrated outpatient care programme compared with present-day standard care in early rheumatoid arthritis (2009) Musculoskelet. Care, 7, pp. 1-16. , March (1); Grimmer-Somers, K., Dolejs, W., Atkinson, J., Worley, A., Integrated GP and allied health care for patients with type 2 diabetes (2008) Aust. Fam. Physician, 37, pp. 774-775. , September (9); Hammar, T., Rissanen, P., Perala, M.L., The cost-effectiveness of integrated home care and discharge practice for home care patients (2009) Health Policy, , March; Olsson, L.E., Hansson, E., Ekman, I., Karlsson, J., A cost-effectiveness study of a patient-centred integrated care pathway (2009) J. Adv. Nurs., 65, pp. 1626-1635. , August (8); Zwar, N., Harris, M., Griffiths, R., Roland, M., Dennis, S., Davies, G.P., Hasan, I., (2006) APHRI Stream Four: A Systematic Review of Chronic Disease Management, , Australian Primary Health Care Research Institute, Sydney; Kodner, D.L., Spreeuwenberg, C., Integrated care: meaning, logic, applications, and implications - a discussion paper (2002) Int. J. Integr. Care, 2, pp. e12; Bodenheimer, T., Wagner, E., Grumbach, K., Improving primary care for patients with chronic illness (2002) J. Am. Med. Assoc., 288, pp. 1775-1779. , October (14); Bodenheimer, T., Wagner, E.H., Grumbach, K., Improving primary care for patients with chronic illness: the chronic care model, part 2 (2002) J. Am. Med. Assoc., 288, pp. 1909-1914. , October (15); Smith, S., Allwright, S., O'Dowd, T., Effectiveness of shared care across the interface between primary and specialty care in chronic disease management (2007) Cochrane Datab. Syst. Rev., 3, pp. CD004910. , July; Ouwens, M., Wollersheim, H., Hermens, R., Hulscher, M., Grol, R., Integrated care programmes for chronically ill patients: a review of systematic reviews (2005) Int. J. Qual. Health Care, 17, pp. 141-146. , April (2); Gillies, A., Assessing and improving the quality of information for health evaluation and promotion (2000) Methods Inf. Med., 39 (3), p. 4; Huaman, M.A., Araujo-Castillo, R.V., Soto, G., Neyra, J.M., Quispe, J.A., Fernandez, M.F., Mundaca, C.C., Blazes, D.L., Impact of two interventions on timeliness and data quality of an electronic disease surveillance system in a resource limited setting (Peru): a prospective evaluation (2009) BMC Med. Inform. Decis. Making, 9. , March; Kiragga, A.N., Castelnuovo, B., Schaefer, P., Muwonge, T., Easterbrook, P.J., Quality of data collection in a large HIV observational clinic database in sub-Saharan Africa: implications for clinical research and audit of care (2011) J. Int. AIDS Soc., 14 (1); Azaouagh, A., Stausberg, J., Frequency of hospital-acquired pneumonia - comparison between electronic and paper-based patient records (2008) Pneumologie, 62, pp. 273-278. , May (5); Mitchell, J., Westerduin, F., Emergency department information system diagnosis: how accurate is it? (2008) Emerg. Med. J., 25, p. 784. , November (11); Moro, M.L., Morsillo, F., Can hospital discharge diagnoses be used for surveillance of surgical-site infections? (2004) J. Hosp. Infect., 56, pp. 239-241. , March (3); de Lusignan, S., Khunti, K., Belsey, J., Hattersley, A., van Vlymen, J., Gallagher, H., Millett, C., Majeed, A., A method of identifying and correcting miscoding, misclassification and misdiagnosis in diabetes: a pilot and validation study of routinely collected data (2010) Diabet. Med., 27, pp. 203-209; Soto, C., Kleinman, K., Simon, S., Quality and correlates of medical record documentation in the ambulatory care setting (2002) BMC Health Serv. Res., 2. , December (1); Liaw, S., Chen, H., Maneze, D., Taggart, J., Dennis, S., Vagholkar, S., Bunker, J., Health reform: is current electronic information fit for purpose? (2011) Emerg. Med. Australasia, , September; Liaw, S., Taggart, J., Dennis, S., Yeo, A., Data quality and fitness for purpose of routinely collected data - a case study from an electronic Practice-Based Research Network (ePBRN) (2011) American Medical Informatics Association Annual Symposium 2011, , Springer Verlag, Washington DC; Lain, S.J., Roberts, C.L., Hadfield, R.M., Bell, J.C., Morris, J.M., How accurate is the reporting of obstetric haemorrhage in hospital discharge data?. A validation study (2008) Aust. N. Z. J. Obstet. Gynaecol., 48, pp. 481-484. , October (5); Quan, H., Li, B., Saunders, L.D., Parsons, G.A., Nilsson, C.I., Alibhai, A., Ghali, W.A., Investigators, I., Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database (2008) Health Serv. Res., 43, pp. 1424-1441. , August (4); Hamilton, W.T., Round, A.P., Sharp, D., Peters, T.J., The quality of record keeping in primary care: a comparison of computerised, paper and hybrid systems (2003) Br. J. Gen. Pract., 53 (DECEMBER 497), pp. 929-933. , (Discussion 33); Thiru, K., Hassey, A., Sullivan, F., Systematic review of scope and quality of electronic patient record data in primary care (2003) Br. Med. J., 326, p. 1070. , May (398); Davis, P., Lay-Yee, R., Schug, S., Briant, R., Scott, A., Johnson, S., Adverse events regional feasibility study: indicative findings (2001) N. Z. Med. J., 114 (1131), pp. 203-205; Runciman, W., Webb, R., Helps, S., Thomas, E., Sexton, B., Studdert, D., A comparison of iatrogenic injury studies in Australia and the USA. II. Reviewer behaviour and quality of care (2000) Int. J. Qual. Health Care, 12 (5), pp. 379-388; Thomas, E., Studdert, D., Runciman, W., Webb, R., Sexton, E., Wilson, R., A comparison of iatrogenic injury studies in Australia and the USA. I. Context, methods, casemix, population, patient and hospital characteristics (2000) Int. J. Qual. Health Care, 12 (5), pp. 371-378; Vincent, C., Neale, G., Woloshynowych, M., Adverse events in British hospitals: preliminary retrospective record review (2001) Br. Med. J., 322, pp. 517-519. , March; Adaji, A., Schattner, P., Jones, K., The use of information technology to enhance diabetes management in primary care: a literature review (2008) Inform. Prim. Care, 16 (3), pp. 229-237; Liaw, S., Boyle, D., Primary care informatics and integrated care of chronic disease (2010) Health Informatics: An Overview, vol. 151, Studies in Health Technology and Informatics, , IOS Press, (Chapter 20, ISBN:978-1-60750-092-6), E. Hovenga, M. Kidd, S. Garde, C.H.L. Cossio (Eds.); Cummings, E., Showell, C., Roehrer, E., Churchill, B., Yee, K., Wong, M., Turner, P., (2010) Discharge, Referral and Admission: A Structured Evidence-based Literature Review, , eHealth Services Research Group, University of Tasmania (on behalf of the Australian Commission on Safety and Quality in Health Care, and the NSW Department of Health), Australia; (2009) Primary Health Care Reform in Australia, Report to Support Australia's First National Primary Health Care Strategy, , Commonwealth of Australia, Australian Government, Canberra; (2009) A Healthier Future For All Australians - Final Report of the National Health and Hospitals Reform Commission - June 2009, , National Health & Hospital Reform Commission, Commonwealth of Australia, Canberra, Ageing DoHa (Ed.); National Preventative Health Taskforce Australia: The Healthiest Country by 2020 - National Preventative Health Strategy - Overview, Commonwealth of Australia Department of Health and Ageing, Canberra, June 20, 2009, Report No.: Publications Approval Number P3-5457 Contract No.: ISBN:1-74186-925-0; Garling, P., Final Report of the Special Commission of Inquiry: Acute Care in NSW Public Hospitals, 2008 (2008), Overview, November 27, 2008 ed. NSW Government, Sydney; Bates, D., Gawande, A., Improving safety with information technology (2003) N. Engl. J. Med., 348, pp. 2526-2534; Rubin, D.L., Lewis, S.E., Mungall, C.J., Misra, S., Westerfield, M., Ashburner, M., Sim, I., Musen, M.A., National Center for Biomedical Ontology: advancing biomedicine through structured organization of scientific knowledge (2006) OMICS, 10, pp. 185-198. , Summer (2); Perez-Rey, D., Maojo, V., Garcia-Remesal, M., Alonso-Calvo, R., Billhardt, H., Martin-Sanchez, F., Sousa, A., ONTOFUSION: ontology-based integration of genomic and clinical databases (2006) Comput. Biol. Med., 36, pp. 712-730. , July-August (7-8); Pawson, R., Greenhalgh, T., Harvey, G., Walshe, K., Realist review - a new method of systematic review designed for complex policy interventions (2005) J. Health Serv. Res. Policy, 10 (SUPPL. 1), pp. 21-34; (2012) Protege User Documentation, , http://protege.stanford.edu/doc/users.html, Biomedical Informatics Unit, Stanford University, Palo Alto, Available from:, (cited 12.04.12); (2012) SNOMED Clinical Terms (SNOMED CT), , http://ihtsdo.org/fileadmin/user_upload/doc/, International Health Terminology Standard Development Organisation (IHTSDO), Available from:, (cited 12.04.12); (2012) Unified Medical Language System® (UMLS®), , http://www.nlm.nih.gov/research/umls/, U.S. National Library of Medicine. US National Library of Medicine, Bethesda, Available from:, [cited 12.04.12]; (2012) Medical Subject Headings (MESH), , http://www.nlm.nih.gov/mesh/, U.S. National Library of Medicine, U.S. National Library of Medicine, Bethesda, Available from:, (cited 12.04.12); Pinto, H.S., Ontologies: how can they be built? (2004) Knowl. Inform. Syst., 6 (4), pp. 441-464; Preece, A., Missier, P., Ernbury, S., Jin, B., Greenwood, M., An ontology-based approach to handling information quality in e-science (2008) Concurr. Comput. Pract. Exp., 20, pp. 253-264. , March (3); Fox, M., Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (1992) Lecture Notes in Artificial Intelligence #604, pp. 25-34. , Springer-Verlag, Berlin, F.J. Belli FaR (Ed.); Baader, F., Horrocks, I., Sattler, U., Chapter 3. Description logics (2007) Handbook of Knowledge Representation, , Elsevier, Berlin, V.L. Frank van Harmelen, Bruce Porter (Eds.); Ontology-based multi-agent systems support human disease study and control (2005) International Conference on Self Organization and Adaptation of Multi-Agent and Grid Systems (SOAS); 2005 Dec 11 2005, , IOS Press, Glasgow, UK/Amsterdam, The Netherlands, *.M. Hadzic, E. Chang (Eds.); Ying, W., Wimalasiri, J., Ray, P., Chattopadhyay, S., Wilson, C., An ontology driven multi-agent approach to integrated e-health systems (2010) Int. J. E-Health Med. Commun., 1 (1), p. 12; Kuziemsky, C., Lau, F., A four stage approach for ontology-based health information system design (2010) Artif. Intell. Med., 50, p. 18; Valencia-Garcia, R., Fernandez-Breis, J.T., Ruiz-Martinez, J.M., Garcia-Sanchez, F., Martinez-Bejar, R., A knowledge acquisition methodology to ontology construction for information retrieval from medical documents (2008) Expert Syst., 25, pp. 314-334. , July (3); Van Buggenhout, C., Ceusters, W., A novel view on information content of concepts in a large ontology and a view on the structure and the quality of the ontology (2005) Int. J. Med. Inf., 74, pp. 125-132. , March (2-4); Wang, R.Y., A product perspective on total data quality management (1998) CACM, 41, pp. 58-65. , February (2); (2009) The CIHI Data Quality Framework, , Canadian Institute for Health Information, CIHI, Ottawa, Ontario; Redman, T., Measuring data accuracy (2005) Information Quality, p. 21. , ME Sharpe, Inc., Armonk NY, R. Wang, E. Rea (Eds.); Wand, Y., Wang, R.Y., Anchoring data quality dimensions in ontological foundations (1996) CACM, 39, pp. 86-95. , November (11); Wang, R., Strong, D., Guarascio, L., Beyond accuracy: what data quality means to data consumers (1996) J. Manage. Inform. Syst., 12 (4), pp. 5-33; Jordan, K., Clarke, A., Symmons, D., Fleming, D., Porcheret, M., Kadam, U., Croft, P., Measuring disease prevalence: a comparison of musculoskeletal disease using four general practice consultation databases (2007) Br. J. Gen. Pract., 57, pp. 7-14; Measuring the quality of data models: an evaluation of the use of quality metrics in practice (2003) 11th European Conf on Information Systems, , D. Moody (Ed.); de Lusignan, S., Hague, N., van Vlymen, J., Kumarapeli, P., Routinely-collected general practice data are complex, but with systematic processing can be used for quality improvement and research (2006) Inform. Prim. Care, 14 (1), pp. 59-66; de Lusignan, S., van Weel, C., The use of routinely collected computer data for research in primary care: opportunities and challenges (2006) Fam. Pract., 23, pp. 253-263. , April (2); Arts, D., de Keizer, N., Scheffer, G.J., de Jonge, E., Quality of data collected for severity of illness scores in the Dutch National Intensive Care Evaluation (NICE) registry (2002) Intens. Care Med., 28, pp. 656-659. , May (5); Britt, H., Miller, G., Bayrarn, C., The quality of data on general practice - a discussion of BEACH reliability and validity (2007) Aust. Fam. Physician, 36, pp. 36-40. , January-February (1-2); de Lusignan, S., Metsemakers, J., Houwink, P., Gunnarsdottir, V., van der Lei, J., Routinely collected general practice data: goldmines for research? A report of the European Federation for Medical Informatics Primary Care Informatics Working Group (EFMI PCIWG) from MIE2006, Maastricht, The Netherlands (2006) Inform. Prim. Care, 14 (3), pp. 203-209; Will, L., (2007) Glossary of Terms Relating to Thesauri and Other Forms of Structured Vocabulary for Information Retrieval, , http://www.willpowerinfo.co.uk/glossary.htm, Available from:; (2003) What are the Differences Between a Vocabulary, a Taxonomy, a Thesaurus, an Ontology, and a Meta-model?, , http://www.metamodel.com/article.php%3Fstory=2003011223271, Jernst, Available from:; Vanopstal, K., Buysschaert, J., Vander Stichele, R., Laureys, G., Vocabularies and retrieval tools in biomedicine: disentangling the terminological knot (2009) J. Med. Syst., 12. , November; Gruber, T.R., Toward principles for the design of ontologies used for knowledge sharing (1995) Int. J. Hum.-Comput. Stud., 43 (5-6); Jacquelinet, C., Burgun, A., Delamarre, D., Strang, N., Djabbour, S., Boutin, B., Le Beux, P., Developing the ontological foundations of a terminological system for end-stage diseases, organ failure, dialysis and transplantation (2003) Int. J. Med. Inf., 70 (2-3), pp. 317-328; Mabotuwana, T., Warren, J., An ontology-based approach to enhance querying capabilities of general practice medicine for better management of hypertension (2009) Artif. Intell. Med., 47 (2), pp. 87-103; Topalis, P., Dialynas, E., Mitraka, E., Deligianni, E., Siden-Kiamos, I., Louis, C., A set of ontologies to drive tools for the control of vector-borne diseases (2011) J. Biomed. Inform., 44, pp. 42-47. , February (1); Brüggemann, S., Grüning, F., Using ontologies providing domain knowledge for data quality management (2009) Stud. Comput. Intel., 221, pp. 187-203; Min, H., Manion, F.J., Goralczyk, E., Wong, Y.N., Ross, E., Beck, J.R., Integration of prostate cancer clinical data using an ontology (2009) J. Biomed. Inform., 42, pp. 1035-1045. , December (6); Young, L., Tu, S.W., Tennakoon, L., Vismer, D., Astakhov, V., Gupta, A., Grethe, J.S., McAuliffe, M.J., Ontology driven data integration for autism research (2009) 22nd IEEE International Symposium on Computer-Based Medical Systems, pp. 54-60. , IEEE; O'Donoghue, J., Herbert, J., O'Reilly, P., Sammon, D., Towards improved information quality: the integration of body area network data within electronic health records (2009) Ambient Assistive Health and Wellness Management in the Heart of the City, Proceeding, pp. 299-302. , M. Mokhtari, I. Khalil, J. Bauchet, D. Zhang, C. Nugent (Eds.); Orme, A.M., Yao, H., Etzkorn, L.H., Indicating ontology data quality, stability, and completeness throughout ontology evolution (2007) J. Softw. Maint. Evol. Res. Pract., 19, pp. 49-75. , January-February (1); Vorochek, O., Biletskiy, Y., Toward assessing data quality of ontology matching on the web CNSR (2007) 2007 Proceedings of the Fifth Annual Conference on Communication Networks and Services Research, , Available from Go to ISI://000246988200045 (serial on the Internet); Nimmagadda, S.L., Nimmagadda, S.K., Dreher, H., Ontology based data warehouse modeling and managing ecology of human body for disease and drug prescription management (2008) 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies, pp. 465-473. , IEEE; Abidi, S., Ontology-based knowledge modeling to provide decision support for comorbid diseases (2011) The 19th European Conference in Artificial Intelligence, pp. 27-39; Buranarach, M., Chalortham, N., Chatvorawit, P., Thein, Y., Supnithi, T., (2009) An Ontology-based Framework for Development of Clinical Reminder System to Support Chronic Disease Healthcare, , http://text.hlt.nectec.or.th/ontology/sites/default/files/reminder_isbme09_cr_0.pdf, Available from; Chalortham, N., Buranarach, M., Supnithi, T., (2009) Ontology Development for Type II Diabetes Mellitus Clinical Support System, , http://text.hlt.nectec.or.th/ontology/sites/default/files/CRdm2css_0.pdf, Available from:; Hadzic, M., Dillon, D.S., Dillon, T.S., Use and modeling of multi-agent systems in medicine (2009) Proceedings of the 20th International Workshop on Database and Expert Systems Application, , A.M. Tjoa, R.R. Wagner (Eds.); Jara, A.J., Blaya, F.J., Zamora, M.A., Skarmeta, A.F.G., (2009) An Ontology and Rule Based Intelligent Information System to Detect and Predict Myocardial Diseases, , IEEE, IEEE, New York; Ontology based personalized modeling for chronic disease risk analysis: an integrated approach (2009) The 15th International Conference on Advances in Neuro-Information Processing 2008, , Springer-Verlag, Berlin/Heidelberg, *.A. Verma, N. Kasabov, A. Rush, Q. Song (Eds.); Baneyx, A., Charlet, J., Jaulent, M.C., Building an ontology of pulmonary diseases with natural language processing tools using textual corpora (2007) Int. J. Med. Inf., 76 (FEBRUARY MARCH 2 3), pp. 208-215. , (Proceedings Paper); Coltell, O., Arregui, M., Perez, C., Domenech, M.A., Corella, D., Chalmeta, R., Building an ontology on genomic epidemiology of cardiovascular diseases (2004) 8th World Multi-Conference on Systemics, Cybernetics, and Informatics, Vol Xvi, Proceedings, , N. Callaos, M. Sanchez, J.M. Pineda (Eds.); Gupta, A., Ludäscher, B., Grethe, J.S., Martone, M.E., Towards a formalization of disease-specific ontologies for neuroinformatics (2003) Neural Netw., 16 (9), pp. 1277-1292; Gedzelman, S., Simonet, M., Bernhard, D., Diallo, G., Palmer, P., Building an ontology of cardio-vascular diseases for concept-based information retrieval (2005) Computers in Cardiology 2005, vol. 32, pp. 255-258. , IEEE; McGarry, K., Garfield, S., Wermter, S., Auto-extraction, representation and integration of a diabetes ontology using Bayesian networks (2007) Twentieth IEEE International Symposium on Computer-Based Medical Systems, Proceedings, pp. 612-617. , P. Kokol, V. Podgorelec, D. MiceticTurk, M. Zorman, M. Verlic (Eds.); Jeon, B.J., Ko, I.Y., (2007) Ontology-based Semi-automatic Construction of Bayesian Network Models for Diagnosing Diseases in e-Health Applications, , IEEE Computer Soc., Los Alamitos, D. Howard, P.K. Rhee, S. Halgamuge, S.J. Yoo (Eds.); Maragoudakis, M., Lymberopoulos, D., Fakotakis, N., Spiropoulos, K., A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments - a case study for pulmonary diseases (2008) 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vols. 1-8, pp. 3807-3810. , Ieee; Tu, S., Tennakoon, L., O'Connor, M., Shankar, R., Das, A., Using an integrated ontology and information model for querying and reasoning about phenotypes: the case of autism (2008) AMIA Annu Symp Proc., pp. 727-731; Colombo, G., Merico, D., Boncoraglio, G., De Paoli, F., Ellul, J., Frisoni, G., Nagy, Z., Antoniotti, M., An ontological modeling approach to cerebrovascular disease studies: the NEUROWEB case (2010) J. Biomed. Inform., 43 (4), pp. 469-484; Ganendran, G., Tran, Q., Ganguly, P., Ray, P., Low, G., An ontology-driven multi-agent approach for healthcare (2002) HIC, pp. 464-469; Ganguly, P., Ray, P., Parameswaran, N., Semantic interoperability in telemedicine through ontology-driven services (2005) Telemed. e-Health, 11 (3), p. 8; Collier, N., Kawazoe, A., Jin, L., Shigematsu, M., Dien, D., Barrero, R.A., Takeuchi, K., Kawtrakul, A., A multilingual ontology for infectious disease surveillance: rationale, design and challenges (2006) Lang. Res. Eval., 40 (3-4), pp. 405-413; Wand, Y., Wang, Y., Anchoring data quality dimensions in ontological foundations (1996) CACM, 36 (11), p. 10; Choquet, R., Qouiyd, S., Ouagne, D., Pasche, E., Daniel, C., Boussaïd, O., Jaulent, M., The Information Quality Triangle: a methodology to assess clinical information quality (2010) Stud. Health Technol. Inform., 160 (PART 1), pp. 699-703; Hogan, W., Wagner, M., Accuracy of data in computer-based patient records (1997) J. Am. Med. Inform. Assoc., 4 (5), pp. 342-355; Michalakidis, G., Kumarapeli, P., Ring, A., van Vlymen, J., Krause, P., de Lusignan, S., A system for solution-orientated reporting of errors associated with the extraction of routinely collected clinical data for research and qua N2 - Purpose: Effective use of routine data to support integrated chronic disease management (CDM) and population health is dependent on underlying data quality (DQ) and, for cross system use of data, semantic interoperability. An ontological approach to DQ is a potential solution but research in this area is limited and fragmented. Objective: Identify mechanisms, including ontologies, to manage DQ in integrated CDM and whether improved DQ will better measure health outcomes. Methods: A realist review of English language studies (January 2001-March 2011) which addressed data quality, used ontology-based approaches and is relevant to CDM. Results: We screened 245 papers, excluded 26 duplicates, 135 on abstract review and 31 on full-text review; leaving 61 papers for critical appraisal. Of the 33 papers that examined ontologies in chronic disease management, 13 defined data quality and 15 used ontologies for DQ. Most saw DQ as a multidimensional construct, the most used dimensions being completeness, accuracy, correctness, consistency and timeliness. The majority of studies reported tool design and development (80%), implementation (23%), and descriptive evaluations (15%). Ontological approaches were used to address semantic interoperability, decision support, flexibility of information management and integration/linkage, and complexity of information models. Conclusion: DQ lacks a consensus conceptual framework and definition. DQ and ontological research is relatively immature with little rigorous evaluation studies published. Ontology-based applications could support automated processes to address DQ and semantic interoperability in repositories of routinely collected data to deliver integrated CDM. We advocate moving to ontology-based design of information systems to enable more reliable use of routine data to measure health mechanisms and impacts. © 2012 Elsevier Ireland Ltd. ER - TY - JOUR T1 - Optimising the use of observational electronic health record data: Current issues, evolving opportunities, strategies and scope for collaboration A1 - Liaw, S.-T. A1 - Powell-Davies, G A1 - Pearce, C A1 - Britt, H A1 - McGlynn, L A1 - Harris, M F Y1 - 2016/// KW - Australia KW - Computer Security KW - Congresses as Topic KW - Cooperative Behavior KW - Electronic Health Records KW - General Practice KW - Humans KW - Privacy KW - Research KW - Software KW - change management KW - computer program KW - computer security KW - cooperation KW - electronic health record KW - electronic medical record KW - ethics KW - general practice KW - human KW - medicare KW - model KW - organization KW - organization and management KW - patent KW - privacy KW - research KW - responsibility KW - software KW - standards JF - Australian Family Physician VL - 45 IS - 3 SP - 153 EP - 156 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962253652&partnerID=40&md5=9e07378b61183dc2790a9f5b278a789b N1 - Cited By :4 Export Date: 10 September 2018 References: Pearce, C., Shearer, M., Gardner, K., Kelly, J., A division's worth of data (2011) Aust Fam Physician, 40, pp. 167-170; Liaw, S.T., Taggart, J., Dennis, S., Yeo, A., Data quality and fitness for purpose of routinely collected data-A case study from an electronic Practice-Based Research Network (ePBRN) (2011) American Medical Informatics Association Annual Symposium 2011, , Washington, DC: Springer Verlag; Pearce, C., Bainbridge, M., A personally controlled electronic health record for Australia (2014) J Am Med Inform Assoc, 21, pp. 707-713; Arend, J., Tsang-Quinn, J., Levine, C., Thomas, D., The patient-centered medical home: History, components, and review of the evidence (2012) Mt Sinai J Med, 79, pp. 433-450; Sinsky, C.A., The patient-centered medical home neighbor: A primary care physician's view (2011) Ann Intern Med, 154, pp. 61-62; Yee, J.H.F., The patient-centered medical home neighbor: A subspecialty physician's view (2011) Ann Intern Med, 154, pp. 63-64; (2001) Crossing the quality chasm: A new health system for the 21st century, , Washington, DC: National Academies Press; (2009) A healthier future for all Australians-Final report of the National Health and Hospitals Reform Commission, , Canberra: DOH; Krist, A., Beasley, J.W., Crosson, J.C., Kibbe, D.C., Electronic health record functionality needed to better support primary care (2014) J Am Med Inform Assoc, 21, pp. 764-771; Kuhn, T., Basch, P., Barr, M., Yackel, T., Clinical documentation in the 21st century: Executive summary of a policy position paper from the American College of Physician. Clinical Documentation in the 21st Century (2015) Ann Intern Med, 162, pp. 301-303; (1997) The computer-based patient record: An essential technology for health care, , Revised edn. Dick RS, Steen EB, Detmer DE, editors. Washington, DC: National Academies Press; (2002) Report to health ministers: Electronic decision support in Australia, , Canberra: National Health Information Management Advisory Committee; (2000) A health information network for Australia, , Canberra: National Electronic Health Records Taskforce; de Lusignan, S., Liaw, S.T., Michalakidis, G., Jones, S., Defining data sets and creating data dictionaries for quality improvement and research in chronic disease using routinely collected data: An ontology driven approach (2011) Inform Prim Care, 19, pp. 127-134; de Lusignan, S., Pearce, C., Shaw, N., What are the barriers to conducting international research using routinely collected primary care data? (2011) Stud Health Technol Inform, 165, pp. 135-140; de Lusignan, S., Liaw, S.T., Krause, P., Key concepts to assess the readiness of data for international research: Data quality, lineage and provenance, extraction and processing errors, traceability, and curation (2011) Yearb Med Inform, 6, pp. 112-121; Liyanage, H., Liaw, S.T., de Lusignan, S., Accelerating the development of an information ecosystem in health care, by stimulating the growth of safe intermediate processing of health information (IPHI) (2012) Inform Prim Care, 20, pp. 81-86; Liyanage, H., Liaw, S., de Lusignan, S., Reporting of Studies Conducted using Observational Routinely Collected Data (RECORD) statement: Call for contributions from the clinical informatics community (2012) Inform Prim Care, 20, pp. 221-224; Liyanage, H., de Lusignan, S., Liaw, S.T., Kuziemsky, C.E., Big data usage patterns in the health care domain: A use case driven approach applied to the assessment of vaccination benefits and risks (2014) IMIA Yearb Med Inform, 9, pp. 27-35; Liaw, S.T., Chen, H., Maneze, D., Health reform: Is current electronic information fit for purpose? (2011) Emerg Med Australas, 24, pp. 57-63; Halamka, J., Overhage, J., Ricciardi, L., Rishel, W., Shirky, C., Diamond, C., Exchanging health information: Local distribution, national coordination (2005) Health Aff(Millwood), 24, pp. 1170-1179; Liaw, S., Taggart, J., Yu, H., de Lusignan, S., Data extraction from electronic health records-Existing tools may be unreliable and potentially unsafe (2013) Aust Fam Physician, 42, pp. 820-823; Liyanage, H., Liaw, S.T., Kuziemsky, C., de Lusignan, S., Ontologies to improve chronic disease management research and quality improvement studies-A conceptual framework (2013) Medinfo 2013, , Aronsky D, Leong S, editors. Copenhagen: Elsevier Press; Liaw, S.T., Rahimi, A., Ray, P., Towards an ontology for data quality in integrated chronic disease: A realist review of the literature (2013) Int J Med Informatics, 82, pp. 10-24; Mazza, D., Pearce, C., Huang, N., Liaw, S.T., Britt, H., (2014) Workshop: Using routinely collected general practice data to inform practice and policy: What do we have now, where do we need to go and how are we going to get there? Primary Health Care Conference, , Canberra: PHC Research Information Service; Greiver, M., Tu, K., Sullivan, F., Using EMR data and data linkages for primary care research: International perspectives on challenges and solutions (2014) Forum-NAPCRG Annual Meeting, , 22 Nov 2014. New York: NAPCRG; Liaw, S.T., Pearce, C., Liyanage, H., Cheah-Liaw, G., de Lusignan, S., An integrated organisation-wide data quality management and information governance framework: Theoretical underpinnings (2014) Inform Prim Care, 21, pp. 1-8 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background With increasing computerisation in general practice, national primary care networks are mooted as sources of data for health services and population health research and planning. Existing data collection programs - MedicinesInsight, Improvement Foundation, Bettering the Evaluation and Care of Health (BEACH) - vary in purpose, governance, methodologies and tools. General practitioners (GPs) have significant roles as collectors, managers and users of electronic health record (EHR) data. They need to understand the challenges to their clinical and managerial roles and responsibilities. Objective The aim of this article is to examine the primary and secondary use of EHR data, identify challenges, discuss solutions and explore directions. Discussion Representatives from existing programs, Medicare Locals, Local Health Districts and research networks held workshops on the scope, challenges and approaches to the quality and use of EHR data. Challenges included data quality, interoperability, fragmented governance, proprietary software, transparency, sustainability, competing ethical and privacy perspectives, and cognitive load on patients and clinicians. Proposed solutions included effective change management; transparent governance and management of intellectual property, data quality, security, ethical access, and privacy; common data models, metadata and tools; and patient/community engagement. Collaboration and common approaches to tools, platforms and governance are needed. Processes and structures must be transparent and acceptable to GPs. © The Royal Australian College of General Practitioners 2016. ER - TY - CONF T1 - The Danish national health informatics strategy A1 - Lippert, S A1 - Kverneland, A Y1 - 2003/// KW - EHR KW - Health Care Sector KW - IT in health care KW - National strategy KW - interoperability VL - 95 SP - 845 EP - 850 N1 - Cited By :6 Export Date: 10 September 2018 References: http://www.im.dk/publikationer/Healthcare/healthcare, Health Care in Denmark, Ministry of Health May 2001.pdf (November 2002); http://www.euro.who.int/observatory/CtryInfo/CtryInfoRes?Country=DEN, Country Information, Denmark (November 2002); http://www.medcom, EDI-toppen.dk (Nov. 2002); http://www.im.dk/Index/publikationer.asp, HEP-projektet. Handlingsplan for Elektroniske Patientjournaler. Ministry of Health, August 1996 (November 2002); http://www.im.dk/Index/publikationer.asp, National strategi for IT i sygehusvxsenet 2000-2002. Ministry of Health, November 1999 (November 2002); http://www.sst.dk/publikationer/index.asp#G, Grundstruktur for Elektronisk Patientjournal, version 1.01 (November 2002); Lone, A., Petersen Jan, A., Conceptual model for documentation of clinical information in the her (2003) Proceedings, MIE; http://www.im.dk/Index/dokumentoversigt.asp, National IT-strategi for sundhedsvaesenet 2003-2007. Hen ingsudkast. Ministry for the Interior and Health, May 2002?. (November 2002)UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-68349084330&doi=10.3233%2f978-1-60750-939-4-845&partnerID=40&md5=2b2d108da1d2c2c3ef34b75fd8377d2d RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The central vision for the future information systems in the Danish health care sector is one of a generally accepted, common information model enabling comprehensive digital reuse of shared clinical data. A generic 'Basic-EHR-structure' has been developed for this purpose by the National Board of Health from a thorough analysis of the production of clinical information. The strategy contributes to the achievement of the national political goals for the health care sector and describes four important steps to be made by the health care IT systems in order to reach full interoperability and digital reusability of clinical information. Some important initiatives of the strategy are a national terminology server, coordinated implementation of EHRs, and the Public Health Information Portal. ER - TY - JOUR T1 - Web-based infectious disease reporting using XML forms A1 - Liu, Danhong A1 - Wang, Xia A1 - Pan, Feng A1 - Xu, Yongyong A1 - Yang, Peng A1 - Rao, Keqin Y1 - 2008/09// KW - Arsenic compounds KW - Bioassay KW - China KW - Communicable Diseases KW - Data elements KW - Data items KW - Data sets KW - Data-input (DI) KW - Document formats KW - Early stages KW - Electronic data KW - Electronic data interchange KW - Electronic health KW - Extensible markup language (XML) KW - Health KW - Health Information Systems (HIS) KW - Health information systems KW - Hospital Information Systems KW - Hospital information systems KW - Hospitals KW - Hypertext systems KW - Infectious diseases KW - Information infrastructures KW - Information management KW - Information science KW - Information sharing KW - Information systems KW - Information theory KW - Information use KW - Interchanges KW - Internet KW - Interoperable KW - Intersections KW - Ireland KW - Markup languages KW - Microarrays KW - National levels KW - Programming Languages KW - Public Health KW - Public health KW - Public health information systems KW - Query languages KW - Real time systems KW - Real-time data KW - Semantics KW - Standardization KW - Standards KW - Surveillance System (MSS) KW - Systems Integration KW - Transmission of data KW - Work flows KW - XML KW - XML documents KW - XML-Schema KW - article KW - electronic data interchange KW - electronic medical record KW - hospital information system KW - human KW - infection control KW - information processing KW - information system KW - markup language KW - medical information system KW - priority journal KW - public health service KW - semantics KW - standard PB - Elsevier JF - International Journal of Medical Informatics VL - 77 IS - 9 SP - 630 EP - 640 DO - 10.1016/j.ijmedinf.2007.10.011 UR - https://www.sciencedirect.com/science/article/pii/S1386505607001864?via%3Dihub UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-47049126126&doi=10.1016%2Fj.ijmedinf.2007.10.011&partnerID=40&md5=a0aa51b99b5c0e239a2df14a545282a8 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Liu et al. - 2008 - Web-based infectious disease reporting using XML forms.pdf N1 - From Duplicate 2 (Web-based infectious disease reporting using XML forms - Liu, D; Wang, X; Pan, F; Xu, Y; Yang, P; Rao, K) Cited By :15 Export Date: 5 April 2018 N2 - Objective: Exploring solutions for infectious disease information sharing among hospital and public health information systems is imperative to the improvement of disease surveillance and emergent response. This paper aimed at developing a method to directly transmit real-time data of notifiable infectious diseases from hospital information systems to public health information systems on the Internet by using a standard eXtensible Markup Language (XML) format. Methods: The mechanism and work flow by which notifiable infectious disease data are created, reported and used at health agencies in China was evaluated. The capacity of all participating providers to use electronic data interchange to submit transactions of data required for the notifiable infectious disease reporting was assessed. The minimum data set at national level that is required for reporting for national notifiable infectious disease surveillance was determined. The standards and techniques available worldwide for electronic health data interchange, such as XML, HL7 messaging, CDA and ATSM CCR, etc. were reviewed and compared, and an XML implementation format needed for this purpose was defined for hospitals that are able to access the Internet to provide a complete infectious disease reporting. Results: There are 18,703 county or city hospitals in China. All of them have access to basic information infrastructures including computers, e-mail and the Internet. Nearly 10,000 hospitals possess hospital information systems used for electronically recording, retrieving and manipulating patients' information. These systems collect 23 data items required in the minimum data set for national notifiable infectious disease reporting. In order to transmit these data items to the disease surveillance system and local health information systems instantly and without duplication of data input, an XML schema and a set of standard data elements were developed to define the content, structure and semantics of the data set. These standards make it possible to view and analyse the data accurately outside the hospital information systems in many different document formats. The paper also identified other issues involved in notifiable disease reporting in the future, such as the adoption of approved vocabulary standards and implementation problems such as the route, secure transfer, parsing, and objective identifying of the XML message. Conclusions: XML is an increasingly important standard for exchange and transmission of data between disparate applications and systems. As in its early stages of developing an interoperable health information system in China, the XML document structures could be a way to exchange the notifiable case information among interest parties on the web at present. © 2007 Elsevier Ireland Ltd. All rights reserved. ER - TY - CONF T1 - A lab-EMR interoperability profile as an ehealth architecture component for resource-constrained settings A1 - Lober, W B A1 - Revere, D A1 - Hills, R Y1 - 2010/// KW - Clinical Laboratory Information Systems KW - Clinical laboratory information systems KW - Computerized medical record systems KW - Database Management Systems KW - Developing countries KW - Electronic Health Records KW - Health Care Rationing KW - Health Resources KW - Information Storage and Retrieval KW - Medical Record Linkage KW - Models, Organizational KW - Public health informatics KW - Systems integration KW - United States KW - Washington KW - conference paper KW - data base KW - electronic medical record KW - health care organization KW - hospital information system KW - information retrieval KW - medical record KW - methodology KW - nonbiological model KW - organization and management VL - 160 SP - 257 EP - 261 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649515643&doi=10.3233%2F978-1-60750-588-4-257&partnerID=40&md5=cf4b251be96769712a570d1f977459f5 N1 - Cited By :2 Export Date: 10 September 2018 References: Marchibroda, J.M., Health information exchange policy and evaluation (2007) J. Biomed. Inform, 40 (6 SUPPL.), pp. S11-S16; (2008), Information Technology Association of Canada. Introduction to Ontario's e-Health Blueprint and Reference Architecture Version 2.7. March; Bailey, C., Boucher, P., Spohr, M., Whitaker, P., Interoperability standards for health information systems (2008) Making the EHealth Connection: Global Partnerships, , Local Solutions. July, Bellagio Italy; Hills, R.A., Lober, W.A., Painter, I.S., Biosurveillance, case reporting, and decision support: Public health interactions with a health information exchange (2008) Biosurveillance and Biosecurity, pp. 10-21. , Istrail S, Pevzner P and Waterman M, eds, Berlin: Springer; Lober, W.B., Wagner, S., Quiles, C., Development and implementation of a loosely coupled, multi-site, networked and replicated electronic medical record in Haiti (2009) Proc. of SOSP Workshop on Networked Systems for Developing Regions; Nelson, J.W., Lamothe, R., Boncy, J., Coq, R.L., Cassagnol, R., Lober, W., Quiles, Q., Sutton, P., Envisioning options for integrated public health information systems for low resource settings: Components, connections, partners, strategies (2008) Proc. of Global Partners in Public Health Informatics Conference; (2008) IHE Laboratory Technical Framework, Vol. 1 (LAB-TF-1) Profiles. (version 2.1), , IHE International, Aug RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Implementation of computerized systems in resource-constrained settings have been gaining traction as a means of improving the delivery of health care, the use and reuse of information, and providing a standards-based capacity for assessing the process and impact of health care. In a resource-constrained environment, systems are often implemented as stand-alone entities focused on specific care activities (for example, delivering antiretroviral therapy). As such, in many countries, taking a generalized approach to linking electronic medical record systems with laboratory information systems (EMR-LIS) is an important area in which to achieve interoperability. In this paper we describe a scenario of use and information interaction interoperability profile based on our experience implementing EMR-LIS integration in two resource-constrained settings. Of significance, the profile emphasizes queued matching in order to avoid mutual dependence while achieving interoperability between systems. © 2010 IMIA and SAHIA. All rights reserved. ER - TY - CONF T1 - A semantic web application framework for health systems interoperability A1 - Lopes, P A1 - Oliveira, J L Y1 - 2011/// KW - Application deployment KW - Bioinformatics KW - Clinical practices KW - Computer programming KW - Health KW - Health care KW - Health systems KW - Heterogeneous data KW - Human genomes KW - Humanism KW - Humanities KW - Humans KW - Interoperability KW - Interoperability framework KW - Knowledge management KW - Medical education KW - Medical profession KW - Patient care KW - Semantic Web KW - Semantic web applications KW - Semantics KW - Software KW - Software solution KW - Software stacks KW - bioinformatics KW - healthcare interoperability KW - semantic exploration KW - semantic integration KW - semantic web SP - 87 EP - 90 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-83255173885&doi=10.1145%2F2064747.2064768&partnerID=40&md5=d3fe4867205ee2afde373a407eb39c65 N1 - Cited By :4 Export Date: 10 September 2018 References: Belleau, F., Nolin, M.-A., Tourigny, N., Rigault, P., Morissette, J., Bio2RDF: Towards a mashup to build bioinformatics knowledge systems (2008) Journal of Biomedical Informatics, 41, pp. 706-716; Wilkinson, M.D., Vandervalk, B., McCarthy, L., (2009) SADI Semantic Web Services - 'Cause You Can't Always GET What You Want!; Bhagat, J., Tanoh, F., Nzuobontane, E., Laurent, T., Orlowski, J., Roos, M., Wolstencroft, K., Goble, C.A., BioCatalogue: A universal catalogue of web services for the life sciences (2010) Nucleic Acids Research, 38 (SUPPL. 2), pp. 689-694; Slater, T., Bouton, C., Huang, E.S., Beyond data integration (2008) Drug Discovery Today, 13, pp. 584-589; Kozhenkov, S., Dubinina, Y., Sedova, M., Gupta, A., Ponomarenko, J., Baitaluk, M., BiologicalNetworks 2.0 - An integrative view of genome biology data (2010) BMC Bioinformatics, 11, p. 610; Cannata, N., Schroder, M., Marangoni, R., Romano, P., A Semantic Web for bioinformatics: Goals, tools, systems, applications (2008) BMC Bioinformatics, 9 (SUPPL. 4), pp. S1; Berners-Lee, T., Hendler, J., Lassila, O., The Semantic Web (2001) Sci Am, pp. 34-43; Miller, E.J., An Introduction to the Resource Description Framework (2001) Journal of Library Administration, 34, pp. 245-255; Uschold, M., Gruninger, M., Ontologies: Principles, Methods and Applications (1996) Knowledge Engineering Review, 11, pp. 93-155; Stevens, R., Goble, C.A., Bechhofer, S., Ontology-based knowledge representation for bioinformatics (2000) Brief Bioinform, 1 (4), pp. 398-414; Hepp, M., Semantic Web and semantic Web services: Father and son or indivisible twins? (2006) Internet Computing, 10, pp. 85-88. , IEEE; Almeida, J., Deus, H., Maass, W., S3DB core: A framework for RDF generation and management in bioinformatics infrastructures (2010) BMC Bioinformatics, 11, p. 387; Kiryakov, A., Ognyanov, D., Manov, D., (2005) OWLIM - A Pragmatic Semantic Repository for OWL, , Springer Berlin / Heidelberg; Lopes, P., Dalgleish, R., Oliveira, J.L., WAVe: Web Analysis of the Variome (2011) Human Mutation, p. 32; Ring, H.Z., Kwok, P.-Y., Cotton, R.G.H., Human Variome Project: An international collaboration to catalogue human genetic variation (2006) Pharmacogenomics, 7 (7), pp. 969-972. , http://www.futuremedicine.com/doi/full/10.2217/14622416.7.7.969, DOI 10.2217/14622416.7.7.969; Webb, A.J., Thorisson, G.A., Brookes, A.J., An informatics project and online "Knowledge Centre" supporting modern genotype-to-phenotype research (2011) Human Mutation, 32 (5), pp. 543-550 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Relevant biomedical advances happen daily, and the medical profession relies on this evolution to deliver an improved patient care. In addition, the growing magnitude of data generated by biomedical software and hardware since the initial discovery of the human genome is remarkable in size and variety. Hence, best-of-breed software solutions are at best a couple years behind clinical practice demands. In this paper we detail an innovative Semantic Web interoperability framework, which provides developers with a complete software stack for semantic application deployment. Interoperability is the defining feature of this framework. On the one hand, new instances are able to integrate several types of distributed and heterogeneous data. On the other hand, collected data are made available through a public SPARQL endpoint. © 2011 ACM. ER - TY - JOUR T1 - COEUS: "semantic web in a box" for biomedical applications. A1 - Lopes, Pedro A1 - Oliveira, José Luís Y1 - 2012/// KW - Computational Biology KW - Semantics KW - Software PB - BioMed Central JF - Journal of biomedical semantics VL - 3 IS - 1 SP - 11 EP - 11 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - UNLABELLED BACKGROUND As the "omics" revolution unfolds, the growth in data quantity and diversity is bringing about the need for pioneering bioinformatics software, capable of significantly improving the research workflow. To cope with these computer science demands, biomedical software engineers are adopting emerging semantic web technologies that better suit the life sciences domain. The latter's complex relationships are easily mapped into semantic web graphs, enabling a superior understanding of collected knowledge. Despite increased awareness of semantic web technologies in bioinformatics, their use is still limited. RESULTS COEUS is a new semantic web framework, aiming at a streamlined application development cycle and following a "semantic web in a box" approach. The framework provides a single package including advanced data integration and triplification tools, base ontologies, a web-oriented engine and a flexible exploration API. Resources can be integrated from heterogeneous sources, including CSV and XML files or SQL and SPARQL query results, and mapped directly to one or more ontologies. Advanced interoperability features include REST services, a SPARQL endpoint and LinkedData publication. These enable the creation of multiple applications for web, desktop or mobile environments, and empower a new knowledge federation layer. CONCLUSIONS The platform, targeted at biomedical application developers, provides a complete skeleton ready for rapid application deployment, enhancing the creation of new semantic information systems. COEUS is available as open source at http://bioinformatics.ua.pt/coeus/. ER - TY - CONF T1 - Semantic interoperability between clinical and public health information systems for improving public health services A1 - Lopez, D M A1 - Blobel, B.G.M.E. Y1 - 2007/// KW - Business Modeling KW - Germany KW - Humans KW - Public Health KW - Public Health Administration KW - Public Health Informatics KW - Semantic Interoperability KW - Semantics KW - Services Integration KW - UML KW - article KW - human KW - medical informatics KW - organization and management KW - public health service KW - semantics VL - 127 SP - 256 EP - 267 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-35548959493&partnerID=40&md5=5836b19c722025178ad036dc5dee6599 N1 - Cited By :6 Export Date: 5 April 2018 N2 - Improving public health services requires comprehensively integrating all services including medical, social, community, and public health ones. Therefore, developing integrated health information services has to start considering business process, rules and information semantics of involved domains. The paper proposes a business and information architecture for the specification of a future-proof national integrated system, concretely the requirements for semantic integration between public health surveillance and clinical information systems. The architecture is a semantically interoperable approach because it describes business process, rules and information semantics based on national policy documents and expressed in a standard language such us the Unified Modeling Language UML. Having the enterprise and information models formalized, semantically interoperable Health IT components/services development is supported. © 2007 The authors and IOS Press. All rights reserved. ER - TY - CONF T1 - Connecting public health and clinical information systems by using a standardized methodology A1 - Lopez, D M A1 - Blobel, B.G.M.E. Y1 - 2007/// KW - Computational Biology KW - Developing Countries KW - HL7 KW - Information Systems KW - architecture KW - information systems KW - public health surveillance KW - semantic interoperability KW - unified process VL - 129 SP - 132 EP - 136 N1 - Cited By :3 Export Date: 10 September 2018 References: Zachman, J., A framework for information systems architecture (1999) IBM Systems Journal, 38 (2-3), pp. 454-471; Open Distributed Processing-Reference Model, , ISO/IEC 10746-1, 2, 3, 4 OMG, 1995-98; MDA Specification, , www.omg.org/mda/, Object Management Group, Inc; Zimmermann, O., Krogdahl, P., Gee, C., Elements of Service-Oriented Analysis and Design, , http://www-128.ibm.com/developerworks/library/ws-soad1/, IBM developerWorks; Kruchten, P., The rational unified process (2003) An Introduction, , Third Edition. Addison Wesley; (2006) HL7 Version 3 Normative, , HL7 Inc. Edition; Healthcare Services Specification Project, , http://hssp.wikispaces.com/, SOA4HL7; Healthcare Information System Architecture, , CEN ENV 12967 European Committee for Standardization; Blobel, B., (2002) Analysis, Design and Implementation of Secure and Interoperable Distributed Health Information Systems, , Amsterdam: IOS Press; http://www.minproteccionsocial.gov.co, Resolución 2542 de 1998. Ministerio de la Protección Social República de Colombia; http://www.minproteccionsocial.gov.co, Decreto 3518 de 2006. Ministerio de la Protección Social República de ColombiaUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650512195&partnerID=40&md5=2d59224518fa77919d1c4f520633e695 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - To meet the challenge for efficient, high quality and sustainable care, health systems in developed and increasingly in developing countries require extended communication and cooperation between all principals involved in citizen's care. The challenge also concerns supporting information systems, which demand interoperation with public health, bioinformatics, genomics, administrative, governmental, and other sources of data. The paper describes an architecture development methodology for modeling the integration between clinical and public health information systems that harmonizes existent standardized modeling approaches and integrates HL7 domain knowledge. An integration-architecture for information sharing between public health surveillance and clinical information systems is derived demonstrating the feasibility of the proposed methodology. Predominantly, a harmonized process for analysis, design, implementation and maintenance of semantically interoperable information systems based on formal grammars is discussed in some detail. © 2007 The authors. All rights reserved. ER - TY - JOUR T1 - XML as a technology to support the information management in public health administrations A1 - López, D M A1 - Fernández, M J A1 - Rendón, A A1 - Figueroa, J A1 - Llamas, M Y1 - 2005/// KW - Information Systems KW - Internet KW - Public Health Administration KW - computer analysis KW - computer program KW - conference paper KW - health survey KW - medical information system KW - priority journal KW - public health service JF - Technology and Health Care VL - 13 IS - 5 SP - 417 EP - 419 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-32444438576&partnerID=40&md5=1770caa269571813efd6d20c523d49c9 N1 - Export Date: 10 September 2018 References: López, D.M., (2005) Arquitectura de Un Sistema de Información para Vigilancia en Salud Pública en Zonas Rurales, , MSc thesis dissertation, Departamento de Telemática, Universidad del Cauca; Martinez, A., Lopez, D.M., Sáez, A., Seaone, J., Rendón, A., Shoemaker, R., Fernández, I., Improving Epidemiologic Surveillance and Health Promoter Training in Rural Latin America through ICT (2005) Telemed J E Health, 11 (4), pp. 39-47 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: Internet technologies have been traditionally used by public health administrations to share administrative information through conventional web-based information systems and in other cases as a communication tool. Health administrations demand flexible Information systems able to support the collection, processing, storing and delivery of health and administrative information. That information is often dynamic (normative and information structure change frequently being necessary to modify the collecting forms and reports), demands several reports to different stakeholders (i.e. epidemiologists need incidence reports and decision makers want trends reports); requires interoperability with other health information systems and it needs to be adjusted to the heterogeneity of healthcare establishments infrastructure: operative systems, low-processing capacity, etc. XML (Extensible Markup Language) is as a key technology to deal, in an integrated way, with the flexibility, interoperability and heterogeneity requirements of information for Public health administrations. A further result of this research is a generic architecture for the Information systems development and also a methodology for the design of such architecture. Methods: Due to no methodology were found for the design of such generic architecture for health information systems, we first developed the desired methodology. The methodology is based on the main concepts of MDA (Model Driven Architecture) and is driven by the Unified Process (UP). The methodology consists of four well-defined UP stages: The Domain Model, The Business Model, the Use Cases Model and the Analysis Model [1]. The outcome of the architectural design process is a set of UML design classes grouped in packages. The architecture separates the functional requisites and the non-functional requisites as shown in Fig. 1. Taking into consideration that the functional requisites are specific for the business of each Information system, we obtained our functional requisites from a public health surveillance department in a health institution in Colombia. This organization's main business is the surveillance of communicable diseases and in consequence the main packages found where: collection, EHC Repository, analysis, case repository, reports management and users management (Fig. 1(a)). On the other hand, the non-functional requisites of flexibility, interoperability and heterogeneity of health information where also modelled and included in the metadata and data communication packages. Other significant non-functional requisite included in the architecture where the security and scalability represented by the three layers separation (model-view-control) and client/server architecture. (Fig. 1(b)). Results: A XML-based information system to support the epidemiological surveillance in a province in Colombia and based on the above architecture was developed. A report of the real use of the above tool is present in [2]. The use of XML metadata and documents lets us to cope with the functional requisites of the system: collection, store, analysis and delivery of epidemiological data; but also to complete the non-functional requisites of flexibility, interoperability, heterogeneity and scalability. XML allows the dynamic creation (thought a XML forms editor) of the collecting forms; the information processing and dynamic generation of reports through XSLT transformations; the storing of information as XML documents to deal with the heterogeneity of systems and communication networks and the data interoperability when structuring the information as metadata files. Figure 2 shows the System architecture and its main functionalities. Discussion: We found that XML is the right technology to implement the designed architecture because it easily implements the mentioned non- functional requisites and also covers the information management needs expressed in the functional requisites. In addition, the architectural approach of this research provides reusability and scalability preserving the knowledge acquired during the system development. ER - TY - JOUR T1 - Enhanced semantic interoperability by profiling health informatics standards A1 - López, Diego M. A1 - Blobel, Bernd A1 - Lopez, D M A1 - Blobel, Bernd Y1 - 2009/// KW - Computer Simulation KW - Delivery of Health Care KW - Feasibility Studies KW - HL7 KW - Hospital Information Systems KW - Humans KW - Integrated KW - Integrated health care systems KW - Java components KW - Profiles KW - Reusability KW - Semantic interoperability KW - Semantics KW - Software KW - Standards KW - Systems Analysis KW - UML KW - UML. KW - article KW - computer program KW - computer simulation KW - feasibility study KW - hospital information system KW - human KW - integrated health care system KW - integrated health care systems KW - organization and management KW - profiles KW - reusability KW - semantic interoperability KW - semantics KW - system analysis PB - Schattauer Publishers JF - Methods of Information in Medicine VL - 48 IS - 2 SP - 170 EP - 177 DO - 10.3414/ME9216 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-68549101770&doi=10.3414%2FME9216&partnerID=40&md5=da2a405efb924315202636e9c23155b9 UR - http://www.schattauer.de/index.php?id=1214&doi=10.3414/ME9216 N1 - From Duplicate 1 (Enhanced semantic interoperability by profiling health informatics standards - Lopez, D M; Blobel, B) Cited By :17 Export Date: 5 April 2018 N2 - Objectives: Several standards applied to the healthcare domain support semantic interoperability. These standards are far from being completely adopted in health information system development, however. The objective of this paper is to provide a method and suggest the necessary tooling for reusing standard health information models, by that way supporting the development of seman - tically interoperable systems and compo - nents. Methods: The approach is based on the definition of UML Profiles. UML profiling is a formal modeling mechanism to specialize reference meta-models in such a way that it is possible to adapt those meta-models to specific platforms or domains. A health information model can be considered as such a metamodel. Results: The first step of the introduced method identifies the standard health information models and tasks in the software development process in which healthcare information models can be reused. Then, the selected information model is formalized as a UML Profile. That Profile is finally applied to system models, annotating them with the semantics of the information model. The approach is supported on Eclipse-based UML modeling tools. The method is integrated into a comprehensive framework for health information systems development, and the feasibility of the approach is demonstrated in the analysis, design, and implementation of a public health surveillance system, reusing HL7 RIM and DIMs specifications. Conclusions: The paper describes a method and the necessary tooling for reusing standard healthcare information models. UML offersseveral advantages such as tooling support, graphical notation, exchangeability, extensibility, semi-automatic code generation, etc. The approach presented is also applicable for harmonizing different standard specifications. © 2009 Schattauer. ER - TY - CONF T1 - Improving maternity care with business intelligence A1 - Loreto, P A1 - Fonseca, F A1 - Morais, A A1 - Peixoto, H A1 - Abelha, A A1 - Machado, J Y1 - 2017/// KW - Business Intelligence KW - Competitive intelligence KW - Data Warehousing KW - Data warehouses KW - Decision making KW - Decision making process KW - Extract transform loads KW - Extract-Transform-Load KW - Health Information Systems KW - Health care KW - Health information systems KW - Improvement measure KW - Indicators KW - Indicators (instruments) KW - Information analysis KW - Information systems KW - Information use KW - Intelligence KW - International healths KW - Internet of things KW - Interoperability KW - Medical computing KW - Obstetrics KW - Power BI KW - Public health KW - Quality of health care KW - Reference values KW - Related works KW - Warehouses VL - 2017 SP - 170 EP - 177 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047413573&doi=10.1109%2FFiCloudW.2017.89&partnerID=40&md5=54a43f1b7c10b42ab82c19d054c3a987 N1 - Export Date: 10 September 2018 References: Machado, J., Abelha, A., (2016) Applying Business Intelligence to Clinical and Healthcare Organizations, , IGI Global; Pereira, A., Marins, F., Rodrigues, B., Portela, F., Santos, M.F., Machado, J., Rua, F., Abelha, A., Improving quality of medical service with mobile health software (2015) Procedia Computer Science, 63, pp. 292-299; Pinheiro, V.M.O., (2015) Arquitetura Empresarial Do Centro Hospitalar Do Alto Ave, , Ph.D. dissertation; E. SPMS - Servicços Partilhados Do Ministério da Saúde, , http://spms.min-saude.pt/product/, Online; accessed 24-April-2017; Cardoso, L., Marins, F., Quintas, C., Portela, F., Santos, M., Abelha, A., Machado, J., Interoperability in healthcare (2014) Cloud Computing Applications for Quality Health Care Delivery, pp. 78-101; Brandão, A., Pereira, E., Esteves, M., Portela, F., Santos, M.F., Abelha, A., Machado, J., A benchmarking analysis of open-source business intelligence tools in healthcare environments (2016) Information, 7 (4), p. 57; Novo, A., Duarte, J., Portela, F., Abelha, A., Santos, M.F., Machado, J., Information systems assessment in pathologic anatomy service (2015) New Contributions in Information Systems and Technologies, pp. 199-209. , Springer; Bonney, W., Applicability of business intelligence in electronic health record (2013) Procedia-Social and Behavioral Sciences, 73, pp. 257-262; Coelho, D., Miranda, J., Portela, F., Machado, J., Santos, M.F., Abelha, A., Towards of a business intelligence platform to Portuguese misericórdias (2016) Procedia Computer Science, 100, pp. 762-767; Ana Pereira, M.F.S.J.M.A.A., Filipe, P., Rua, F., Pervasive business intelligence in intensive medicine (2017) ETELEMED 2017: The Ninth International Conference on EHealth, Telemedicine, and Social Medicine, pp. 37-41; Brandão, A., Pereira, E., Portela, F., Santos, M., Abelha, A., Machado, J., Real-time business intelligence platform to maternity care (2014) Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on, pp. 379-384. , IEEE; Kimball, R., Caserta, J., (2011) The Data Warehouse? ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data, , John Wiley & Sons; Tremblay, M.C., Fuller, R., Berndt, D., Studnicki, J., Doing more with more information: Changing healthcare planning with olap tools (2007) Decision Support Systems, 43 (4), pp. 1305-1320; Vassiliadis, P., A survey of extract-transform-load technology (2009) International Journal of Data Warehousing and Mining (IJDWM), 5 (3), pp. 1-27; Machado, J., Silva, E., Abelha, A., Business intelligence platform for nosocomial infection incidence (2017) Indian Journal of Science and Technology, 10 (10); Ali, S.M., Gupta, N., Nayak, G.K., Lenka, R.K., Big Data Visualization: Tools and Challenges; Tereso, M., Bernardino, J., Open source business intelligence tools for smes (2011) Information Systems and Technologies (CISTI), 2011 6th Iberian Conference on, pp. 1-4. , IEEE; http://www.tableau.com/, Software T.[online; Accessed 23-April- 2017]; https://powerbi.microsoft.com/pt-br/, Online; accessed 23-April- 2017; Plotly, https://plot.ly/, Online; accessed 23-April-2017; Gephi, https://gephi.org/, Online; accessed 23-April-2017]; https://products.office.com/pt-pt/excel, Excel Online; accessed 23- April-2017; https://www.spagobi.org/, SpagoBI Online; accessed 23-April-2017; Askari, R., Shafii, M., Baghian, N., Comparing performance indicators of obstetrics and gynecology ward at yazd educational hospitals with expected limits of indicators, 2015 (2016) Osong Public Health and Research Perspectives, 7 (3), pp. 197-204; Mainz, J., Defining and classifying clinical indicators for quality improvement (2003) International Journal for Quality in Health Care, 15 (6), pp. 523-530; Mainz, J., Developing evidence-based clinical indicators: A state of the art methods primer (2003) International Journal for Quality in Health Care, 15, pp. i5-i11; Sadeghi-Bazargani, H., Farhoudi, M., Hajebrahimi, S., Naghavi-Behzad, M., Sohrabnavi, Z., Azami-Aghdash, S., A systematic review on clinical indicators, their types and codification processes (2014) Journal of Clinical Research & Governance, 4 (1); Boulkedid, R., Alberti, C., Sibony, O., Quality indicator development and implementation in maternity units (2013) Best Practice & Research Clinical Obstetrics & Gynaecology, 27 (4), pp. 609-619; Prevedello, L.M., Andriole, K.P., Hanson, R., Kelly, P., Khorasani, R., Business intelligence tools for radiology: Creating a prototype model using open-source tools (2010) Journal of Digital Imaging, 23 (2), pp. 133-141; Ali, O., Crvenkovski, P., Johnson, H., Using a business intelligence data analytics solution in healthcare (2016) Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2016 IEEE 7th Annual, pp. 1-6. , IEEE; http://www.healthline.com/health/pregnancy/what-is-an-obstetrician, HealthLine Online; accessed 22-April-2017; http://www.wisegeek.org/what-is-an-obstetrician.htm, wiseGEEK, Online; accessed 22-April-2017; https://www.urmc.rochester.edu/encyclopedia/content.aspx?ContentTypeID=90&ContentID=P02336, U. of Rochester Medical Center, Online; accessed 22-April-2017; Pereira, S., Portela, F., Santos, M.F., Machado, J., Abelha, A., Predicting type of delivery by identification of obstetric risk factors through data mining (2015) Procedia Computer Science, 64, pp. 601-609; Kornelson, K.P., Vajjiravel, M., Prasad, R., Clark, P.D., Najm, T., (2006) Method and System for Developing Extract Transform Load Systems for Data Warehouses, , Nov. 21; Estatísticas da saúde 2015 (2017) Statistics Portugal, Tech. Rep.; Hospital maternity activity 2015-16 (2016) National Health System, Tech. Rep.; Australia's mothers and babies 2014 (2016) Australian Institute of Health and Welfare, Tech. Rep. RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The aim of this paper is to develop clinical indicators for obstetrics through the use of Business Intelligence (BI) tools, since valid and reliable clinical indicators can help measuring quality of healthcare services and support decision-making processes. This paper gives an overview of concepts related to Health Information Systems (HIS) and BI, along with some related work to highlight the advantages that BI solutions can bring when applied to healthcare. In this paper is also presented the data warehousing and the ETL process, that was necessary for the development of indicators and which is usually hidden from endusers, is described. The indicators were developed using Power BI and were analysed and compared with reference values from both national and international health reports. The discussion of the developed indicators made it possible to measure the quality of the obstetrics service, to identify the problematic areas and to decide whether improvement measures should be taken. © 2017 IEEE. ER - TY - JOUR T1 - Cross-Network Directory Service: Infrastructure to enable collaborations across distributed research networks A1 - Malenfant, J M A1 - Hochstadt, J A1 - Nolan, B A1 - Barrett, K A1 - Corriveau, D A1 - Dee, D A1 - Harris, M A1 - Herzig-Marx, C A1 - Nair, V P A1 - Wyner, Z A1 - Wyner, Z A1 - Brown, J S Y1 - 2019/// JF - Learning Health Systems VL - 3 IS - 2 DO - 10.1002/lrh2.10187 N2 - ©2019 The Authors. Learning Health Systems published by Wiley Periodicals, Inc. on behalf of the University of Michigan Introduction: Existing large-scale distributed health data networks are disconnected even as they address related questions of healthcare research and public policy. This paper describes the design and implementation of a fully functional prototype open-source tool, the Cross-Network Directory Service (CNDS), which addresses much of what keeps distributed networks disconnected from each other. Methods: The set of services needed to implement a Cross-Directory Service was identified through engagement with stakeholders and workgroup members. CNDS was implemented using PCORnet and Sentinel network instances and tested by participating data partners. Results: Web services that enable the four major functional features of the service (registration, discovery, communication, and governance) were developed and placed into an open-source repository. The services include a robust metadata model that is extensible to accommodate a virtually unlimited inventory of metadata fields, without requiring any further software development. The user interfaces are programmatically generated based on the contents of the metadata model. Conclusion: The CNDS pilot project gathered functional requirements from stakeholders and collaborating partners to build a software application to enable cross-network data and resource sharing. The two partners—one from Sentinel and one from PCORnet—tested the software. They successfully entered metadata about their organizations and data sources and then used the Discovery and Communication functionality to find data sources of interest and send a cross-network query. The CNDS software can help integrate disparate health data networks by providing a mechanism for data partners to participate in multiple networks, share resources, and seamlessly send queries across those networks. ER - TY - JOUR T1 - Barriers, Facilitators, and Potential Solutions to Advancing Interoperable Clinical Decision Support: Multi-Stakeholder Consensus Recommendations for the Opioid Use Case A1 - Marcial, L H A1 - Blumenfeld, B A1 - Harle, C A1 - Jing, X A1 - Keller, M S A1 - Lee, V A1 - Lin, Z A1 - Dover, A A1 - Midboe, A M A1 - Al-Showk, S A1 - Solomon, H A1 - Kawamoto, K Y1 - 2019/// JF - AMIA ... Annual Symposium proceedings. AMIA Symposium VL - 2019 SP - 637 EP - 646 N2 - ©2019 AMIA - All rights reserved. With the advent of interoperability standards such as FHIR, SMART, CDS Hooks, and CQL, interoperable clinical decision support (CDS) holds great promise for improving healthcare. In 2018, the Agency for Healthcare Research and Quality (AHRQ)-sponsored Patient-Centered CDS Learning Network (PCCDS LN) chartered a Technical Framework Working Group (TechFWG) to identify barriers, facilitators, and potential solutions for interoperable CDS, with a specific focus on addressing the opioid epidemic. Through an open, multi-stakeholder process that engaged 54 representatives from healthcare, industry, and academia, the TechFWG identified barriers in 6 categories: regulatory environment, data integration, scalability, business case, effective and useful CDS, and care planning and coordination. Facilitators and key recommendations were also identified for overcoming these barriers. The key insights were also extrapolated to CDS-facilitated care improvement outside of the specific opioid use case. If applied broadly, the recommendations should help advance the availability and impact of interoperable CDS delivered at scale. ER - TY - JOUR T1 - Archetype-based data warehouse environment to enable the reuse of electronic health record data A1 - Marco-Ruiz, L A1 - Moner, D A1 - Maldonado, J A A1 - Kolstrup, N A1 - Bellika, J G Y1 - 2015/// KW - Aggregation functions KW - Article KW - Artificial intelligence KW - Clinical decision support systems KW - Computational linguistics KW - Data reuse KW - Data warehouse KW - Data warehouses KW - Databases, Factual KW - Decision Support Systems, Clinical KW - Decision support systems KW - Delivery of Health Care KW - Digital storage KW - Electronic Health Record(EHR) System KW - Electronic Health Records KW - Electronic health record KW - Humans KW - Information Storage and Retrieval KW - Interoperability KW - Medical Record Linkage KW - Medical Records Systems, Computerized KW - Metadata KW - Norway KW - OpenEHR KW - Query languages KW - Records management KW - Salmonella KW - Semantic interoperability KW - Semantics KW - Software KW - Systems Integration KW - User-Computer Interface KW - Warehouse infrastructures KW - clinical data repository KW - computer interface KW - computer program KW - controlled study KW - data base KW - data extraction KW - decision support system KW - electronic medical record KW - factual database KW - health care delivery KW - human KW - information processing KW - information retrieval KW - laboratory test KW - medical informatics KW - medical record KW - organization and management KW - pertussis KW - priority journal KW - procedures KW - semantics KW - standards KW - system analysis KW - workflow JF - International Journal of Medical Informatics VL - 84 IS - 9 SP - 702 EP - 714 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946500646&doi=10.1016%2Fj.ijmedinf.2015.05.016&partnerID=40&md5=e3a871d4996be4b04da8d1cfaede7235 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Marco-Ruiz et al. - 2015 - Archetype-based data warehouse environment to enable the reuse of electronic health record data.pdf N1 - Cited By :20 Export Date: 10 September 2018 References: Selby, J.V., Krumholz, H.M., Kuntz, R.E., Collins, F.S., Network news powering clinical research (2013) Sci. Transl. Med., 5. , April 24 (182), 182fs13; Jensen, P.B., Jensen, L.J., Brunak, S., Mining electronic health records: towards better research applications and clinical care (2012) Nat. Rev. Genet., 13 (JUNE 6), pp. 395-405; Kawamoto, K., Houlihan, C.A., Balas, E.A., Lobach, D.F., Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success (2005) BMJ, 330, p. 765. , April 2 (7494); Friedman, C.P., Wong, A.K., Blumenthal, D., Achieving a nationwide learning health system (2010) Sci. Transl. Med., 2. , Oct 11 (57), 57cm29; Terry, S.F., Terry, P.F., Power to the people: participant ownership of clinical trial data (2011) Sci. Transl. Med., 3. , September 2 (69), 69cm3; Krist, A.H., Beasley, J.W., Crosson, J.C., Kibbe, D.C., Klinkman, M.S., Lehmann, C.U., Electronic health record functionality needed to better support primary care (2014) J. Am. Med. Inf. Assoc., 21, pp. 764-771. , January 9 (5); Electronic Health Records for Clinical Research http://www.ehr4cr.eu/, [Internet]. [cited 14.09.14]; http://www.pcornet.org, [Internet]. PCORnet. [cited 14.09.14]; http://commonfund.nih.gov/hcscollaboratory/index, [Internet]. [cited 14.09.14]; Nadler, J.J., Downing, G.J., Liberating health data for clinical research applications (2010) Sci. Transl. Med., 2. , October 2 (18), 18cm6; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., HL7Clinical document architecture, release 2 (2006) J. Am. Med. Inf. Assoc., 13, pp. 30-39. , January 1 (1); Beale, T., (2002) Archetypes Constraint-Bbased Domain Models for Futureproof Information Systems, , OOPSLA, 2002, Workshop Behav Semant; Health informatics - Electronic health record communication (2008); Stroetmann, V.N., Kalra, D., Lewalle, P., Rector, A., Rodrigues, J.M., Stroetmann, K.A., (2009) Semantic Interoperability for Better Health and Safer Healthcare [Internet], , http://dx.doi.org/10.2759/38514, January, European Commission, Directorate-General Information Society and Media; Goossen, W., Goossen-Baremans, A., van der Zel, M., Detailed clinical models: a review (2010) Health Inf. Res., 16 (4), p. 201; http://www.opencimi.org/, [Internet]. [cited 14.11.14]; http://www.epsos.eu/, [Internet]. [cited 13.11.14]; Health and Social Care Information Centre http://systems.hscic.gov.uk/interop/background/itk, [Internet]. [cited 28.03.14]; (2014), http://https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index.html%3Fredirect=/EHRIncentivePrograms/, Overview [Internet] [cited 08.09.14]; Blumenthal, D., Tavenner, M., The 'meaningful use' regulation for electronic health records (2010) N. Engl. J. Med., 363, pp. 501-504. , July 13 (6); Schadow, G., Russler, D.C., Mead, C.N., McDonald, C.J., Integrating medical information and knowledge in the HL7 RIM (2000) Proc. AMIA Annu. Symp. AMIA Symp., pp. 764-768; Rector, A.L., Johnson, P.D., Tu, S., Wroe, C., Rogers, J., Quaglini, S., Interface of inference models with concept and medical record models (2001) Proc. Artif. Intell. Med. Eur. AIME-2001, 1 (JANUARY), pp. 314-323; Safran, C., Reuse of clinical data (2014) IMIA, 9 (1), pp. 52-54; http://www.hl7org/Special/Committees/arden/index.cfm, [Internet]. [cited 13.11.14]; http://www.hl7org/implement/standards/product_brief.cfm%3Fproduct_id=5, (HL7 Version 3 Standard: Gello: A Common Expression Language, Release 2) [Internet]. [cited 13.11.14]; Greenes, R.A., (2014) Clinical Decision Support: The Road to Broad Adoption, p. 929. , Academic Press; Peleg, M., Keren, S., Denekamp, Y., Mapping computerized clinical guidelines to electronic medical records: knowledge-data ontological mapper (KDOM) (2008) J. Biomed. Inform., 41 (FEBRUARY 1), pp. 180-201; Kawamoto, K., Del Fiol, G., Strasberg, H.R., Hulse, N., Curtis, C., Cimino, J.J., Multi-national, multi-institutional analysis of clinical decision support data needs to inform development of the HL7 virtual medical record standard (2010) AMIA Annu. Symp. Proc. AMIA Symp. AMIA Symp., 2010, pp. 377-381; Marcos, M., Maldonado, J.A., Martínez-Salvador, B., Boscá, D., Robles, M., Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility (2013) J. Biomed. Inf., 46 (AUGUST 4), pp. 676-689; Fernández-Breis, J.T., Maldonado, J.A., Marcos, M., Legaz-García, M.D.C., Moner, D., Torres-Sospedra, J., Leveraging electronic healthcare record standards and semantic web technologies for the identification of patient cohorts (2013) J. Am. Med. Inf. Assoc. JAMA, (AUGUST 9); http://www.mobiguide-project.eu/, [Internet]. [cited 14.11.14]; González-Ferrer, A., Peleg, M., Verhees, B., Verlinden, J.-M., Marcos, C., (2013) Data Integration for Clinical Decision Support Based on OpenEHR Archetypes and HL7 Virtual Medical Record. Process Support and Knowledge Representation in Health Care [Internet], pp. 71-84. , http://link.springer.com/chapter/10.1007/978-3-642-36438-9_5, Springer, Berlin Heidelberg, [cited 21.03.14]; Pathak, J., Bailey, K.R., Beebe, C.E., Bethard, S., Carrell, D.C., Chen, P.J., Normalization and standardization of electronic health records for high-throughput phenotyping: the SHARPn consortium (2013) J. Am. Med. Inf., 20 (DECEMBER e2), pp. e341-e348; Holstiege, J., Mathes, T., Pieper, D., Effects of computer-aided clinical decision support systems in improving antibiotic prescribing by primary care providers: a systematic review (2014) J. Am. Med. Inf. Assoc. JAMIA, (AUGUST 14); Chen, P., Tanasijevic, M.J., Schoenenberger, R.A., Fiskio, J., Kuperman, G.J., Bates, D.W., A computer-based intervention for improving the appropriateness of antiepileptic drug level monitoring (2003) Am. J. Clin. Pathol., 119 (MARCH 3), pp. 432-438; Bellika, J.G., Hasvold, T., Hartvigsen, G., Propagation of program control: a tool for distributed disease surveillance (2007) Int. J. Med. Inf., 76 (APRIL 4), pp. 313-329; Data Mining in Clinical Medicine http://www.springer.com/life+sciences/systems+biology+and+bioinformatics/book/978-1-4939-1984-0, [Internet]. [cited 27.10.14]; Drools - Drools - Business Rules Management System http://www.drools.org/, (Java™, Open Source) [Internet]. [cited 20.11.14]; http://nasjonalikt.no/no/satsingsomrader/2_struktur_-_systemarkitektur_informasjonsgrunnlag_og_sikkerhet/tiltak_155_folkeregisteret_i_helsenettet/Tiltak+15.5+Folkeregisteret+i+helsenettet.9UFRjK5S.ips, [Internet]. [cited 10.11.14]; http://www.openehr.org/wiki/display/spec/Archetype+Query+Language+Description, [Internet]; Clinical Knowledge Manager http://www.openehr.org/ckm/, [Internet]. OpenEHR Clinical Knowledge Manager. [cited 14.10.13]; Maldonado, J.A., Moner, D., Boscá, D., Fernández-Breis, J.T., Angulo, C., Robles, M., LinkEHR-Ed. A multi-reference model archetype editor based on formal semantics (2009) Int. J. Med. Inf., 78 (AUGUST 8), pp. 559-570; Maldonado, J.A., Costa, C.M., Moner, D., Menárguez-Tortosa, M., Boscá, D., Miñarro Giménez, J.A., Using the researchEHR platform to facilitate the practical application of the EHR standards (2012) J. Biomed. Inf., 45 (AUGUST 4), pp. 746-762; Mok, W.Y., Ng, Y.-K., Embley, D.W., A normal form for precisely characterizing redundancy in nested relations (1996) ACM Trans. Database Syst., 21 (MARCH 1), pp. 77-106; Marand, D.O.O., Think!MED Clinical TM; Kimball, R., Ross, M., (2013) The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, p. 600. , Wiley, Indianapolis, IN; Frankel, H., Beale, T., (2007) OpenEHR EHR. Extract Information Model, , The OpenEHR Foundation; Kikhoste (pertussis) - veileder for helsepersonell - Folkehelseinstituttet http://www.fhi.no/eway/default.aspx%3Fpid=239&trg=Content_6493&Main_6157=6287:0:25,5499&MainContent_6287=6493:0:25,6833&Content_6493=6441:82766::0:6446:62:::0:0, [Internet]. [cited 18.09.14]; Pertussis - Communicable Disease Control Manual. ; Salmonellose - veileder for helsepersonell - Folkehelseinstituttet http://www.fhi.no/eway/default.aspx%3Fpid=239&trg=Content_6493&Main_6157=6287:0:25,5499&MainContent_6287=6493:0:25,6833&Content_6493=6441:82847::0:6446:106:::0:0, [Internet]. [cited 08.09.14]; Rong, C., Guide Definition Language (GDL) (2013), http://www.openehr.org/downloads/ds_and_guidelines, [Internet]; Klann, J.G., Buck, M.D., Brown, J., Hadley, M., Elmore, R., Weber, G.M., Query health: standards-based, cross-platform population health surveillance (2014) J. Am. Med. Inf. Assoc., (APRIL 3). , amiajnl -2014-002707; http://www.w3org/TR/rdf-sparql-query/, [Internet]. [cited 21.09.14]; Lezcano, L., Sicilia, M.-A., Rodríguez-Solano, C., Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules (2011) J. Biomed. Inform., 44 (APRIL 2), pp. 343-353; Bates, D.W., Kuperman, G.J., Wang, S., Gandhi, T., Kittler, A., Volk, L., Ten commandments for effective clinical decision support: making the practice of evidence-based medicine a reality (2003) J. Am. Med. Inf. Assoc. JAMIA, 10 (DECEMBER 6), pp. 523-530; Hu, H., Correll, M., Kvecher, L., Osmond, M., Clark, J., Bekhash, A., DW4TR: a data warehouse for translational research (2011) J. Biomed. Inf., 44 (DECEMBER 6), pp. 1004-1019; Yoo, S., Kim, S., Lee, K.-H., Jeong, C.W., Youn, S.W., Park, K.U., Electronically implemented clinical indicators based on a data warehouse in a tertiary hospital: its clinical benefit and effectiveness (2014) Int. J. Med. Inf., 83 (JULY 7), pp. 507-516; Danciu, I., Cowan, J.D., Basford, M., Wang, X., Saip, A., Osgood, S., Secondary use of clinical data: the vanderbilt approach (2014) J. Biomed. Inf., , http://www.sciencedirect.com/science/article/pii/S1532046414000392, [cited 21.09.14]; Murphy, S.N., Weber, G., Mendis, M., Gainer, V., Chueh, H.C., Churchill, S., Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) (2010) J. Am. Med. Inf. Assoc. JAMIA, 17 (APRIL 2), pp. 124-130 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed. Objective: To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse. Materials and methods: The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases. Results: Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language. Discussion: Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world of possibilities toward semantic or concept-based reuse, query and communication of clinical data. © 2015 Elsevier Ireland Ltd. ER - TY - JOUR T1 - Publication, discovery and interoperability of Clinical Decision Support Systems: A Linked Data approach A1 - Marco-Ruiz, Luis A1 - Pedrinaci, Carlos A1 - Maldonado, J A A1 - Panziera, Luca A1 - Chen, Rong A1 - Bellika, J Gustav Y1 - 2016/// KW - Decision Support Systems, Clinical KW - Semantics PB - Academic Press JF - Journal of Biomedical Informatics VL - 62 SP - 243 EP - 264 CY - Dip. di Etologia, Ecologia ed Evoluzione, University of Pisa, via A. Volta 6, Pisa, I-56126, Italy. vformi@discau.unipi.it DO - S0047-2484(98)90270-6 [pii] ENGLAND UR - https://www.sciencedirect.com/science/article/pii/S153204641630065X?via%3Dihub N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND The high costs involved in the development of Clinical Decision Support Systems (CDSS) make it necessary to share their functionality across different systems and organizations. Service Oriented Architectures (SOA) have been proposed to allow reusing CDSS by encapsulating them in a Web service. However, strong barriers in sharing CDS functionality are still present as a consequence of lack of expressiveness of services’ interfaces. Linked Services are the evolution of the Semantic Web Services paradigm to process Linked Data. They aim to provide semantic descriptions over SOA implementations to overcome the limitations derived from the syntactic nature of Web services technologies. OBJECTIVE To facilitate the publication, discovery and interoperability of CDS services by evolving them into Linked Services that expose their interfaces as Linked Data. MATERIALS AND METHODS We developed methods and models to enhance CDS SOA as Linked Services that define a rich semantic layer based on machine interpretable ontologies that powers their interoperability and reuse. These ontologies provided unambiguous descriptions of CDS services properties to expose them to the Web of Data. RESULTS We developed models compliant with Linked Data principles to create a semantic representation of the components that compose CDS services. To evaluate our approach we implemented a set of CDS Linked Services using a Web service definition ontology. The definitions of Web services were linked to the models developed in order to attach unambiguous semantics to the service components. All models were bound to SNOMED-CT and public ontologies (e.g. Dublin Core) in order to count on a lingua franca to explore them. Discovery and analysis of CDS services based on machine interpretable models was performed reasoning over the ontologies built. DISCUSSION Linked Services can be used effectively to expose CDS services to the Web of Data by building on current CDS standards. This allows building shared Linked Knowledge Bases to provide machine interpretable semantics to the CDS service description alleviating the challenges on interoperability and reuse. Linked Services allow for building ‘digital libraries’ of distributed CDS services that can be hosted and maintained in different organizations. ER - TY - JOUR T1 - An enhanced process of concept alignment for dealing with overweight and obesity A1 - Martínez-Villaseñor, M L A1 - González-Mendoza, M Y1 - 2013/// KW - Diet and exercise monitoring KW - Overweight and obesity KW - Schema matching KW - User modeling interoperability JF - Journal of Universal Computer Science VL - 19 IS - 9 SP - 1315 EP - 1333 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883700921&partnerID=40&md5=1472bbb04d4d90dc8b97eb71c431f460 N1 - Cited By :2 Export Date: 10 September 2018 References: Berkovsky, S., Decentralized Mediation of User Models for a Better Personalization (2006) Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 404-408. , http://dx.doi.org/10.1007/11768012_59, [Berkovsky, 06], In ed. Vincent Wade, Helen Ashman, and Barry Smyth, 4018: Springer Berlin / Heidelberg; Berkovsky, S., Heckmann, D., Kuflik, T., Addressing Challenges of Ubiquitous User Modeling:Between Mediation and Semantic Integration (2009) Advances in Ubiquitous User Modelling, 5830, pp. 1-19. , [Berkovsky, 09], doi:10.1007/978-3-642-05039-8_1; Bravo, J., Alamán, X., Riesgo, T., Ubiquitous Computing and Ambient Intelligence: New Challenges for Computing (2006) Journal of Universal Computer Science, 21 (3), pp. 233-235. , http://www.jucs.org/jucs_12_3/ubiquitous_computing_and_ambient, [Bravo, 06]; Bernstein, P.A., Madhavan, J., Rahm, E., Generic Schema Matching, Ten Years Later (2011) Proceedings of the VLDB Endowment, 4 (11), pp. 695-701. , [Bernstein, 11]; Bellahsene, Z., Bonifati, A., Duchateau, F., Velegrakis, Y., On Evaluating Schema Matching and Mapping (2011) Schema Matching and Mapping, pp. 253-291. , [Bellahsene, 11], In ed. Zohra Bellahsene, Angela Bonifati, and Erhard Rahm, Springer; Cali, A., Calvanese, D., Colucci, S., Di, T., Francesco, N., A Description Logic Based Approach for Matching User Profiles (2004) Proceedings of the International Workshop on Description Logics, pp. 1-10. , [Cali, 04], In (DL 2004); Carmagnola, F., Dimitrova, V., An Evidence-Based Approach to Handle Semantic Heterogeneity in Interoperable Distributed User Models (2008) Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 73-82. , [Carmagnola, 08], In 5th International Conference, AH 2008, ed. Wolfgang Nejdl, Judy Kay, Pearl Pu, and Eelco Herder, Hannover, Germany: Springer. doi:isbn:978-3-540-70984-8; Carmagnola, F., Handling Semantic Heterogeneity in Interoperable Distributed User Models (2009) Advances in Ubiquitous User Modelling, 5830, pp. 20-36. , http://www.springerlink.com/content/g227v147n06rx619/, [Carmagnola, 09], doi:10.1007/978-3-642-05039-8_2; Carmagnola, F., Cena, F., Gena, C., User Model Interoperability: A Survey (2011) User Modeling and User-Adapted Interaction, 21 (3), pp. 285-331. , http://www.springerlink.com/index/10.1007/s11257-011-9097-5, [Carmagnola, 11], (February 18) doi:10.1007/s11257-011-9097-5; Cena, F., Furnari, R., A Model for Feature-Based User Model Interoperability on the Web (2009) Advances in Ubiquitous User Modelling, 5830, pp. 37-54. , http://dx.doi.org/10.1007/978-3-642-05039-8_3, [Cena, 09], In ed. Tsvi et al. Kuflik, Springer Berlin / Heidelberg; Cruz, I.F., Xiao, H., The Role of Ontologies in Data Integration (2005) Journal of Engineering Intelligent Systems, 13, pp. 245-252. , [Cruz, 05], 2005; Dice, L.R., Measures of the Amount of Ecologic Association between Species (1945) Ecology, p. 26. , [Dice, 45]; Dolog, P., Schäfer, M., A Framework for Browsing, Manipulating and Maintaining Interoperable Learner Profiles (2005) Proceedings of UM2005 10th International Conference on User Modeling., , [Dolog, 05], In; Euzenat, J., Shvaiko, P., (2007) Ontology Matching., p. 333. , [Euzenat 07], Springer-Verlag, Berlin Heidelberg. ISBN: 978-3-540-49611-3; González, G., López, B.J., A Multi-agent Smart User Model for Crossdomain Recommender Systems (2005) Proceedings of Beyond Personalization: The Next Stage of Recommender Systems Research, , [González, 05], In International Conference on Intelligent User Interfaces IUI'05. San Diego, California, USA; Gruber, T.R., Toward Principles for the Design of Ontologies Used for Knowledge Sharing (1995) International Journal of Human-Computer Studies-Special issue: The role of formal ontology in the information technology., 43 (5-6), pp. 907-928. , http://dx.doi.org/10.1006/ijhc.1995.1081, [Gruber, 95], 1995. doi:10.1006/ijhc.1995.1081; Heckmann, D., (2005) Ubiquitous User Modeling, , [Heckmann, 05], Ph. D Dissertation, Department of Computer Science, Saarland University Germany, Saarland, Germany; Kay, J., Kummerfeld, R.J., Lauder, P., Managing Private User Models and Shared Personas (2003) Proceedings of the Workshop on UM for Ubiquitous Computing, pp. 22-26. , [Kay, 03], In Pittsburg, PA, USA; Kalfoglou, Y., Schorlemmer, M., Ontology Mapping: The State of the Art (2003) The Knowledge Engineering Review, 18 (1), pp. 1-31. , http://dx.doi.org/10.1017/S0269888903000651, [Kalfoglou, 03], doi:10.1017/S0269888903000651; Martinez-Villaseñor, M.L., Gonzalez-Mendoza, M., Hernandez-Gress, N., Towards a Ubiquitous User Model for Profile Sharing and Reuse (2012) Sensors, 12 (10), pp. 13249-13283. , http://www.mdpi.com/1424-8220/12/10/13249, [Martinez-Villaseñor, 12], doi:10.3390/s121013249; Martinez-Villaseñor, M.L., Gonzalez-Mendoza, M., Process of Concept Alignment for Interoperability Between Heterogeneous Sources (2012) 11th Mexican International Conference on Artificial Intelligence, pp. 310-319. , [Martinez-Villaseñor, 12a], MICAI 2012, San Luis Potosí, México, October 27-November 4, LNAI 7669; Martinez-Villaseñor, M.L., Gonzalez-Mendoza, M., Towards an Ontology for Ubiquitous User Modeling Interoperability (2012) KEOD 2012-Proceedings of the International Conference on Knowledge Engineering and Ontology Development, pp. 239-244. , [Martinez-Villaseñor, 12b], In 4-7 October, ed. J. Filipe and J. L. G. Dietz, Barcelona, Spain: SciTePress. doi:isbn:978-989-8565-30-3; Mehta, B., Niederee, C., Stewart, A., Degemmis, M., Lops, P., Semeraro, G., Ontologically-Enriched Unified User Modeling for Cross-System Personalization (2005) User Modeling 2005, 3538, pp. 119-123. , http://dx.doi.org/10.1007/11527886_16, [Mehta, 05], In ed. L. Ardissono, P. Brna, and A. Mitrovic, Springer Berlin / Heidelberg; Mehta, B., Learning from What Others Know: Privacy Preserving Cross System Personalization (2007) Proceedings of the 11th International Conference on User Modeling, pp. 57-66. , http://dx.doi.org/10.1007/978-3-540-73078-1_9, [Mehta, 07], In Berlin, Heidelberg: Springer-Verlag. doi:10.1007/978-3-540-73078-1_9; Miles, A., Pérez-Agüera, J.R., "SKOS: Simple Knowledge Organization for the Web (2007) Cataloging & Classification Quarterly, 43 (3-4), pp. 69-83. , http://www.tandfonline.com/doi/abs/10.1300/J104v43n03_04, [Miles, 07], doi:doi:10.1300/J104v43n03_04; Niu, X., McCalla, G., Vassileva, J., Purpose-based User Modelling in a Multi-agent Portfolio Management System.2003 (2003) Proceedings of UM'03 Proceedings of the 9th international conference on User modeling, pp. 398-402. , [Niu, 03], In Springer-Verlag Berlin, Heidelberg; Noy, N.F., Semantic Integration: A Survey of Ontology-based Approaches SIGMOD Record, 33 (4). , http://doi.acm.org/10.1145/1041410.1041421, [Noy, 04], Stanford University, Stanford, CA, 65-70. December 2004. doi:10.1145/1041410.1041421; Rahm, E., Bernstein, P., A Survey of Approaches to Automatic Schema Matching (2001) The VLDB Journal, 10 (4), pp. 334-350. , http://dx.doi.org/10.1007/s007780100057, [Rahm, 01]; Razmerita, L., Angehrn, A., Maedche, E., Ontology-based User Modeling for Knowledge Management Systems (2003) Proceedings of the Ninth International Conference of User Modeling, 2702, pp. 213-217. , [Razmerita, 03], In; Rui, J., Rodrigues, H., Otero, N., Ambient Intelligence: Beyond the Inspiring Vision (2010) Journal of Universal Computer Science, 16 (12), pp. 1480-1499. , http://www.jucs.org/jucs_16_12/ambient_intelligence_beyond_the, [Rui, 10], June; Shvaiko, P., Euzenat, J., A Survey of Schema-Based Matching Approaches (2005) Journal on Data Semantics, pp. 146-171. , http://dx.doi.org/10.1007/11603412_5, [Shvaiko, 05], Ed. Stefano Spaccapietra. IV 3730: doi:10.1007/11603412_5; Shvaiko, P., A Classification of Schema-based Matching Approaches (2005) Journal on Data Semnatics, (4), pp. 146-171. , [Shvaiko, 05a]; Shvaiko, P., Giunchiglia, F., Schorlemmer, M., McNeill, F., Bundy, A., Marches, M., Yatskevich, M., (2006) OpenKnowledge Deliverable 3.1.: Dynamic Ontology Matching: A Survey., , [Shvaiko, 06], Department of Information Engineering and Computer Science, DIT-06-046, 27 July; Shvaiko, P., Euzenat, J., Ten Challenges for Ontology Matching (2008) On the Move to Meaningful Internet Systems: OTM 2008, 5332, pp. 1164-1182. , http://dx.doi.org/10.1007/978-3-540-88873-4_18, [Shvaiko, 08], In ed. Robert Meersman and Zahir Tari, Springer Berlin / Heidelberg; Shvaiko, P., Euzenat, J., Ontology Matching: State of the Art and Future Challenges (2013) Knowledge and Data Engineering, IEEE Transactions On 25 (1), pp. 158-176. , [Shvaiko, 13], TrasLab, Inf. Trentina, Trento, Italy: doi:10.1109/TKDE.2011.253; Sosnovsky, S., Brusilovsky, P., Yudelson, M., Mitrovic, A., Mathews, M., Kumar, A., Semantic Integration of Adaptive Educational Systems (2009) Advances in Ubiquitous User Modelling, pp. 134-158. , [Sosnovsky, 09], In ed. A Kuflik, T., Berkovsky, S., Carmagnola, F., Heckmann D., & Krüger, LNCS 5830. Berlin Heidelberg: Springer-Verlag, Berlin Heidelberg; Stewart, C., Cristea, A., Celik, I., Ashman, H., Interoperability Between AEH User Models (2006) Proceedings of the Joint International Workshop on Adaptivity, , http://doi.acm.org/10.1145/1149933.1149937, [Stewart, 06], In Personalization & the Semantic Web, 21-30. Odense, Denmark, ACM. doi:10.1145/1149933.1149937; Thuy, P., (2012) Hybrid Similarity Measure for XML Data Integration and Transformation, , [Thuy, 12], Ph.D. Dissertation. Department of Computer Engineering, Kyung Hee University, Seoul, Korea; Trella, M., Cornejo, R., Guzman, E., Bueno, D., An Educational Component Based Framework for Web ITS Development (2003) Proceedings of the 2003 International Conference on Web Engineering ICEW 2722, pp. 134-143. , [Trella, 03], In Springer-Verlag, Heidelberg, 2003; Uschold, M., Gruninger, M., Ontologies and Semantics for Seamless Connectivity (2004) SIGMOD Rec., 33 (4), pp. 58-64. , http://doi.acm.org/10.1145/1041410.1041420, [Uschold, 04], doi:10.1145/1041410.1041420; Van der Sluijs, K., Houben, G.J., A Generic Component for Exchanging User Models Between Web-based Systems (2006) International Journal of Continuing Engineering Education and Life Long Learning, 16 (1-2), pp. 64-76. , http://wwwis.win.tue.nl/~houben/respub/ijceell2006, [Van der Sluijs, 06]; Vassileva, J., Distributed User Modelling for Universal Information Access (2001) Proceedings of the 9th International Conference on Human-Computer Interaction, pp. 122-126. , [Vassileva, 01], In Ed. Lawrence Erlbaum, New Orleans, USA; Viviani, M., Bennani, N., Egyed-Zsigmond, E., A Survey on User Modeling in Multi-application Environments (2010) Proceedings of the 2010 Third International Conference on Advances in Human-Oriented and Personalized Mechanisms, pp. 111-116. , http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5600339, [Viviani, 10], In Technologies and Services, Nice, France. Ieee. doi:10.1109/CENTRIC.2010.30; Wache, H., Vögele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., Hübner, S., Ontology-based Integration of Information-a Survey of Existing Approaches (2001) IJCAI--01 Workshop: Ontologies and Information Sharing, pp. 108-117. , http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.8073, [Wache, 01], In ed. H Stuckenschmidt; Wang, Y., Cena, F., Carmagnola, F., Cortassa, O., Gena, C., Stash, N., Aroyo, L., RSS-Based Interoperability for User Adaptive Systems (2008) Proceedings of the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 353-356. , http://dx.doi.org/10.1007/978-3-540-70987-9_52, [Wang, 08], In Ed. Wolfgang et al. Nejdl, Berlin, Heidelberg: Springer-Verlag, doi:10.1007/978-3-540-70987-9_52; (2007) WHO Regional Office for Europe: The Challenge of Obesity in the WHO European Region and the Strategies for Response., , http://www.euro.who.int/document/E90711.pdf, [WHO Regional Office for Europe, 07], Available at Accesed on February 10th, 2012; Wu, Z., Palmer, M., Verb Semantics and Lexical Selection (1994) Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, pp. 133-138. , In Las Cruces, NM, USA RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - A major challenge for creating personalized diet and activity applications is to capture static, semi-static and dynamic information about a person in a user-friendly way. Sharing and reusing information between heterogeneous sources like social networking applications, personal health records, specialized applications for diet and exercise monitoring, and personal devices with attached sensors can achieve a better understanding of the user. Gathering distributed user information from heterogeneous sources and making sense of it to enable user model interoperability entails handling the semantic heterogeneity of the user models. In this paper, we enhance the process of concept alignment to automatically determine semantic mapping relations to enable interoperability between heterogeneous health and fitting applications. We add an internal structure similarity measure to increase the quality of generated mappings of our previous work. We show that the addition of an internal structure analysis of source data in the process of concept alignment improves the efficiency and effectiveness of measuring results. Constrain and data type verification done in the internal structure analysis proved to be useful when dealing with common conflicts between concepts. © J.UCS. ER - TY - CHAP T1 - Distributed geospatial data management for entomological and epidemiological studies A1 - Martins, H A1 - Rocha, J G Y1 - 2012/// KW - Feasibility Studies KW - Information Systems JF - Discovery of Geospatial Resources: Methodologies, Technologies, and Emergent Applications SP - 220 EP - 240 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898317986&doi=10.4018%2F978-1-4666-0945-7.ch011&partnerID=40&md5=928db14bbfde6822db6a3cd4a6aa3bc4 N1 - Cited By :1 Export Date: 10 September 2018 References: Anselin, L., Interactive techniques and exploratory spatial data analysis (1999) Geographical Information Systems: Principles, Techniques, Management and Applications, pp. 253-266. , Longley, P. A. (Eds.), Horboken, NJ: John Wiley & Sons, Inc; Boulos, M., Towards evidence-based, GIS-driven national spatial health information infrastructure and surveillance services in the United Kingdom (2004) International Journal of Health Geographics, 3 (1), pp. 1-50. , doi:10.1186/1476-072X-3-1; Boulos, M., Honda, K., Web GIS in practice IV: Publishing your health maps and connecting to remote WMS sources using the open source UMN MapServer and DM solutions MapLab (2006) International Journal of Health Geographics, 5 (1), pp. 1-7. , doi:10.1186/1476-072X-5-6; Croner, C., Public health, GIS, and the internet (2003) Annual Review of Public Health, 24, pp. 57-82. , doi:10.1146/annurev.publhealth.24.012902.140835; Doyle, J., Han, Q., Weakliam, J., Bertolotto, M., Wilson, D., Developing nonproprietary personalized maps for Web and mobile environments (2005) Web and Wirelless Geographical Information Systems, 3428, pp. 181-194. , doi:10.1007/11427865_14; Durr, P., Spatial epidemiology: Introduction and overview (2004) GIS and Spatial Analysis in Veterinary Science, pp. 35-64. , Durr, P., & Gatrell, A. (Eds.), Oxfordshire, UK: CABI Publishing. doi:10.1079/9780851996349.0035; Elliott, P., Wartenberg, D., Spatial epidemiology: Current approaches and future challenges (2004) Environmental Health Perspectives, 112 (9), pp. 998-1006. , doi:10.1289/ehp.6735; Gao, S., Mioc, D., Anton, F., Yi, X., Coleman, D., Online GIS services for mapping and sharing disease information (2008) International Journal of Health Geographics, 7 (1), pp. 1-12. , doi:10.1186/1476-072X-7-8; Gatrell, A., Senior, M., Health and health care applications (1999) Geographical Information Systems: Principles, Techniques, Management and Applications, pp. 925-938. , Longley, P. A. (Eds.), Horboken, NJ: John Wiley & Sons, Inc; Goodchild, M.F., Communicating geographic information in a digital age (2000) Annals of the Association of American Geographers. Association of American Geographers, 90 (2), pp. 344-355. , doi:10.1111/0004-5608.00198; Houe, H., Ersboll, A.K., Toft, N., (2004) Introduction to Veterinary Epidemiology, , Denmark, Biofolia; Kamadjeu, R., Tolentino, H., Web-based public health geographic information systems for resources-constrained environment using scalable vector graphics technology: A proof of concept applied to the expanded program on immunization data (2006) International Journal of Health Geographics, 5 (1), pp. 1-8. , doi:10.1186/1476-072X-5-24; Kim, M., Kim, M., Lee, E., Joo, I., Web services framework for geo-spatial services (2005) Web and Wireless Geographical Information Systems, 3428, pp. 1-13. , doi:10.1007/11427865_1; Kistemann, T., Dangendorf, F., Schweikart, J., New perspectives on the use of geographical information systems (GIS) in environmental health sciences (2002) International Journal of Hygiene and Environmental Health, 205 (3), pp. 169-181. , doi:10.1078/1438-4639-00145; Lakhani, K., von Hippel, E., How open source software works: Free user-to-user assistance (2003) Research Policy, 32 (6), pp. 923-943. , doi:10.1016/S0048-7333(02)00095-1; Lembo, A.J., Wagenet, L.P., Schusler, T., Degloria, S.D., Creating affordable internet map server applications for regional scale applications (2007) Journal of Environmental Management, 85 (4), pp. 1120-1131; Luaces, M., Brisaboa, N., Parama, J., Viqueira, J., A generic framework for GIS applications (2005) Web and Wireless Geographical Information Systems, 3428, pp. 94-109. , doi:10.1007/11427865_8; Maclachlan, J.C., Jerrett, M., Abernathy, T., Sears, M., Bunch, M.J., Mapping health on the internet: A new tool for environmental justice and public health research (2007) Health & Place, 13 (1), pp. 72-86. , doi:10.1016/j.healthplace.2005.09.012; Mellor, P., Wittmann, E., Bluetongue virus in the Mediterranean basin 1998-2001 (2002) Veterinary Journal (London, England), 164, pp. 20-37. , doi:10.1053/tvjl.2002.0713; Mellor, P.S., Boorman, J., Baylis, M., Culicoides biting midges: Their role as arbovirus vectors (2000) Annual Review of Entomology, 45, pp. 307-340. , doi:10.1146/annurev.ento.45.1.307; Mitchell, T., (2005) Web Mapping Illustrated, , New York, NY, O'Reilly; Nebert, D.D., (2004) The SDI Cookbook, , http://www.gsdi.org/docs2004/Cookbook/cookbookV2.0.pdf, (Ed.), Retrieved from; (2010) OpenGIS Web Map Service (WMS) Implementation Specification, , http://www.opengeospatial.org/stan-dards/wms, OGC, Retrieved August 2010 from; Peng, Z., Internet GIS for public participation (2001) Environment and Planning. B, Planning & Design, 28 (6), pp. 889-905. , doi:10.1068/b2750t; Pfeiffer, D., Hugh-Jones, M., Geographical information systems as a tool in epidemiological assessment and wildlife disease management (2002) Revue Scientifique Et Technique De L'Office International Des Epizooties, 21 (1), pp. 91-102; Pfeiffer, D., Robinson, T., Stevenson, M., Stevens, K., Rogers, D., Clements, A., (2008) Spatial Analysis in Epidemiology, , Oxford, UK: Oxford University Press. doi:10.1093/acprof:oso/9780198509882.001.0001; Purse, B., Mellor, P., Baylis, M., Bluetongue in the Mediterranean: Prediction of risk in space and time (2005) Environmental Change and Malaria Risk: Global and Local Implications, pp. 125-136. , a, Takken, W. (Eds.), Dordrecht, The Netherlands: Springer. doi:10.1007/978-1-4020-3929-4_12; Purse, B., Mellor, P., Rogers, D., Samuel, A., Mertens, P., Baylis, M., Climate change and the recent emergence of bluetongue in Europe (2005) Nature Reviews Microbiology, 3 (2), pp. 171-181. , b, doi:10.1038/nrmicro1090; Rushton, G., Public health, GIS, and spatial analytic tools (2003) Annual Review of Public Health, 24, pp. 43-56. , doi:10.1146/annurev.publ-health.24.012902.140843; Sellers, R.F., Mellor, P.S., Temperature and the persistence of viruses in culicoides spp. during adverse conditions (1993) Revue Scientifique Et Technique (International Office of Epizootics), 12 (3), pp. 733-755; Sondheim, M., Gardels, M., Buehler, K., GIS interoperability (1999) Geographical Information Systems: Principles, Techniques, Management and Applications, pp. 347-358. , Longley, P. A. (Eds.), Horboken, NJ: John Wiley & Sons, Inc; Vatsavai, R.R., Shekhar, S., Burk, T.E., Lime, S., UMN-MapServer: A high-performance, interoperable, and open source web mapping and geo-spatial analysis system (2006) Geographic Information Science, pp. 400-417. , Raubal, M. (Eds.), Berlin, Germany: Springer-Verlag. doi:10.1007/11863939_26; Verwoerd, D.W., Erasmus, B.J., Bluetongue (2004) Infectious Diseases of Livestock, pp. 1201-1215. , Coetzer, J. W., & Tustin, R. C. (Eds.), Oxford, UK: Oxford University Press; Zeilhofer, P., Arraes Neto, P.S., Maja, W.Y., Vecchiato, D.A., A web-based, componentoriented application for spatial modelling of habitat suitability of mosquito vectors (2009) International Journal of Digital Earth, 2 (4), pp. 327-342. , doi:10.1080/17538940902887324; Zhang, T., Tsou, M.H., Developing a grid-enabled spatial web portal for internet GIServices and geospatial cyberinfrastructure (2009) International Journal of Geographical Information Science, 23 (5), pp. 605-630. , doi:10.1080/13658810802698571 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Geographical Information Systems (GIS) are now considered a valuable and essential tool to epidemiology. Epidemiological phenomena are strongly associated with spatial and temporal factors, and, as such, the use of GIS for epidemiological data recording and management may help health professionals to better understand spatio-temporal disease patterns. Bluetongue (BT) is an infectious disease of domestic and wild ruminants that has recently expanded to northern areas where it was never recorded. As a consequence, several entomological surveillance programs were implemented in European countries. Since these surveillance programs are natively distributed along countries, the supporting software platforms should handle the distributed nature of the program and its related data. The authors have studied the feasibility of a distributed web based application able to support the spatial nature of the entomological data. In fact, they designed a completely new thematic Spatial Data Infrastructure (SDI) where all components, data, metadata, services, policies, etc., and actors from the different institutions are considered. Their aim is not only to support the BT surveillance program but also to contribute to a more detailed knowledge about the epidemiology of the disease. Since the authors were able to design all the supporting software, all syntactical interoperability was guaranteed by the use of Open Geospatial Consortium (OGC) standards. The semantic interoperability was assured by design, by developing a unique data model. Data invariants are guaranteed either by the interface, with validation routines written in Javascript, or by the data constrains included in the database. Integration and interoperability with other BT programs might require some additional effort, but all the necessary semantic translation could be encapsulated into the WFS component. © 2012, IGI Global. ER - TY - CONF T1 - Integration of health data using enterprise service bus A1 - Masethe, H D A1 - Olugbara, O O A1 - Ojo, S O A1 - Adewumi, A O Y1 - 2013/// KW - Application programs KW - Computer science KW - DHIS KW - EHR KW - Enterprise Service Bus KW - Enterprise service bus KW - HIS KW - HL7 KW - Health KW - Information Systems KW - Information use KW - Interoperability KW - Microarrays KW - NHIMS KW - SOA KW - South Africa VL - 2 SP - 839 EP - 843 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903467690&partnerID=40&md5=835ca31fa947e5afee1b60f79b4c83c5 N1 - Cited By :1 Export Date: 10 September 2018 References: Motswaledi, A., Ramokgopa, G., (2012) National EHealth Strategy South Africa, , Pretoria, South Africa; Zuma, N.D., (1994) White Paper for the Transformation of the Health System in South Africa, , Pretoria, South Africa; Health solutions (2013) Gijima, , http://www.gijima.com/services-and-solutions/health-solutions, [Accessed: 17-Mar-2013]; Matsotso, M.M., (2011) District Health Management Information System (DHMIS), , Pretoria; Ketaki, K., (2009) Data Integration in Reporting Systems Using Enterprise Service Bus, , Ohio State University, Ohio; Hansen, D.P., Pang, C., Maeder, A., HDI: Integrating health data and tools (2007) Soft Comput, 11, pp. 361-367; Tsiknakis, M., An open, component-based information infrastructure for integrated health information networks (2002) International Journal of⋯, 68 (1-3), pp. 3-26. , Dec; Braa, J., Hedberg, C., The struggle for district-based health information systems in South Africa (2002) The Information Society, 18 (2), pp. 113-127. , Mar; Gul, O., Al-Qutayri, M., Vu, Q.H., Yeun, C.Y., Data integration of electronic health records using artificial neural networks (2012) The 7th International Conference for Internet Technology and Secured Transactions, 7, pp. 313-317; Smith, B., Austin, A., Brown, M., King, J., Lankford, J., Meneely, A., Williams, L., (2010) Challenges for Protecting the Privacy of Health Information: Required Certification can Leave Common Vulnerabilities Undetected, pp. 1-12; Roque, F.S., Slaughter, L., Tkat, A., (2010) A Comparison of Several Key Information Visualization Systems for Secondary use of Electronic Health Record Content, pp. 76-83. , no. June; Dogac, A., (2008) Interoperability in EHealth Systems, pp. 2026-2027. , no. July; Sartipi, K., Yarmand, M.H., Down, D.G., Mined-knowledge and decision support services in electronic health (2007) International Workshop on Systems Development in SOA Environments SDSOA07 ICSE Workshops 2007, pp. 1-6; Rajan, S., Ramaswamy, S., On the need for a holistic approach to information quality in healthcare and medicine (2010) ACMSE, pp. 1-5; Factors that have contributed to a lack of integration in health information systems security (2004) The Journal of Information Technology in Healthcare, 5 (2), pp. 313-328. , F. J; Seebode, C., Trautwein, M., Ort, M., Lehmann, J., For semantic exploitation of clinical data (2013) International MultiConference of Engineers and Computer Scientists, 1, pp. 13-15; Hägglund, M., Scandurra, I., Moström, D., Koch, S., Bridging the gap: A virtual health record for integrated home care⋯ (2007) Journal of Integrated Care, 7, pp. e26. , June Jan; Gong, Y., Healthcare information integration and shared platform based on service-oriented architectures (2010) 2nd International Conference on Signal Processing Systems (ICSPS), pp. 523-527; Nazih, M., Alaa, G., Generic service patterns for web enabled public healthcare systems (2011) 7th International Conference on Next Generation Web Services Practices, pp. 274-279 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The Department of Health in South Africa has a challenge in the healthcare service delivery monitoring and performance due to the non-existence of a functional health information system capable to produce the real time information. The health system is characterized by lack of coordination and automation, dominance of the manual and lack of interoperability between the existing health information systems. The government has invested considerable in the acquisition of software applications that did not generate expected outcomes. The research proposes a framework as a roadmap to guide the design of the integrated national health patient based information system. ER - TY - JOUR T1 - Lessons Learned in Creating Interoperable Fast Healthcare Interoperability Resources Profiles for Large-Scale Public Health Programs A1 - Matney, Susan A1 - Heale, Bret A1 - Hasley, Steve A1 - Decker, Emily A1 - Frederiksen, Brittni A1 - Davis, Nathan A1 - Langford, Patrick A1 - Ramey, Nadia A1 - Huff, Stanley Y1 - 2019/01// JF - Applied Clinical Informatics VL - 10 IS - 01 SP - 087 EP - 095 DO - 10.1055/s-0038-1677527 UR - http://www.thieme-connect.de/DOI/DOI?10.1055/s-0038-1677527 N2 - Objective This article describes lessons learned from the collaborative creation of logical models and standard Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) profiles for family planning and reproductive health. The National Health Service delivery program will use the FHIR profiles to improve federal reporting, program monitoring, and quality improvement efforts. ER - TY - JOUR T1 - Laying a community-based foundation for data-driven semantic standards in environmental health sciences A1 - Mattingly, C J A1 - Boyles, R A1 - Lawler, C P A1 - Haugen, A C A1 - Dearry, A A1 - Haendel, M Y1 - 2016/// KW - Cooperative Behavior KW - Environmental Exposure KW - Environmental Health KW - Humanism KW - Humanities KW - Humans KW - Internet KW - National Institute of Environmental Health Science KW - Review KW - Semantics KW - United States KW - community KW - computer program KW - cooperation KW - data base KW - education KW - environmental exposure KW - environmental health KW - funding KW - gene ontology KW - human KW - language KW - national health organization KW - phenotype KW - priority journal KW - quality control KW - standards KW - statistics and numerical data JF - Environmental Health Perspectives VL - 124 IS - 8 SP - 1136 EP - 1140 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84980357135&doi=10.1289%2Fehp.1510438&partnerID=40&md5=ccca7855a12548c85cc3e5e728b6af00 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Mattingly et al. - 2016 - Laying a community-based foundation for data-driven semantic standards in environmental health sciences.pdf N1 - Cited By :3 Export Date: 10 September 2018 References: Ashburner, M., Ball, C.A., Blake, J.A., Botstein, D., Butler, H., Cherry, J.M., Gene ontology: Tool for the unification of biology. The Gene Ontology Consortium (2000) Nat Genet, 25, pp. 25-29; (2015) A Curated, Searchable Portal of Inter-Related Data Standards, Databases, and Policies in the Life, Environmental and Biomedical Sciences, , https://www.biosharing.org, Biosharing, accessed 1 February 2016]; Davis, A.P., Grondin, C.J., Lennon-Hopkins, K., Saraceni-Richards, C., Sciaky, D., King, B.L., The Comparative Toxicogenomics Database’s 10th year anniversary: Update 2015 (2015) Nucleic Acids Res, 43, pp. D914-D920; (2015) Github, , https://github.com, accessed 10 October 2015; (2015) About: The Gene Ontology Project, , http://geneontology.org/page/about, accessed 10 October 2015]; Haendel, M.A., Balhoff, J.P., Bastian, F.B., Blackburn, D.C., Blake, J.A., Bradford, Y., Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon (2014) J Biomed Semantics, 5, p. 21; Köhler, S., Doelken, S.C., Mungall, C.J., Bauer, S., Firth, H.V., Bailleul-Forestier, I., (2014); The Human Phenotype Ontology project: Linking molecular biology and disease through phenotype data Nucleic Acids Res, 42, pp. D966-D974; Liu, B., Pop, M., ARDB-Antibiotic Resistance Genes Database (2009) Nucleic Acids Res, 37, pp. D443-D447. , http://ardb.cbcb.umd.edu, accessed 10 October 2015]; Margolis, R., Derr, L., Dunn, M., Huerta, M., Larkin, J., Sheehan, J., The National Institutes of Health’s Big Data to Knowledge (BD2K) initiative: Capitalizing on biomedical big data (2014) J am Med Inform Assoc, 21, pp. 957-958; (2015) The Monarch Initiative, , http://monarchinitiative.org, accessed 10 October 2015]; (2014) Software Discovery Index Meeting Report-Request for Comments, , https://nciphub.org/resources/889/download/Software_Discovery_Index_Workshop_Report.pdf, accessed 1 February 2016]; (2015) Computer Access to Research on Dietary Supplements (CARDS) Database, , http://ods.od.nih.gov/Research/CARDS_Database.aspx, accessed 10 October 2015]; (2016) Children’s Health Exposure Analysis Resource (CHEAR), , http://www.niehs.nih.gov/research/supported/exposure/chear/, accessed 1 February 2016]; Peterson, J., Garges, S., Giovanni, M., McInnes, P., Wang, L., The NIH Human Microbiome Project (2009) Genome Res, 19, pp. 2317-2323. , NIH HMP Working Group; (2016), http://www.ncbi.nlm.nih.gov, accessed 1 February 2016]; (2015), http://www.ncbi.nlm.nih.gov/sra, accessed 10 October 2015]; (2015) Bioportal Homepage, , http://bioportal.bioontology.org, accessed 10 October 2015]; (2015) Gene, , http://www.ncbi.nlm.nih.gov/gene/, accessed 10 October 2015]; (2015) Medical Subject Headings, , http://www.nlm.nih.gov/mesh, accessed 10 October 2015]; (2011) Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease (2011), , Washington, DC:National Academies Press; (2015) Research Coordination Networks (RCN). 2015, , http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=11691, accessed 10 October 2015]; (2015), http://orcid.org, accessed 10 October 2015]; (2016) OWL 2 Web Ontology Language, Document Overview, , http://www.w3.org/TR/owl2-overview/, OWL (Web Ontology Language), Second Edition), accessed 1 February 2016]; (2014) Phenotype Day @ ISMB 2014. Joint Bio-Ontologies and Biolink Sigs Session, , http://phenoday2014.bio-lark.org, Phenoday (Phenotype Day), 12 July, 2014-Boston, US. Description, accessed 1 February 2016]; Port, J.A., Cullen, A.C., Wallace, J.C., Smith, M.N., Faustman, E.M., Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments (2014) Environ Health Perspect, 122, pp. 222-228; Port, J.A., Wallace, J.C., Griffith, W.C., Faustman, E.M., Metagenomic profiling of microbial composition and antibiotic resistance determinants in Puget Sound (2012) Plos One, 7; Richesson, R.L., Nadkarni, P., Data standards for clinical research data collection forms: Current status and challenges (2011) J am Med Inform Assoc, 18, pp. 341-346; Schriml, L.M., Mitraka, E., The Disease Ontology: Fostering interoperability between biological and clinical human disease-related data (2015) Mamm Genome, 26, pp. 584-589; Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration (2007) Nat Biotechnol, 25, pp. 1251-1255; (2015) SMW (Semantic Mediawiki), , https://semantic-mediawiki.org, accessed 1 February 2016]; Tenenbaum, J.D., Sansone, S.A., Haendel, M., A sea of standards for omics data: Sink or swim? (2014) J am Med Inform Assoc, 21, pp. 200-203; Tenopir, C., Dalton, E.D., Allard, S., Frame, M., Pjesivac, I., Birch, B., Changes in data sharing and data reuse practices and perceptions among scientists worldwide (2015) Plos One, 10; Van Panhuis, W.G., Paul, P., Emerson, C., Grefenstette, J., Wilder, R., Herbst, A.J., A systematic review of barriers to data sharing in public health (2014) BMC Public Health, 14, p. 1144; (2015) Protégé, , http://protege.stanford.edu, accessed 1 February 2016]; (2015) Welcome to Wikipedia, , https://en.wikipedia.org/wiki/Main_Page, accessed 1 February 2016]; Wild, C.P., Complementing the genome with an “exposome”: The outstanding challenge of environmental exposure measurement in molecular epidemiology (2005) Cancer Epidemiol Biomarkers Prev, 14, pp. 1847-1850; Xiang, Z., Mungall, C., Ruttenberg, A., He, Y., Ontobee: A Linked Data Server and Browser for Ontology Terms (2011) Proceedings of the 2Nd International Conference on Biomedical Ontologies (ICBO), pp. 279-281. , http://ceur-ws.org/Vol-833/paper48.pdf, 28-30 July 2011, Buffalo, New York, accessed 1 February 2016]; Youngblood, J., Wallace, J., Port, J., Cullen, A., Faustman, E., Metagenomic applications for environmental health surveillance: A one health case study from the Pacific Northwest ecosystem (2014) Planet@Risk, 2 (4), pp. 281-284. , https://planet-risk.org/index.php/pr/article/viewFile/106/221, accessed 1 February 2016]; Zimmerman, A.S., New knowledge from old data. The role of standards in the sharing and reuse of ecological data (2008) Science, Technology, & Human Values, 33, pp. 631-652 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: Despite increasing availability of environmental health science (EHS) data, development, and implementation of relevant semantic standards, such as ontologies or hierarchical vocabularies, has lagged. Consequently, integration and analysis of information needed to better model environmental influences on human health remains a significant challenge. Objectives: We aimed to identify a committed community and mechanisms needed to develop EHS semantic standards that will advance understanding about the impacts of environmental exposures on human disease. Methods: The National Institute of Environmental Health Sciences sponsored the “Workshop for the Development of a Framework for Environmental Health Science Language” hosted at North Carolina State University on 15-16 September 2014. Through the assembly of data generators, users, publishers, and funders, we aimed to develop a foundation for enabling the development of community-based and data-driven standards that will ultimately improve standardization, sharing, and interoperability of EHS information. Discussion: Creating and maintaining an EHS common language is a continuous and iterative process, requiring community building around research interests and needs, enabling integration and reuse of existing data, and providing a low barrier of access for researchers needing to use or extend such a resource. Conclusions: Recommendations included developing a community-supported web-based toolkit that would enable a) collaborative development of EHS research questions and use cases, b) construction of user-friendly tools for searching and extending existing semantic resources, c) education and guidance about standards and their implementation, and d) creation of a plan for governance and sustainability. © 2016, Public Health Services, US Dept of Health and Human Services. All rights reserved. ER - TY - BOOK T1 - The road to the future of healthcare: Transmitting interoperable healthcare data through a 5G based communication platform A1 - Mavrogiorgou, A A1 - Kiourtis, A A1 - Touloupou, M A1 - Kapassa, E A1 - Kyriazis, D A1 - Themistocleous, M Y1 - 2019/// JF - Lecture Notes in Business Information Processing VL - 341 SP - 383 EP - 401 SN - 9783030113940 DO - 10.1007/978-3-030-11395-7_30 N2 - ©2019, Springer Nature Switzerland AG. Current devices and sensors have revolutionized our daily lives, with the healthcare domain exploring and adapting new technologies. The rapid explosion of digital healthcare happened with the help of current 4G LTE technologies including innovations such as the continuous monitoring of patient vitals, teleporting doctors to a virtual environment or leveraging Artificial Intelligence to generate new medical insights. The arised problem is that current 4G LTE based communication platforms will not be able to keep up with the exploding connectivity demands. This is where the new 5G technology comes, expected to support ultra-reliable, low-latency and massive data communications. In this paper, an end-to-end approach is being provided in the healthcare domain for gathering medical data, anonymizing it, cleaning it, making it interoperable, and finally storing it through 5G network technologies, for their transmission to a different location, supporting real-time results and decision-making. ER - TY - CONF T1 - PARENT joint action: Increasing the added value of patient registries in a cross-border setting A1 - Meglič, M A1 - Doupi, P A1 - Pristaš, I A1 - Skalkidis, Y A1 - Zaletel, M A1 - Orel, A Y1 - 2013/// KW - Cross-border KW - Electronic Health Records KW - Europe KW - European Union KW - Government Programs KW - Guidelines as Topic KW - Health Information Management KW - Information Dissemination KW - International Cooperation KW - Knowledge Management KW - Medical Record Linkage KW - Patient Registries KW - Registries KW - Semantics KW - electronic medical record KW - government KW - information dissemination KW - international cooperation KW - medical record KW - organization and management KW - practice guideline KW - procedures KW - register KW - standards VL - 192 IS - 1 SP - 1161 EP - 1161 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894308168&doi=10.3233%2F978-1-61499-289-9-1161&partnerID=40&md5=f1771065872c59e57fbfa57c82133e4b N1 - Cited By :2 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Patient registries are poorly interoperable and as a result data exchange or aggregation across organizations, regions and countries for secondary purposes (i.e. research and public health) is difficult to perform. PARENT Joint Action aims to provide EU Member States with a set of guidelines, recommendations and tools to support setting-up, management and governance of interoperable patient registries, thus helping EU Member States to drive down cost and interoperability risks of patient registries as well as improving secondary us-age of registry data in a cross-border setting. © 2013 IMIA and IOS Press. ER - TY - CONF T1 - BioMIMS - SOA platform for research of rare hereditary diseases A1 - Melament, A A1 - Peres, Y A1 - Vitkin, E A1 - Kostirev, I A1 - Shmueli, N A1 - Sangiorgi, L A1 - Mordenti, M A1 - D'Ascia, S Y1 - 2011/// KW - Buses KW - Data analytics KW - Data fusion KW - Data integration KW - Data mining KW - Genetic Diseases, Inborn KW - Health care KW - Healthcare standards KW - Hospitals KW - Information services KW - Information technology KW - Integration KW - Medical imaging KW - Message oriented middleware KW - Metadata KW - Middleware KW - Pedigree analysis KW - Rare hereditary diseases KW - Research KW - Service Oriented KW - Service oriented architecture KW - Service oriented architecture (SOA) KW - Services management KW - Standards SP - 83 EP - 90 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051936312&doi=10.1109%2FSRII.2011.19&partnerID=40&md5=2fe301ff6dff03fed7d89d9f51d1879f N1 - Cited By :3 Export Date: 10 September 2018 References: http://www.cwhonors.org; http://cwhonors.org/viewCaseStudy2010.asp?NominationID=222&Username= cbroibi; http://www.ibm.com/smarterplanet/us/en/; TRICARE; rare diseases definition. Final rule (2010) Fed Regist., 75 (151), p. 47458. , Office of the Secretary, DoD, Aug 6; (2005) Rare Diseases: Understanding This Public Health Priority, , www.eurordis.org; Michael, B., (2008) Introduction to Service-Oriented Modeling: Service Analysis, Design, and Architecture, , John Wiley and Sons; Banavar, G., Chandra, T., Strom, R., Sturman, D., A case for message oriented middleware (1999) Proceedings of the 13th International Symposium on Distributed Computing, pp. 1-18. , Bratislava, Slovak Republic, Springer: Berlin; Yu, C., Yao, Z., XML-Based DICOM data format (2009) Journal of Digital Imaging, 23 (2), pp. 192-202. , DOI: 10.1007/s10278-008-9173-5; Shabo, A., Hughes, S.K., Family history information exchange services using HL7 clinical genomics standard specifications (2005) International Journal on Semantic Web & Information Systems, 1 (4), pp. 42-65; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., Shabo, A., HL7 clinical document architecture, release 2 (2006) Journal of the American Medical Informatics Association, 13 (1), pp. 30-39. , DOI 10.1197/jamia.M1888, PII S1067502705001878; http://www.hl7.org/; http://www.ihe.net/profiles/; IBM Enterprise Content Management, , http://www-01.ibm.com/software/data/content-management/; Quinlan, J.R., Induction of decision trees (1986) Machine Learning, 1 (1), pp. 81-106; MacQueen, J.B., Some methods for classification and analysis of multivariate observations (1967) Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281-297. , University of California Press; Irad, B.-G., Bayesian networks (2007) Encyclopedia of Statistics in Quality and Reliability, , Ruggeri, Fabrizio; Kennett, Ron S. Faltin, Frederick W. John Wiley & Sons. doi: 10.1002/9780470061572.eqr089. ISBN 978-0-470-01861-3; http://commons.apache.org/math; Bovée, J.V.M.G., Hogendoorn, P.C.W., (2002) Multiple Osteochondromas. in World Health Organization Classification of Tumours. Pathology and Genetics of Tumours of Soft Tissue and Bone, pp. 360-362. , Hogendoorn PCW: Edited by: Fletcher CDM, Unni KK and Mertens F. Lyon, IARC Press; Rauch, F., Glorieux, F.H., Osteogenesis imperfecta (2004) Lancet, 363 (9418), pp. 1377-1385. , DOI 10.1016/S0140-6736(04)16051-0, PII S0140673604160510; Osteogenesis Imperfecta(OI), , http://www.easilybrokenbones.com RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: BioMIMS is an award-winning platform that realizes our vision for how information technologies can support the research of rare hereditary diseases. a disease is considered rare when it affects only a small percentage of the population; most rare diseases are genetic. Researching rare hereditary diseases imposes several significant challenges for dedicated informatics tools. Collaboration is a critical element in the research process, and partnerships among research centers are essential to ensure advances in understanding and treating these diseases. Because a single research center usually lacks sufficient data for conducting meaningful research, data must be shared among partners. Consequently, the first challenge of the underlying platform is to merge information gathered from dispersed hospitals, research centers, clinics, labs and other facilities. Additionally, various data types such as clinical, genomic, imaging data, and pedigrees, must be combined to create a comprehensive disease view. Obtaining and visualizing all the available data is the first step toward gaining insights through analytics. Research questions cannot always be known in advance and tend to change over time; therefore, an effective platform should be able to integrate various data mining and analytic algorithms. Platform Architecture: We designed BioMIMS based on Service Oriented Architecture (SOA) principles. The BioMIMS architecture is composed of a rich set of fine-grained services decoupled by a central bus. The bus orchestrates the existing services according to predefined workflows, following the Message Oriented Middleware (MOM) concept. Message queues provide temporary storage when the destination service is busy or not connected. All the messages running through the bus and handled by the different services are based on approved industry standards. Medical images are uploaded to and retrieved from the appropriate system service in DICOM v3.0 format, while clinical and family history data areuploaded and retrieved according to HL7 v2.x and HL7 v3 Family History standards. Patients may have different patient identifiers in different systems. to ensure the correct identification of patients and their data in a standard manner, BioMIMS supports IHE Patient Identifier Cross-Reference (PIX) and Patient Demographic Query (PDQ) transactions. to enable interoperability at the cross-hospital and regional levels, metadata are extracted from the stored information according to IHE Cross-enterprise Document Sharing (XDS/XDS-I) Profiles. a SOA approach, based on standard interfaces has numerous benefits, namely: A) a flexible architecture that allows easy integration of new services, creation of new workflows by reusing existing ones, and easy integration with existing applications; b) inherent scalability; c) speedy custom application development that reduces total IT costs. Platform Validation: BioMIMS was validated by researchers of the Rizzoli Orthopaedic Institute (IOR). IOR researchers uploaded and investigated data for two different orthopedic diseases - Multiple Osteochondromas (MO) and Osteogenesis Imperfecta (OI) The researchers confirmed several presumed insights for the available data using BioMIMS. Moreover, a few interesting points arose during the validation process, helping to determine goals for future studies. © 2011 IEEE. ER - TY - JOUR T1 - Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress A1 - Meystre, S M A1 - Lovis, C A1 - Bürkle, T A1 - Tognola, G A1 - Budrionis, A A1 - Lehmann, C U Y1 - 2017/// KW - Biomedical Research KW - Data Mining KW - Delivery of Health Care KW - Forecasting KW - Health Care Costs KW - Humans KW - Privacy KW - data mining KW - forecasting KW - health care delivery KW - human KW - medical research JF - Yearbook of medical informatics VL - 26 IS - 1 SP - 38 EP - 52 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032830539&doi=10.15265%2FIY-2017-007&partnerID=40&md5=325ee268a968fceeabda083dae626602 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Meystre et al. - 2017 - Clinical Data Reuse or Secondary Use Current Status and Potential Future Progress.pdf N1 - Cited By :6 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research. Georg Thieme Verlag KG Stuttgart. ER - TY - CONF T1 - Ontology techniques for representing the problem of discourse: Design of solution application perspective A1 - Miah, S J A1 - Islam, H A1 - Samsudin, A Z H Y1 - 2017/// KW - Artificial intelligence KW - Big data KW - Business management KW - Computer privacy KW - Decision support systems KW - Design KW - Design solution KW - Design solutions KW - Distributed computer systems KW - End users KW - End-users KW - Human computer interaction KW - Interoperability KW - Knowledge components KW - Knowledge modelling KW - Ontology KW - Ontology-driven applications KW - Public administration KW - Record management systems KW - Semantic integration KW - Semantics KW - Social sciences computing KW - System research KW - Systems analysis KW - Universe of discourse SP - 148 EP - 153 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85017342338&doi=10.1109%2FCIT.2016.115&partnerID=40&md5=0293e037e459a21c90af9052b24c8bf4 N1 - Export Date: 10 September 2018 References: Sawass, A.F., Lu, J., Building an advance domain ontology model of information science (OIS) (2014) International Journal of Digital Information and Wireless Communication, 4 (2), pp. 258-266; Sprehe, J.T., The positive benefits of electronic records management in the context of enterprise content management (2005) Government Information Quarterly, 22 (2), pp. 297-303; Chen, Y.J., Development of a method for ontology-based empirical knowledge representation and reasoning (2010) Decision Support Systems, 50, pp. 1-20; Liddle, S.W., Hewett, K.A., Embley, D.W., An integrated ontology development environment for data extraction (2003) 2nd International Conference on Information Systems Technology and Its Applications, , National Technical University, Kharkiv, Ukraine, June 19-21; Miah, S.J., Kerr, D., Gammack, J., A design environment ontology for stakeholders developed decision support tools in the Australian dairy industry (2006) Proceedings of the 17th Australasian Conference on Information Systems (ACIS2006), , Adelaide, Australia; Navigli, R., Velardi, P., Learning domain ontologies from document warehouses and dedicated web sites (2004) Computational Linguistics, 30 (2), pp. 151-179; Abrahams, B., (2006) Tourism Information Systems Integration and UtilisationWithin the Semantic Web, , Unpublished PhD thesis. School of Management and Information Systems,Victoria University, Melbourne, Australia; Joo, J., Lee, S.M., Adoption of the Semantic Web for overcoming technical limitations of knowledge management systems (2009) Expert Systems with Applications, 36 (3), pp. 7318-7327; Foguem, K.B., Coudert, T., Geneste, L., Knowledge formalization in experience feedback processes: An ontology-based approach (2008) Special Issue on Enterprise Integration and Interoperability in Manufacturing Systems, , A. Molina and H. Panetto (Eds). Computers In Industry, 59/5, May; Chapurlat, V., Braesch, C., Verification, validation, qualification and certification of enterprise models: Statements and opportunities (2008) Special Issue on Enterprise Integration and Interoperability in Manufacturing Systems, , A. Molina and H. Panetto (Eds). Computers In Industry, 59/5, May; Jacinto, A.S., De Oliveira, J.M.P., An ontology-based architecture for intelligent tutoring system (2008) Interdisciplinary Studies in Computer Science, 19 (1), pp. 25-35; Panetto, H., Molina, A., Enterprise integration and interoperability in manufacturing systems: Trends and issues (2008) Computers in Industry, Elsevier, 59 (7), pp. 641-646; Genesereth, M.R., Nilsson, N.J., (1987) Logical Foundation of Artificial Intelligence, , Morgan Kaufmann, Los Altos, California; Gruber, T.R., A translation approach to portable ontology specification (1993) Knowledge Acquisition, 5 (2), pp. 199-220; Guarino, N., Formal ontology in information systems (1998) Proceedings of FOIS'98, pp. 3-15. , Trento, Italy, 6-8 June. Amsterdam, IOS Press; Fernández, M., (1996) CHEMICALS: Ontología Deelementos Químicos, , Final-Year Project, Facultad de Informática de la Universidad Politécnica de Madrid; Arpírez, J.C., Gómez-Pérez, A., Lozano, A., Pinto, H.S., Reference Ontology and (ONTO) 2 Agent: The ontology yellow pages (1998) Workshop on Applications of Ontologies and Problem-Solving Methods. European Conference on Artificial Intelligence (ECAI'98), , Brighton (United Kingdom); Uschold, M., Gruninger, M., Ontologies: Principles, methods and applications (1996) The Knowledge Engineering Review, 11, pp. 93-155; Staab, S., Schunurr, H.P., Studer, R., Sure, Y., Knowledge processes and ontologies (2001) IEEE Intelligent Systems, Special Issue on Knowledge Management, 16 (1), pp. 26-34; Mizoguchi, R., Ikeda, M., Seta, K., Vanwelkenhuysen, J., Ontology for modelling the world from problem solving perspectives (1995) Proceedings of IJCAI-95 Workshop on Basic Ontological Issues in Knowledge Sharing, pp. 1-12; Fernandez-Lopez, M., Gomez-Perez, A., Sierra, J.P., Sierra, A.P., Building a chemical ontology using methodology and the ontology design environment (1999) IEEE Intelligent Systems, 14 (1), pp. 37-46; Fernandez, M., Gomez-Perez, A., Juristo, N., METHONTOLOGY: From ontological art towards ontological engineering (1997) Presented to AAAI97, Workshop on Ontological Engineering, Stanford University, pp. 33-40; Noy, N., Fergerson, R., Musen, M., The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility (2000) Knowledge Engineering and Knowledge Management Methods, Models, and Tools, 1937, pp. 17-32. , In R. Dieng &O. Corby (Eds.); Uren, V., Cimiano, P., Iria, J., Handschuh, S., Vargas-Vera, M., Motta, E., Ciravegna, F., Semantic annotation for knowledge management: Requirements and a survey of the state of the art (2006) Web Semantics: Science, Services and Agents on the World Wide Web, 4 (1), pp. 14-28; Arbon, P., The development of conceptual models for mass-gathering health (2004) Prehospital and Disaster Medicine. the Official Journal of the National Association of EMS Physicians and the World Association for Emergency and Disaster Medicine in Association with the Acute Care Foundation, 19, pp. 208-212; Hyland-Wood, D., Carrington, D., Kaplan, S., Enhancing software maintenance by using semantic web techniques (2014) International Semantic WebConferences(ISWC)-2006, , http://www.itee.uq.edu.au/~dwood/papers/SoftwareMaintenanceViaSemWeb.pdf, Accessed on June 14; Miah, S.J., A new semantic knowledge sharing approach for egovernment systems (2014) 4th IEEE International Conference on Digital Ecosystems and Technologies, Dubai, United Arab Emirates, 457-462, 2010, URL, , http://ieeexplore.ieee.org/document/5610607/, Accessed on June 10; Miah, S.J., (2008) An Ontology Based Design Environment for Rural Decision Support, , Unpublished PhD Thesis, IIIE and Griffith Business School, Griffith University, Brisbane, Australia RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Ontology has been applied in various problem domains such as health, agriculture, public administration and business management, to develop solution models for effective knowledge modelling. The models help define structures of knowledge components and their relationship among them within a problem domain that may provide better representation of a system design architecture. Such basic model of knowledge components can provide a transparent approach for enhancing design thinking and comprehension for both users and system developers. This makes the ontology technique as one of the prominent techniques for designing system solution in a context-sensitive manner. In this paper, we describe the use of ontology in two design cases for representing the problem universe of discourse. First design case is on a record management system and second case is on a decision support system. For both system design cases, the ontology technique provided benefits for gaining semantic integration and interoperability in designing the solutions. Findings from our studies suggest that ontology enables provisions both to end users and to system developers for achieving design goals that in turn maximize various user benefits. © 2016 IEEE. ER - TY - ICOMM T1 - Open Data Protocol A1 - Microsoft Y1 - 2012/// UR - https://www.odata.org/ ER - TY - JOUR T1 - Design restful web service of national population database for supporting e-health interoperability service A1 - Miftakul Amin, M A1 - Sutrisman, A D I A1 - Stiawan, D A1 - Ermatita A1 - Maseleno, A Y1 - 2018/// JF - Journal of Theoretical and Applied Information Technology VL - 96 IS - 15 SP - 4794 EP - 4805 N2 - ©2005 – ongoing JATIT & LLS. The Government of the Republic of Indonesia nowdays has implemented a centralized national population database with Electronic Identity Card (e-ID) as the sole reference to the legality and validity of data used for various public services. In line with the population database, the government has also run a National Health Insurance Program which also needs e-ID card data to obtain health services. When patients visit health service providers such as hospitals, health centers, medical centers, and health clinics, personal data is requested for registration by showing ID cards, so the presence of a national demographic database is not yet optimal. The presence of RESTful Web Service technology enables communication between different platform applications, so the demographic database can be accessed using a variety of different client applications, operating systems, programming languages, and databases. This study aims to design the national demographic database using RESTful Web Services, which can be implemented to support e-health services. E-ID data can be used by the health provider for patient registration and patient referral. The demographic database can be used as a reference for valid demographic data. The test that has been done shows that the performance of the system design developed, reliable to be implemented with the accuracy of the acquisition of data records of valid residence in accordance with the design of data structures. ER - TY - JOUR T1 - Toward web-based Careflow Management Systems A1 - Miller, K A1 - Maccaull, W Y1 - 2009/// KW - Healthcare KW - Interoperability KW - Ontology KW - Verification KW - Web-based systems JF - Journal of Emerging Technologies in Web Intelligence VL - 1 IS - 2 SP - 137 EP - 145 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954025496&doi=10.4304%2Fjetwi.1.2.137-145&partnerID=40&md5=b7e9282cd4c4907da3267d6a55e98201 N1 - Cited By :14 Export Date: 10 September 2018 References: Clarke, L., Chen, Y., Avrunin, G., Chen, B., Cobleigh, R., Frederick, K., Henneman, E., Osterweil, L., (2005) Process Programming to Support Medical Safety: A Case Study on Blood Transfusion, , Amherst, MA; http://logic.stfx.ca, Antigonish, NS Last accessed Mar. 2009; Marcos, M., Roomans, H., Ten Teije, A., Van Harmelen, F., Improving medical protocols through formalisation: A case study (2002) Proceedings of the Sixth World Conference on Integrate Design and Process Technology; (1999) Technical Report (WFMC-TC-1011) v3.0, , Workflow Management Coalition Terminology and Glossary, Workflow Management Coalition, Winchester, UK; http://www.infowayinforoute.ca/lang-en, Last accessed March, 2009; (2008) Advancing Canada's Next Generation of Health Care, , 2015: Canada Health Infoway Report; Chandrasekaran, B., Josephson, R., Benjamins, V.R., What are ontologies, and why do we need them? (1999) IEEE Intelligent Systems, 14 (1), pp. 20-26; http://www.hc-sc.gc.ca/hcssss/ehealth-esante/index-eng.php, Last accessed Jul. 2009; http://www.health2con.com/, Last accessed Jul. 2009; Eysenbach, G., Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness, , http://www.jmir.org/2008/3/e22/, Last accessed Jul. 2009; http://obofoundry.org/wiki/index.php/OBOFoundry-Principles, OBO Foundry Principles, Last accessed Jul. 2009; The Protege Ontology Editor and Knowledge Acquisition System, , http://protege.stanford.edu, Last accessed December 2008; Ferris, F.D., Balfour, H.M., Bowen, K., Farley, J., Hardwick, M., Lamontagne, C., Lundy, M., West, P.J., (2002) A Model to Guide Hospice Palliative Care: Based on National Principles and Norms of Practice, , Canadian Hospice Palliative Care Association, Ottawa, ON; Clarke Jr., E.M., Grumberg, O., Peled, D.A., (1999) Model Checking, , MIT Press, Cambridge, Massachusetts; Huth, M.R.A., Ryan, M.D., (2000) Logic in Computer Science: Modelling and Reasoning About Systems, , Cambridge University Press, Cambridge, England; Miller, K., MacCaull, W., Verification of careflow management systems with timed BDICTL logic 3d International Workshop on Process-oriented Information Systems in Healthcare (ProHealth 09); Jensen, K., Coloured petri nets: A high level language for system design and analysis (1989) Applications and Theory of Petri Nets, pp. 342-416; Miller, K., (2009) Timed BDIC T L Verification of Ontology Driven Workflow in a Shared Memory Environment, , Master's Thesis. Saint Francis Xavier University. expected; Wang, H., MacCaull, W., Distributed-memory Verification of Real-time Systems Using Explicit-time Description Methods. Submitted to the 38th International Conference on Parallel Processing (ICPP-2009); Clarke, E.M., The birth of model checking (2008) 25 Years of Model Checking: History, Achievements, Perspectives, pp. 1-26. , Springer-Verlag, Berlin, Heidelberg; Van Der Aalst, W.M.P., The application of Petri nets to workflow management (1998) Journal of Circuits, Systems and Computers, 8 (1), pp. 21-66; OpenClinical: Knowledge Management for Medical Care, , http://www.openclinical.org/gmmsummaries.html, Last accessed March, 2009; Terenziani, P., Carlini, C., Montani, S., Towards a comprehensive treatment of temporal constraints in clinical guidelines (2002) Proc. Ninth International Symposium on Temporal Representation and Reasoning (Time-02), , IEEE Computer Society Press, Manchester; Giordano, L., Terenziani, P., Bottrighi, A., Montani, S., Donzella, L., (2006) Model Checking for Clinical Guidelines: An Agent-based Approach. AMIA 2006, , accepted for publication, Washington; Panzarasa, S., Madde, S., Quaglini, S., Pistarini, C., Stefanelli, M., Evidence-based careflow management systems: The case of post-stroke rehabilitation (2002) Journal of Biomedical Informatics, 35 (2), pp. 123-139. , DOI 10.1016/S1532-0464(02)00505-1, PII S1532046402005051; Christov, S., Chen, B., Avrunin, G.S., Clarke, L.A., Osterweil, L.J., Brown, D., Cassells, L., Mertens, W., Rigorously defining and analyzing medical processes: An experience report. MoDELS 2007 workshops (2008) LNCS, 5002, pp. 118-131. , Springer-Verlag, Berlin, Heidelberg; Dallien, J., MacCaull, W., Tien, A., Initial work in the design and development of verifiable workflow management systems and some applications to health care (2008) 3rd Workshop on Agents Applied in Health Care, 5th International Workshop on Model-based Methodologies for Pervasive and Embedded Software, pp. 78-91. , MOMPES; Imam, F., (2008) An Inconsistency Tolerant Approach to Ontology Merging, , Master's Thesis. Saint Francis Xavier University; Jewers, H., Foshay, N., MacCaull, W., Norgrove, J., Miller, K., Involving palliative care team members in designing information technology for assessment, communication, and information management for patient-centered palliative care (2008) International Symposium on the Terminally Ill; Stefanelli, M., (2002) Careflow Management Systems, , OpenClinical Briefing Paper; A Real ROI from Twitter? The Start of Social Medical Networks, , http://blogs.zdnet.com/BTL/?p=18618, Last accessed Jul. 2009; Van Der Aalst, W.M.P., Hofstede, T.A.H.M., Workflow patterns: On the expressive power of (petrinet-based) workflow languages (2002) Proceedings of the Fourth Workshop on the Practical use of Coloured Petri Nets and CPN Tools (CPN 2002), pp. 1-20. , Jensen, K. ed; Van Der Aalst, W.M.P., Hofstede, A., (2002) YAWL: Yet Another Workflow Language. QUT Technical Report, , FIT-TR-2002-06, Queensland University of Technology, Brisbane RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Health care systems are prime examples of ultra large scale systems involving complex, distributive processes with a high degree of variability. There are ubiquitous communication and massive data and knowledge management requirements including documentation and reporting. Health care systems are also critical systems, where errors can be very costly in terms of lives, quality of life, and/or dollars. The efficient use of limited resources is not only desirable but necessary. Designing these processes and managing their performance is difficult and error prone. We discuss a web-based Careflow Management System, currently under development, that takes advantage of emerging web technology and extends existing workflow management systems with formal verification features applying high performance computing methods to support real-time monitoring and adaptation. Healthcare ontologies are integrated into the system to allow advanced reasoning and to ensure accurate and relevant knowledge sharing among the various collaborators enhancing interoperability between specialized systems devoted to each area. © 2009 ACADEMY PUBLISHER. ER - TY - JOUR T1 - An openEHR based approach to improve the semantic interoperability of clinical data registry A1 - Min, L A1 - Tian, Q A1 - Lu, X A1 - An, J A1 - Duan, H Y1 - 2018/// KW - Archetypes KW - Clinical data registry KW - Semantic interoperability KW - openEHR JF - BMC Medical Informatics and Decision Making VL - 18 CY - College of Biomedical Engineering and Instrument Science, Zhejiang University, Zheda Road, Hanghzou, China DO - 10.1186/s12911-018-0596-8 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044221285&doi=10.1186%2Fs12911-018-0596-8&partnerID=40&md5=4f88adb54d77857892b2b700b1b47720 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Min et al. - 2018 - An openEHR based approach to improve the semantic interoperability of clinical data registry.pdf N1 - Export Date: 5 April 2018 N2 - Background: Clinical data registry is designed to collect and manage information about the practices and outcomes of a patient population for improving the quality and safety of care and facilitating novel researches. Semantic interoperability is a challenge when integrating the data from more than one clinical data registry. The openEHR approach can represent the information and knowledge semantics by multi-level modeling, and it advocates the use of collaborative modeling to facilitate reusing existing archetypes with consistent semantics so as to be a potential solution to improve the semantic interoperability. Methods: This paper proposed an openEHR based approach to improve the semantic interoperability of clinical data registry. The approach consists of five steps: clinical data registry meta-information collection, data element definition, archetype modeling, template editing, and implementation. Through collaborative modeling and maximum reusing of existing archetype at the archetype modeling step, the approach can improve semantic interoperability. To verify the feasibility of the approach, this paper conducted a case study of building a Coronary Computed Tomography Angiography (CCTA) registry that can interoperate with an existing Electronic Health Record (EHR) system. Results: The CCTA registry includes 183 data elements, which involves 20 archetypes. A total number of 45 CCTA data elements and EHR data elements have semantic overlap. Among them, 38 (84%) CCTA data elements can be found in the 10 reused EHR archetypes. These corresponding clinical data can be collected from the EHR system directly without transformation. The other 7 (16%) CCTA data elements correspond to one coarse-grained EHR data elements, and these clinical data can be collected with mapping rules. The results show that the approach can improve semantic interoperability of clinical data registry. Conclusions: Using an openEHR based approach to develop clinical data registry can improve the semantic interoperability. Meanwhile, some challenges for broader semantic interoperability are identified, including domain experts' involvement, archetype sharing and reusing, and archetype semantic mapping. Collaborative modeling, easy-to-use tools, and semantic relationship establishment are potential solutions for these challenges. This study provides some experience and insight about clinical modeling and clinical data registry development. © 2018 The Author(s). ER - TY - JOUR T1 - Public Health Surveillance Meets Translational Informatics: A Desiderata A1 - Mirhaji, P Y1 - 2009/// KW - Biotechnology KW - Engineering research KW - Epidemiology KW - Health KW - Information services KW - Information systems KW - Information theory KW - Information use KW - Knowledge engineering KW - Quality assurance KW - Semantics KW - article KW - biological warfare KW - biosurveillance KW - disease surveillance KW - early diagnosis KW - health education KW - health status KW - human KW - human computer interaction KW - information dissemination KW - information processing KW - medical informatics KW - morbidity KW - mortality KW - public health KW - public health information systems KW - public health preparedness KW - public health surveillance KW - semantic integration of heterogeneous information KW - semantic systems KW - signal processing KW - situation awareness KW - syndromic surveillance KW - translational Informatics JF - Journal of Laboratory Automation VL - 14 IS - 3 SP - 157 EP - 170 DO - 10.1016/j.jala.2009.02.007 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-65449153306&doi=10.1016%2Fj.jala.2009.02.007&partnerID=40&md5=3c657cc56173bde86b0318dc91e884d3 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Mirhaji - 2009 - Public Health Surveillance Meets Translational Informatics A Desiderata(2).pdf N1 - Cited By :7 Export Date: 5 April 2018 N2 - “Public health surveillance (PHS) is the ongoing and systematic collection, analysis, interpretation, and dissemination of data regarding a health-related event for use in public health action to reduce morbidity and mortality and to improve health.” As information technology gains acceptance as a core element of public health practice, many approaches to the design of PHS systems have been proposed, much has been spent implementing them, and expectations have been high. Unfortunately, the systems implemented so far have been criticized as having not met expectations, especially in the domain of early detection and bioterrorism readiness, or so-called syndromic surveillance (The term “syndromic surveillance” applies to monitoring health-related data that precede diagnosis to signal a sufficient probability of a case or an outbreak that warrants public health response.). There are no fully established frameworks to enable seamless interoperability, information sharing, and collaboration among PHS stakeholders and the technological and infrastructural requirements to fulfill the grand vision of initiatives such as the Public Health Information Network and National Health Information Network are poorly investigated and documented. In this article, we examine the current state of the conceptualization, design, analysis, and implementation of PHS systems from a translational informatics perspective. Although most examples in this article are informed by the needs of public health preparedness (syndromic and bioterrorism detection and response), we believe the framework we introduce is generalizable and applicable to the broader context of PHS systems. We also apply concepts from cognitive science and knowledge engineering to suggest directions for improvement and further research. © 2009, Society for Laboratory Automation and Screening. All rights reserved. ER - TY - CONF T1 - Informatics Critical to Public Health Surveillance A1 - Mirhaji, P A1 - Zhang, J A1 - Smith, J W A1 - Madjid, M A1 - Casscells, S W A1 - Lillibridge, S R Y1 - 2003/// KW - Biosecurity KW - Bioterrorism (BT) KW - Costs KW - Data reduction KW - Disease Outbreaks KW - Diseases KW - Epidemiology KW - Health care KW - Informatics KW - Interoperability KW - Large scale systems KW - Program diagnostics KW - Public Health Information Systems KW - Public Health Surveillance KW - Semantic Integration of Heterogeneous Information KW - Semantic Visualization KW - Syndromic Surveillance VL - 5071 SP - 151 EP - 163 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-1642434191&doi=10.1117%2F12.500842&partnerID=40&md5=a376171eed1bc0590d3adf4152999194 N1 - Cited By :2 Export Date: 10 September 2018 References: Updated guidelines for evaluating public health surveillance systems (2001) Recommendations from the Guidelines Working Group, , Centers for Disease Control and Prevention; Sosin, D.M., (2002) Draft Framework for Evaluating Syndromic Surveillance Systems for Bioterrorism Preparedness, , Center for Disease Control and Prevention; Mandl, K.D., (2002) Infrastructure and Methods to Support Real Time Biosurveillance, , BOSTON: Harvard Medical School; Mostashari, F., Syndromic Surveillance in New York City (2002) National Syndromic Surveillance Conference, , New York City; Lombardo, J., Pavlin, J., Burkom, H., Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II) (2002) National Syndromic Surveillance Conference; Integrating Public Health Information and Surveillance Systems (1995) A Report and Recommendations, , Center for Disease Control and Prevention, Agency for Toxic Substances and Disease Registration; Sujansky, W., Heterogeneous Database Integration in Biomedicine (2001) Journal of Biomedical Informatics, 34, pp. 285-298; Sujansky, W., (1994) Toward a Standard Query Model for Sharing Decision-support Applications, , American Medical Informatics Association, Fall; (2001) NEDSS Logical Data Model (NLDM)- Overview and Users' Guide, , Center for Disease Control and Prevention; Berners-Lee, T., Semantic Web (2000) The World Wide Web Consortium (W3C) Conference on Semantic Web - XML2000, , http://www.w3.org/2000/Talks/1206-xm12k-tbl; Baeza-Yates, R., Ribeiro-Neto, B., Text and Multimedia Languages and Properties (1999) Modern Information Retrieval, p. 142. , ACM press, Adison Wesley; Fensel, D., Harmelen, F.V., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., OIL: An Ontology Infrastructure for the Semantic Web (2001) IEEE Intelligent Systems, 16 (2), pp. 38-45; Fensel, D., Horrocks, I., Harmelen, F.V., Decker, S., Erdmann, M., Klein, M., OIL in a nutshell (2000) Lecture Notes in Artificial Intelligence, , 12th European Workshop on Knowledge Acquisition, Modeling, and Management (EKAW'00). Springer-Verlag; Geroimenko, V., The XML Revolution and the Semantic Web (2003) Visualizing the Semantic Web, , Vladimir Geroimenko CC, ed. XML-based internet and information visualization: Springer; Vdovjak, R., Eindhoven, G.-J.H., RDF Based Architecture for Semantic Integration of Heterogeneous Information Sources (2001) Workshop on Information Integration on the Web, , Eindhoven University of Technology; Graham, J.V., Buckeridge, D.L., Pincus, Z., Choy, M.K., O'Connor, M.J., Musen, M.A., A Knowledge-Based Approach to Defining Syndromes (2002) National Syndromic Surveillance Conference, , Stanford Medical Informatics, Stanford University, Stanford, CA; Tarr, M.J., Visual Pattern Recognition (2000) Encyclopedia of Psychology, , Washigton DC; Helminski, K., Harvey, A., The Rumi Collection (2000) An Anthology of Translations of Mevlana Jalaluddin Rumi, , Shambhala Publications; Euit, C., Sabou, M., Harmelen, F.V., Ontology based information visualization (2003) Visualizing the Semantic Web, , Vladimir Geroimenko CC, ed.: Springer Verlag; Boyack, K., Wylie, B., Davidson, G., Information Visualization, Human-Computer Interaction, and Cognitive Psychology (2001) Domain Visualizations, , Sandia National Laboratories; Chen, C., Visualization of Knowledge Structures (2002) Handbook of Software Engineering and Knowledge Engineering, , Department of Information Systems and Computing, Brunel University, UK; Silvescu, A., Reinoso-Castillo, J., Honavar, V., (2002) Ontology-driven Information Extraction and Knowledge Acquisition from Heterogeneous, Distributed, Autonomous Biological Data Sources, , Artificial Intelligence Research Laboratory, Iowa State University; Zhang, J., Silvescu, A., Honavar, V., Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction (2002) Lecture Notes in Artificial Intelligence, 2371. , Symposium on Abstraction, Reformulation, and Approximation. Springer-Verlag; Wang, C., Leong, T.-Y., Knowledge-Based Formulation of Dynamic Decision Models (1998) Pacific Rim International Conference on Artificial Intelligence; (2002) Public Health Information Technology Functions and Specifications(for Emergency Preparedness and Bioterrorism), , Center for Disease Control and Prevention, February 8; (2000) Model Emergency Response Communications Plan for Infectious Disease Outbreaks and Bioterrorist Events, , Association of State and Territorial Directors of Health Promotion and Public Health Education; Loonsk, J.W., (2002) Data Transfer and Transformation, National Syndromic Surveillance Conference, , New York City. Center for Disease Control and Prevention; Gradle, B., Report on Patient Privacy (2001) Consent for Uses, Disclosures for Treatment, Payment, Operations, , Washington DC: office of the law firm of Epstein Becker & Green., October; (1996) Report on H.R. 3103, , Health Insurance Portability and Accountability Act. Section 1173(d)(2); Hutwagner, L., Seeman, M., Thompson, W., TreadWell, T., Early Aberration Reporting System (CDC-EARS) (2002) National Syndromic Surveillance Conference, , New York. Center for Disease Control and Prevention; Moore, A., Cooper, G., Tsui, R., Wagner, M., (2001) Summary of Biosurveillance-relevant Technologies, , Carnegie Mellon University:School of Computer Science, University of Pittsburgh:Center for Biomedical Informatics; MacDonald, S.C., What's wrong with evaluating "syndromic surveillance"? (2002) National Syndromic Surveillance Conference, , New York City. Washington State Dept. of HealthOffice of Epidemiology; Smith, J.E., Winkler, R.L., Fryback, D.G., The First Positive: Computing Positive Predictive Value at the Extremes (2000) Annals of Internal Medicine, 132, pp. 804-809; Efron, B., Tibshirani, R., (1993) An Introduction to the Bootstrap, , Chapman and Hall; Walenstein, A., Cognitive support in software engineering tools: A distributed cognition framework (2000) Computing Science, , SIMON FRASER UNIVERSITY; Wright, P., Fields, B., Harrison, M., (1999) Analysing Human-computer Interaction as Distributed Cognition: The Resources Model, , University of York Heslington; Zhang, J., Patel, V.L., Johnson, K.A., Malin, J., Smith, J.W., Designing Human-Centered Distributed Information Systems (2002) IEEE Intelligent Systems, 15 (5), pp. 42-47; Studer, R., Benjamins, V.R., Fensel, D., Knowledge Engineering: Principles and Methods (1998) Data and Knowledge Engineering, 25, pp. 161-197 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public health surveillance is the ongoing, systematic collection, analysis, interpretation, and dissemination of data regarding a health-related event for use in public health action to reduce morbidity and mortality and to improve health1 by effective response management and coordination. As new pressures for early detection of disease outbreaks have arisen, particularly for outbreaks of possible bioterrorism (BT) origin, and as electronic health data have become increasingly available, so has the demand for public health situation awareness systems Although these systems are valuable for early warning of public health emergencies, there remains the cost of developing and managing such large and complex systems and of investigating inevitable false alarms. Whether these systems are dependable and cost effective enough and can demonstrate a significant and indispensable role in detection or prevention of mass casualty events of BT origin remains to be proven. This article will focus on the complexities of design, analysis, implementation and evaluation of public health surveillance and situation awareness systems and, in some cases, will discuss the key technologies being studied in Center for Biosecurity Informatics Research at University of Texas, Health Science Center at Houston. ER - TY - JOUR T1 - Describing the Breakbone Fever: IDODEN, an Ontology for Dengue Fever A1 - Mitraka, E A1 - Topalis, P A1 - Dritsou, V A1 - Dialynas, E A1 - Louis, C Y1 - 2015/// KW - Animals KW - Article KW - Biological Ontologies KW - Culicidae KW - Databases, Factual KW - Dengue KW - Fever KW - Humans KW - Q Fever KW - Software KW - animal KW - biological ontology KW - clinical trial (topic) KW - data base KW - dengue KW - dengue vaccine KW - disease course KW - disease ontology KW - drug information KW - epidemiological data KW - factual database KW - human KW - medical information system KW - medical terminology KW - messenger RNA KW - software KW - transmission JF - PLoS Neglected Tropical Diseases VL - 9 IS - 2 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84924064459&doi=10.1371%2Fjournal.pntd.0003479&partnerID=40&md5=9e428725276f0e58b5f1cefbfec22ec5 N1 - Cited By :3 Export Date: 10 September 2018 References: Dengue Hemorrhagic Fever: Diagnosis, Treatment, Prevention and Control (2009) A joint publication of the World Health Organization (WHO) and the Special Programme for Research and Training in Tropical Diseases (TDR); http://whqlibdoc.who.int/publications/2009/9789241547871_eng.pdf, World Health Organization, 2009. Dengue Guidelines for Diagnosis, Treatment, Prevention and Control. Accessed August 28, 2014; Eisen, L., Lozano-Fuentes, S., Use of mapping and spatial and space-time modeling approaches in operational control of Aedes aegypti and dengue (2009) PLoS Negl Trop Dis, 3, p. 411; Fisher, F.P., Myers, B.A., Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia (2011) Int J Health Geogr, 10, p. 15; Duncombe, J., Clements, A., Hu, W., Weinstein, P., Ritchie, S., Espino, F.E., Geographical Information Systems for Dengue Surveillance (2012) Am J Trop Med Hyg, 86, pp. 753-755; Chansang, C., Kittayapong, P., Application of Mosquito Sampling Count and Geospatial Methods to Improve Dengue Vector Surveillance Am J Trop Med Hyg, 77, pp. 897-902; Kittayapong, P., Yoksan, S., Chansang, U., Chansang, C., Bhumiratana, A., Suppression of Dengue Transmission by Application of Integrated Vector Control Strategies at Sero-Positive GIS-Based Foci (2008) Am J Trop Med Hyg, 78, pp. 70-76; Eisen, L., Coleman, M., Lozano-Fuentes, S., McEachen, N., Orlans, M., Coleman, M., Multi-disease data management system platform for vector-borne diseases (2011) PLoS Negl Trop Dis, 5, p. 1016; Stevens, R., Aranguren, M.E., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, Using OWL to model biological knowledge (2007) Int. J. Human-Computer Studies, 65, pp. 583-594; Lin, Y., Sakamoto, N., Ontology Driven Modeling for the Knowledge of Genetic Susceptibility to Disease (2009) Kobe J Med Sci, 55, pp. 53-66; Gene ontology: tool for the unification of biology (2000) Nat Genet, 25, pp. 25-29; Creating the gene ontology resource: design and implementation (2001) Genome Res, 11, pp. 1425-1433; Lewis, S., Ashburner, M., Reese, M.G., Annotating eukaryote genomes (2000) Curr Opin Struct Biol, 10, pp. 349-354; Beissbarth, T., Interpreting experimental results using gene ontologies (2006) Methods Enzymol, 411, pp. 340-352; Thomas, P.D., Mi, H., Lewis, S., Ontology annotation: mapping genomic regions to biological function (2007) Curr Opin Chem Biol, 11, pp. 4-11; Bodenreider, O., Biomedical ontologies in action: role in knowledge management, data integration and decision support (2008) Yearb Med Inform, 2008, pp. 67-79; Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration (2007) Nat Biotechnol, 25, pp. 1251-1255; Whetzel, P.L., Noy, N.F., Shah, N.H., Alexander, P.R., Nyulas, C., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications (2011) Nucleic Acids Res, 39, pp. 541-545; Dahdul, W.M., Balhoff, J.P., Blackburn, D.C., Diehl, A.D., Haendel, M.A., A unified anatomy ontology of the vertebrate skeletal system (2012) PLoS One, 7, p. 51070; Lin, Y., Xiang, Z., He, Y., Brucellosis Ontology (IDOBRU) as an extension of the Infectious Disease Ontology (2011) J Biomed Semant, 2, p. 9; Degtyarenko, K., de Matos, P., Ennis, M., Hastings, J., Zbinden, M., ChEBI: a database and ontology for chemical entities of biological interest (2008) Nucleic Acids Res, 36, pp. 344-350; Schulz, S., Jansen, L., Formal ontologies in biomedical knowledge representation (2013) Yearb Med Inform, 8, pp. 132-146; Schulz, S., Balkanyi, L., Cornet, R., Bodenreider, O., From Concept Representations to Ontologies: A Paradigm Shift in Health Informatics? (2013) Health Inform Res, 19, pp. 235-242; Megy, K., Emrich, S., Lawson, D., Dialynas, E., Koscielny, G., VectorBase: improvements to a bioinformatics resource for invertebrate vector genomics (2012) Nucl. Acids Res, 40, pp. 715-719; Topalis, P., Dialynas, E., Mitraka, E., Deligianni, E., Siden-Kiamos, I., Louis, C., A set of ontologies to drive tools for the control of vector-borne diseases (2011) J Biomed Inform, 44, pp. 42-47; Topalis, P., Tzavlaki, C., Vestaki, K., Dialynas, E., Sonenshine, D.E., Anatomical ontologies of mosquitoes and ticks, and their web browsers in VectorBase (2008) Insect Mol. Biol, 17, pp. 87-89; Dialynas, E., Topalis, P., Vontas, J., Louis, C., MIRO and IRbase: IT tools for the epidemiological monitoring of insecticide resistance in mosquito disease vectors (2009) PLoS Negl Trop Dis, 3, p. 465; Topalis, P., Mitraka, E., Bujila, I., Deliyanni, E., Dialynas, E., (2010) IDOMAL: An ontology for malaria Malaria J, 9, p. 230; http://oboformat.googlecode.com/svn/branches/2011–11–29/doc/obo-syntax.html, Mungall C, Ruttenberg A, Horrocks I, Osumi-Sutherland, D. (2011) The OBO Flat File Format Guide, version 1.4. Accessed August 28, 2014; http://www.w3.org/TR/owl-features/, McGuinness, DL, van Harmelen F (2004) OWL Web Ontology Language, W3C Recommendation. Accessed August 28, 2014; Dritsou, V., Mitraka, E., Topalis, P., Louis, C., (2012) Getting the best from two worlds: Converting between OBO and OWL formats; Knublauch, H., Fergerson, R.W., Noy, N.F., Musen, M.A., McIlraith, S.A., Plexousakis, D., v Harmelen, F., The Protégé OWL Plugin: An Open Development Environment for Semantic Web Applications (2004) The Semantic Web ISWC, pp. 229-243; Goldfain, A.G., Smith, B., Cowell, L.G., Galton, A., Mizoguchi, R., Dispositions and the Infectious Disease Ontology (2010) Formal Ontology in Information Systems. Proceedings of the Sixth International Conference (FOIS 2010), pp. 400-413; Topalis, P., Mitraka, E., Dritsou, V., Dialynas, E., Louis, C., IDOMAL: The malaria ontology revisited (2013) J. Biomed. Semant, 4, p. 16; Simon, J., Dos Santos, M., Fielding, J., Smith, B., Formal ontology for natural language processing and the integration of biomedical databases (2006) Int J Med Inform, 75, pp. 224-231; Grenon, P., Smith, B., Goldberg, L., Biodynamic ontology: applying BFO in the biomedical domain (2004) Stud Health Technol Inform, 102, pp. 20-38; http://purl.obolibrary.org/obo/bfo/2012-07-20/Reference, Basic Formal Ontology 2.0. Draft specification and users’. Accessed August 28, 2014; Courtot, M., Gibson, F., Lister, A., Malone, J., Schober, D., MIREOT: the Minimum Information to Reference an External Ontology Term (2009) The 1st International Conference on Biomedical Ontology (ICBO); Buttigieg, P.L., Morrison, N., Smith, B., Mungall, C.J., Lewis, S.E., The environment ontology: contextualising biological and biomedical entities (2013) J Biomed Semant, 4, p. 43; Normile, D., Surprising New Dengue Virus Throws a Spanner in Disease Control Efforts (2013) Science, 342, p. 415; Smith, B., Ceusters, W., Klagges, B., Kohler, J., Kumar, A., Relations in Biomedical Ontologies (2005) Genome Biol, 6, p. 46; Breteau, H., La fièvre jaune en Afrique-Occidentale Française; un aspect de la médecine préventive massive (1954) Bull World Health Organ, 11, pp. 453-481; Röhl, J., Jansen, L., (2014) J Biomed Semant, 25, p. 27; Malone, J., Holloway, E., Adamusiak, T., Kapushesky, M., Zheng, J., Modeling Sample Variables with an Experimental Factor Ontology (2010) Bioinformatics, 26, pp. 1112-1118; Yauch, L.E., Shresta, S., Dengue virus vaccine development (2014) Adv Virus Res, 88, pp. 315-372; Thisyakorn, U., Thisyakorn, C., Latest developments and future directions in dengue vaccines (2014) Ther Adv Vaccines, 2, pp. 3-9; Topalis, P., Lawson, D., Collins, F.H., Louis, C., How can ontologies help vector biology? (2008) Trends Parasitol, 24, pp. 249-252; Sanchez-Vargaz, I., Travanty, E.A., Keene, K.M., Fran, A.W., Beaty, B.J., RNA interference, arthropod-borne viruses, and mosquitoes (2004) Virus. Res, 102, pp. 65-74; Kakumani, P.K., Ponia, S.S., S, R.K., Sood, V., Chinnappan, M., Role of RNA interference (RNAi) in dengue virus replication and identification of NS4B as an RNAi suppressor (2013) J Virol, 87, pp. 8870-8883; Lee, T.C., Lin, Y.L., Liao, J.T., Su, C.M., Lin, C.C., Utilizing liver-specific microRNA-122 to modulate replication of dengue virus replicon (2010) Biochem Biophys Res Commun, 396, pp. 596-601; Xie, P.W., Xie, Y., Zhang, X.J., Huang, H., He, L.N., Inhibition of Dengue virus 2 replication by artificial micrornas targeting the conserved regions (2013) Nucleic Acid Ther, 23, pp. 244-252; Rodenhuis-Zybert, I.A., Wilschut, J., Smit, J.M., Dengue virus life cycle: viral and host factors modulation infectivity (2010) Cell Mol Life Sci, 67, pp. 2773-2786; Whitehom, J., Farrar, J., (2010) Dengue Br Med Bull, 95, pp. 161-173; Halstead, S.B., Nimmannitya, S., Cohen, S.N., Observations related to pathogenesis of dengue hemorrhagic fever. IV. Relation of disease severity to antibody response and virus recovered (1970) Yale Jour Biol Med, 42, pp. 311-328; Halstead, S.B., Antibody, macrophages, dengue virus infection, shock, and hemorrhage: a pathogenetic cascade (1989) Rev Inf Dis, 11, pp. 830-839; Theiler, M., Casals, J., Moutousses, C., Etiology of the 1927–28 epidemic of dengue in Greece (1960) Proc Soc Exp Biol Med, 103, pp. 244-246; Papaevangelou, G., Halstead, S.B., Infections with two dengue viruses in Greece in the 20th century. Did dengue hemorrhagic fever occur in the 1928 epidemic? (1977) J Trop Med Hyg, 80, pp. 46-51; Halstead, S.B., Papaevangelou, G., Transmission of dengue 1 and 2 viruses in Greece in 1928 (1980) Am J Trop Med Hyg, 29, pp. 635-637; Chastel, C., Lessons from the Greek dengue epidemic of 1927–1928 (2009) Bull Acad Natl Med, 93, pp. 485-493; Louis, C., Daily newspaper view of dengue fever epidemic, Athens, Greece, 1927–1931 (2012) Emerg Infect Dis, 18, pp. 78-82; Norrby, R., Outlook for a dengue vaccine (2014) Clin Microbiol Infect Clin Microbiol Infect Suppl, 5, pp. 92-94; Lozano-Fuentes, S., Bandyopadhyay, A., Cowell, L.G., Goldfain, A., Eisen, L., Ontology for vector surveillance and management (2013) J Med Entomol, 50, pp. 1-14 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Ontologies represent powerful tools in information technology because they enhance interoperability and facilitate, among other things, the construction of optimized search engines. To address the need to expand the toolbox available for the control and prevention of vector-borne diseases we embarked on the construction of specific ontologies. We present here IDODEN, an ontology that describes dengue fever, one of the globally most important diseases that are transmitted by mosquitoes. We constructed IDODEN using open source software, and modeled it on IDOMAL, the malaria ontology developed previously. IDODEN covers all aspects of dengue fever, such as disease biology, epidemiology and clinical features. Moreover, it covers all facets of dengue entomology. IDODEN, which is freely available, can now be used for the annotation of dengue-related data and, in addition to its use for modeling, it can be utilized for the construction of other dedicated IT tools such as decision support systems. The availability of the dengue ontology will enable databases hosting dengue-associated data and decision-support systems for that disease to perform most efficiently and to link their own data to those stored in other independent repositories, in an architecture- and software-independent manner. © 2015 Mitraka et al. ER - TY - CHAP T1 - The Roadmap for Sharing Electronic Health Records: The Emerging Ubiquity and Cloud Computing Trends A1 - Mohammed, Sabah A1 - Fiaidhi, Jinan Y1 - 2010/12// KW - Clinical workflow KW - Cloud computing KW - Computer systems KW - Computerized information systems KW - Computerized medical records KW - Degree of penetration KW - Disease surveillance KW - Electronic document exchange KW - Electronic health record KW - Electronic medical record system KW - Health KW - Health care KW - Health care professionals KW - Health information systems KW - Health-care system KW - Information systems KW - Local system KW - Medical computing KW - Medical information systems KW - Medical papers KW - Modern technologies KW - Paperless KW - Records management KW - Retail industry KW - Roadmap KW - Systems analysis KW - Technology KW - Ubiquitous computing KW - Vision based KW - Web technologies PB - Springer, Berlin, Heidelberg VL - 6485 LNCS SP - 27 EP - 38 DO - 10.1007/978-3-642-17569-5_4 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651096378&doi=10.1007%2F978-3-642-17569-5_4&partnerID=40&md5=2faa3de7cd754f3a7290482c41ab17bb UR - http://link.springer.com/10.1007/978-3-642-17569-5_4 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Mohammed, Fiaidhi - 2010 - The Roadmap for Sharing Electronic Health Records The Emerging Ubiquity and Cloud Computing Trends.pdf N1 - From Duplicate 1 (The roadmap for sharing electronic health records: The emerging ubiquity and cloud computing trends - Mohammed, S; Fiaidhi, J) Export Date: 5 April 2018 N2 - Medical paper-based records have been in existence for decades and their gradual replacement by computer-based records has been slowly underway for over twenty years in healthcare systems. Computerized information systems have not achieved the same degree of penetration in healthcare as that seen in other sectors such as finance, transport and the manufacturing and retail industries. Further, deployment has varied greatly from country to country and from specialty to specialty and in many cases has revolved around local systems designed for local use. Electronic medical record systems lie at the center of any computerized health information system. Without them other modern technologies such as disease surveillance systems cannot be effectively integrated into routine clinical workflow. The paperless, interoperable, multi-provider, multi-specialty, multi-discipline computerized medical record, which has been a goal for many researchers, healthcare professionals, administrators and politicians for the past two decades, is however about to become reality in many countries. This article provides a roadmap vision based on the emerging web technologies that hold great promise for addressing the challenge of sharing electronic health records. It starts with addressing the ubiquity trend and how it can be realized based on the new cloud computing paradigm to share electronic heath records like the community of care records/documents (CCRs, CCDs). The article also addresses the security concerns related to sharing electronic health records over the cloud. ER - TY - JOUR T1 - The development and deployment of Common Data Elements for tissue banks for translational research in cancer - An emerging standard based approach for the Mesothelioma Virtual Tissue Bank A1 - Mohanty, S K A1 - Mistry, A T A1 - Amin, W A1 - Parwani, A V A1 - Pople, A K A1 - Schmandt, L A1 - Winters, S B A1 - Milliken, E A1 - Kim, P A1 - Whelan, N B A1 - Farhat, G A1 - Melamed, J A1 - Taioli, E A1 - Dhir, R A1 - Pass, H I A1 - Becich, M J Y1 - 2008/// KW - Biological Markers KW - Computational Biology KW - Databases as Topic KW - Genome KW - Humans KW - Medical Informatics Applications KW - Mesothelioma KW - Pleural Neoplasms KW - Software KW - Systems Integration KW - Tissue Banks KW - article KW - biology KW - cancer registry KW - cancer research KW - cancer tissue KW - computer program KW - data analysis software KW - data base KW - demography KW - epidemiological data KW - health care facility KW - human KW - information processing KW - information retrieval KW - information storage KW - medical informatics KW - medical information KW - medical information system KW - medical society KW - mesothelioma KW - pleura tumor KW - system analysis JF - BMC Cancer VL - 8 N1 - Cited By :26 Export Date: 10 September 2018 References: The National Biospecimen Network (NBN) Blueprint, , http://biospecimens.cancer.gov/biospecimen/network/index.asp; Becich, M.J., The role of the pathologist as tissue refiner and data miner: The impact of functional genomics on the modern pathology laboratory and the critical roles of pathology informatics and bioinformatics (2000) Mol Diagn, 5 (4), p. 287. , 10.1054/modi.2000.20431 11172493; Eiseman, E., (2003) Case Studies of Existing Human Tissue Repositories: "Best Practices" for a Biospecimen Resource for the Genomic and Proteomic Era, , Rand Corporation Santa Monica, CA: RAND; Tobias, J., Chilukuri, R., Komatsoulis, G.A., Mohanty, S.K., Sioutos, N., Warzel, D.B., Wright, L.W., Crowley, R.S., The CAP cancer protocols - A case study of caCORE based data standards implementation to integrate with the Cancer Biomedical Informatics Grid (2006) BMC Med Inform Decis Mak, 6, p. 25. , Jun 20; 10.1186/1472-6947-6-25; Winget, M.D., Baron, J.A., Spitz, M.R., Brenner, D.E., Warzel, D., Kincaid, H., Thornquist, M., Feng, Z., Development of common data elements: The experience of and recommendations from the early detection research network (2003) Int J Med Inform, 70, pp. 41-48. , 10.1016/S1386-5056(03)00005-4 12706181; The Cooperative Breast Cancer Tissue Resource, , http://www-cbctr.ims.nci.nih.gov/; Glass, A.G., Donis-Keller, H., Mies, C., Russo, J., Zehnbauer, B., Taube, S., Aamodt, R., The Cooperative Breast Cancer Tissue Resource: Archival tissue for the investigation of tumor markers (2001) Clin Cancer Res, 7, pp. 1843-1849. , 11448894; Patel, A.A., Kajdacsy-Balla, A., Berman, J.J., Bosland, M., Datta, M.W., Dhir, R., Gilbertson, J., Becich, M.J., The development of common data elements for a multi-institute prostate cancer tissue bank: The Cooperative Prostate Cancer Tissue Resource (CPCTR) experience (2005) BMC Cancer, 5, p. 108. , Aug 21; 10.1186/1471-2407-5-108; Gilbertson, J.R., Gupta, R., Nie, Y., Patel, A.A., Becich, M.J., Automated clinical annotation of tissue bank specimens (2004) Medinfo, 11 (PART 1), p. 607. , 15360884; Patel, A.A., Gilbertson, J.R., Parwani, A.V., Dhir, R., Datta, M.W., Gupta, R., Berman, J.J., Becich, M.J., An informatics model for tissue banks - Lessons learned from the Cooperative Prostate Cancer Tissue Resource (2006) BMC Cancer, 6, p. 120. , Cooperative Prostate Cancer Tissue Resource May 5; 10.1186/ 1471-2407-6-120; Melamed, J., Datta, M.W., Becich, M.J., Orenstein, J.M., Dhir, R., Silver, S., Fidelia-Lambert, M., Berman, J.J., The cooperative prostate cancer tissue resource: A specimen and data resource for cancer researchers (2004) Clin Cancer Res, 10 (14), p. 4614. , 10.1158/1078-0432.CCR-04-0240 Jul 15; 10.1158/1078-0432.CCR-04-0240; The Cancer Biomedical Informatics Grid (caBIG), , https://cabig.nci.nih.gov/; Patel, A.A., Gilbertson, J.R., Showe, L.C., London, J.W., Ross, E., Ochs, M.F., Carver, J., Becich, M.J., A Novel Cross-Disciplinary Multi-institutional Approach to Translational Cancer research: Lessons learned from Pennsylvania Cancer alliance Bioinformatics Consortium (PCABC) (2007) Cancer Informatics, , PCABC; http://www.cdc.gov/search.do?action=search&queryText=NIOSH, The National Institute for Occupational Safety and Health (NIOSH); http://www.mesotissue.org, Mesothelioma Virtual Tissue Bank (MVB); The NCICB's Cancer Data Standards Repository (caDSR), , http://ncicb.nci.nih.gov/core/caDSR; 45 CFR (Code of Federal Regulations), 164.514(6) (2) (i). Standards for Privacy of Individually Identifiable Health Information (Final), , http://www.hhs.gov/ocr/regtext.html, Department of Health and Human Services; Dhir, R., Grzybicki, D., Bisceglia, M., Winters, S., Aamodt, R., Swanson, D., Becich, M.J., A multi-disciplinary approach to honest broker services for tissue banks and clinical data: A pragmatic and practical model (Manuscript under preparation) (2007); http://chtn.nci.nih.gov/, The NCI's Cooperative Human Tissue Network (CHTN); The NCI's Early Detection Research Network Website (EDRN), , http://edrn.nci.nih.gov/; http://www.cfr.epi.uci.edu/, The NCI's Cancer Family Registries (CFR); http://spores.nci.nih.gov/, The NCI's Specialized Programs of Research Excellence (SPOREs); North American Association of Central Cancer Registry Data Standards for Cancer Registries, , http://www.naaccr.org/index.asp?Col_SectionKey=7&Col_ContentID=122; The College of American Pathologists Cancer Protocols, , http://www.cap.org/apps/docs/cancer_protocols/protocols_index.htm; Association of Directors of Anatomic and Surgical Pathology Recommendations for the Reporting of Pleural Mesothelioma (2007) Am J Clin Pathol, 127, pp. 15-19. , 10.1309/6A30YQHBMTHEJTEM 17145632; Fleming, I.D., American Joint Committee on Cancer, American Cancer Society, American College of Surgeons (2002) AJCC Cancer Staging Manual, , Philadelphia: Lippincott-Raven 6; UPMC Network Cancer Registry, , http://www.upci.upmc.edu/Internet/research/boic/ris.html; The CAP Cancer Protocols: Checklist for Mesothelioma, , http://www.cap.org/apps/docs/cancer_protocols/2005/thoracicmeso05_pw.pdf; Garte, S., Boffetta, P., Caporaso, N., Vineis, P., Metabolic gene allelic nomenclature (2001) Cancer Epidemiol Biomarkers Prev, 10, pp. 1305-1306. , 11751451; Unified Modeling Language, , http://www.uml.org; Enterprise Architect, , http://www.sparxsystems.com.au/ea.htm; XML Metadata Interchange (XMI), , http://www.omg.org/technology/documents/formal/xmi.htm; The ISO/IEC 11179 Specification Developed By the National Institute of Standards and Technology (NIST), , http://isotc.iso.ch/livelink/livelink/fetch/2000/2489/Ittf_Home/PubliclyAvailableStandards.htm; The Clinical Annotation Engine, , https://cabig.nci.nih.gov/inventory/cae; http://www.cbmi.pitt.edu/, The Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PAUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-42549156562&doi=10.1186%2f1471-2407-8-91&partnerID=40&md5=2dd12fdc885838281498f41d67f96a75 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: Recent advances in genomics, proteomics, and the increasing demands for biomarker validation studies have catalyzed changes in the landscape of cancer research, fueling the development of tissue banks for translational research. A result of this transformation is the need for sufficient quantities of clinically annotated and well-characterized biospecimens to support the growing needs of the cancer research community. Clinical annotation allows samples to be better matched to the research question at hand and ensures that experimental results are better understood and can be verified. To facilitate and standardize such annotation in bio-repositories, we have combined three accepted and complementary sets of data standards: the College of American Pathologists (CAP) Cancer Checklists, the protocols recommended by the Association of Directors of Anatomic and Surgical Pathology (ADASP) for pathology data, and the North American Association of Central Cancer Registry (NAACCR) elements for epidemiology, therapy and follow-up data. Combining these approaches creates a set of International Standards Organization (ISO) - compliant Common Data Elements (CDEs) for the mesothelioma tissue banking initiative supported by the National Institute for Occupational Safety and Health (NIOSH) of the Center for Disease Control and Prevention (CDC). Methods: The purpose of the project is to develop a core set of data elements for annotating mesothelioma specimens, following standards established by the CAP checklist, ADASP cancer protocols, and the NAACCR elements. We have associated these elements with modeling architecture to enhance both syntactic and semantic interoperability. The system has a Java-based multi-tiered architecture based on Unified Modeling Language (UML). Results: Common Data Elements were developed using controlled vocabulary, ontology and semantic modeling methodology. The CDEs for each case are of different types: demographic, epidemiologic data, clinical history, pathology data including block level annotation, and follow-up data including treatment, recurrence and vital status. The end result of such an effort would eventually provide an increased sample set to the researchers, and makes the system interoperable between institutions. Conclusion: The CAP, ADASP and the NAACCR elements represent widely established data elements that are utilized in many cancer centers. Herein, we have shown these representations can be combined and formalized to create a core set of annotations for banked mesothelioma specimens. Because these data elements are collected as part of the normal workflow of a medical center, data sets developed on the basis of these elements can be easily implemented and maintained. © 2008 Mohanty et al; licensee BioMed Central Ltd. ER - TY - BOOK T1 - International journal of environmental research and public health. A1 - Molecular Diversity Preservation International., Luciana A1 - Marins, Fernando A1 - Portela, Filipe A1 - Santos, Manuel A1 - Abelha, António A1 - Machado, José Y1 - 2004/// PB - Molecular Diversity Preservation International JF - International Journal of Environmental Research and Public Health VL - 11 IS - 5 SP - 5349 EP - 5371 UR - https://www.academia.edu/14341588/The_Next_Generation_of_Interoperability_Agents_in_Healthcare N2 - Title from journal's home page (viewed Jan. 28, 2005). ER - TY - BOOK T1 - Semantic Multi Agent Architecture for Chronic Disease Monitoring and Management A1 - Nachabe, L A1 - El Hassan, B A1 - Taleb, J Y1 - 2019/// JF - Lecture Notes on Data Engineering and Communications Technologies VL - 29 SP - 284 EP - 294 DO - 10.1007/978-3-030-12839-5_26 N2 - ©2019, Springer Nature Switzerland AG. Population all over the world is experiencing an epidemic of chronic disease (such as diabetes, heart disease, etc.) which is considered as the leading cause of morbidity and mortality. These diseases are complex and require the intervention and interaction between different stakeholders (doctors, nurses, experts, dietitians). Moreover, patient self-monitoring and management can contribute in the diagnosis and treatment. With the evolution of medical sensors and m-health applications, vital signs monitoring is becoming easier. However, a new approach for chronic disease health care monitoring and management is needed in order to insure intelligence decision making, interoperability between existing systems, and interaction across stakeholders, as well as early diagnosis and self-monitoring. In this paper, we present a semantic multi agent architecture based on predefined ontology and using JADE framework. This architecture encompasses two main agents: contractor and manager in order to offer the adequate data to the requested parties (doctors/patients). ER - TY - JOUR T1 - Avoiding interoperability and delay in healthcare monitoring system using block chain technology A1 - Narayana, V L A1 - Gopi, A P A1 - Chaitanya, K Y1 - 2019/// JF - Revue d'Intelligence Artificielle VL - 33 IS - 1 SP - 45 EP - 48 DO - 10.18280/ria.330108 N2 - ©2019 Lavoisier. All rights reserved. Blockchain is using in every aspect now because of its distributed ledger which is immutable. It provides the information to the users directly without any third party involvement. It mediates the transactions directly between the interacting parties securely. It also eliminates the friction and also the cost of current intermediaries. It is now using in healthcare system to provide the interoperability, security, decentralization and other. EMR is presently using in healthcare which has some issues. The issues in healthcare are patient cannot access the data of his/her own health information. So by this healthcare has issues like interoperability and delay in communication and some other. These issues can be solved by using the Blockchain in healthcare. By this Blockchain provide security by giving the patients to access their own data rather than provider. ER - TY - JOUR T1 - OpenPVSignal: Advancing information search, sharing and reuse on pharmacovigilance signals via fair principles and Semantic Web Technologies A1 - Natsiavas, P A1 - Boyce, R D A1 - Jaulent, M.-C. A1 - Koutkias, V Y1 - 2018/// KW - Adverse drug reactions KW - Article KW - Drug safety KW - FAIR principles KW - Internet KW - Knowledge engineering KW - Linked data KW - Netherlands KW - Ontologies KW - Periodicals as Topic KW - Pharmacovigilance signals KW - Semantic web KW - Semantics KW - United States KW - World Health KW - access to information KW - automation KW - computer model KW - conceptual framework KW - data processing KW - drug information KW - drug safety KW - drug surveillance program KW - food and drug administration KW - information dissemination KW - knowledge KW - machine KW - medical technology KW - ontology KW - publication KW - semantic web KW - signal detection KW - standardization KW - world health organization JF - Frontiers in Pharmacology VL - 9 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049095117&doi=10.3389%2Ffphar.2018.00609&partnerID=40&md5=d62939483afe8ba1aaab603a566aa334 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Natsiavas et al. - 2018 - OpenPVSignal Advancing information search, sharing and reuse on pharmacovigilance signals via fair principles.pdf N1 - Export Date: 10 September 2018 References: (2011) National Safety and Quality Health Service Standards, , https://www.safetyandquality.gov.au/wp-content/uploads/2011/01/NSQHS-Standards-Sept2011.pdf, Sydney, NSW (Accessed May 24 2017); Baader, F., Horrocks, I., Sattler, U., Description Logics (2004) Handbook on Ontologies, pp. 3-28. , eds S. Staab and R. Studer (Berlin; Heidelberg: Springer); Berners-Lee, T., Hendler, J., Lassila, O., The semantic web: a new form of web content that is meaningful to computers will unleash a revolution of new possibilities (2001) Sci. Am, 284, pp. 29-37; Biryukov, M., Groues, V., Satagopam, V., Schneider, R., BioKB-Text mining and semantic technologies for the biomedical content discovery (2017) Proceedings of the 10th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences (SWAT4LS 2017), , http://www.swat4ls.org/wp-content/uploads/2017/11/SWAT4LS-2017_paper_5.pdf, eds A. Paschke, A. Burger, A. Splendiani, M. S. Marshall, P. Romano, and V. Presutti (Rome: CEUR Workshop Proceedings (CEUR-WS.org)). (Accessed January 23, 2018); Bizer, C., The emerging web of linked data (2009) IEEE Intell. Syst, 24, pp. 87-92; Bousquet, C., Sadou, É., Souvignet, J., Jaulent, M.-C., Declerck, G., Formalizing MedDRA to support semantic reasoning on adverse drug reaction terms (2014) J. Biomed. Inform, 49, pp. 282-291; Boyce, R.D., Ryan, P.B., Norén, G.N., Schuemie, M.J., Reich, C., Duke, J., (2014) Drug Saf, 37, pp. 557-567; Callahan, A., Cruz-Toledo, J., Ansell, P., Dumontier, M., (2013) Bio2RDF Release 2, Improved Coverage, Interoperability And Provenance Of Life Science Linked Data, pp. 200-212. , (Berlin; Heidelberg: Springer); (2013) (Es)omeprazole and Tinnitus Case, LAREB, , https://databankws.lareb.nl/Downloads/KWB_2013_3_(Es)omeprazole_and_tinnitus.pdf, ADR Signal Report (Accessed July 18 2017); Clark, T., Ciccarese, P.N., Goble, C.A., Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications (2014) J. Biomed. Semantics, 5, p. 28; (2010) Practical Aspects of Signal Detection in Pharmacovigilance, Council for International Organizations of Medical Sciences, , https://cioms.ch/shop/product/practical-aspects-of-signal-detection-in-pharmacovigilance-report-of-cioms-working-group-viii/, Report of CIOMS. Working Group VIII. CIOMS, Geneva; Courtot, M., Brinkman, R.R., Ruttenberg, A., The logic of surveillance guidelines: an analysis of vaccine adverse event reports from an ontological perspective (2014) PLoS ONE, 9; Cox, S., Little, C., Hobbs, J., Pan, F., (2017) Time Ontology in OWL, , https://www.w3.org/TR/owl-time/; Large-scale adverse effects related to treatment evidence standardization (LAERTES): an open scalable system for linking pharmacovigilance evidence sources with clinical data (2017) J. Biomed. Semantics, 8, p. 11; (2011) Drug Safety and Availability-FDA Drug Safety Communication: Low Magnesium Levels can be Associated with Long-Term Use of Proton Pump Inhibitor Drugs (PPIs), , https://www.fda.gov/Drugs/DrugSafety/ucm245011.htm, Center for Drug Evaluation and Research (Accessed January 4 2018); Gaignard, A., Skaf-Molli, H., Bihouée, A., From scientific workflow patterns to 5-star linked open data (2016) 8th USENIX Workshop on the Theory and Practice of Provenance (TaPP 16), , https://www.usenix.org/conference/tapp16/workshop-program/presentation/gaignard, (Washington, DC: USENIX Association) (Accessed January 15 2018); Gil, Y., Miles, S., Belhajjame, K., Deus, H., Garijo, D., Klyne, G., (2013) W3C PROV Model Primer, , https://www.w3.org/TR/prov-primer/, (Accessed July 12 2017); Hassanzadeh, O., Zhu, Q., Freimuth, R., Boyce, R., Extending the "web of drug identity" with knowledge extracted from United States product labels (2013) AMIA Jt. Summits Transl. Sci, 2013, pp. 64-68; He, Y., Sarntivijai, S., Lin, Y., Xiang, Z., Guo, A., Zhang, S., OAE: the ontology of Adverse Events (2014) J. Biomed. Semantics, 5, p. 29; Heath, T., Bizer, C., Linked Data: evolving the web into a global data space (2011) Synth. Lect. Semant. Web Theory Technol, 1, pp. 1-136; Himmelstein, D.S., Lizee, A., Hessler, C., Brueggeman, L., Chen, S.L., Hadley, D., Systematic integration of biomedical knowledge prioritizes drugs for repurposing (2017) Elife, 6; Hu, Y., Bajorath, J., Learning from "big data": compounds and targets (2014) Drug Discov. Today, 19, pp. 357-360; Jiang, G., Duke, J.D., Pathak, J., Chute, C.G., An ontological representation of adverse drug events (2011) 2nd International Conference on Biomedical Ontology, , http://icbo.buffalo.edu/2011/workshop/adverse-events/docs/papers/GuoquianAEICBO2011_submission.pdf, ICBO 2011 (Buffalo, NY, United States) (Accessed July 17 2017); Jiang, G., Liu, H., Solbrig, H.R., Chute, C.G., ADEpedia 2.0: integration of normalized adverse drug events (ADEs) knowledge from the UMLS (2013) AMIA Jt. Summits Transl. Sci, 2013, pp. 100-104; Koutkias, V.G., Jaulent, M.-C., Computational approaches for pharmacovigilance signal detection: toward integrated and semantically-enriched frameworks (2015) Drug Saf, 38, pp. 219-232; Koutkias, V.G., Lillo-Le Louët, A., Jaulent, M.-C., Exploiting heterogeneous publicly available data sources for drug safety surveillance: computational framework and case studies (2017) Expert Opin. Drug Saf, 16, pp. 113-124; Kuhn, M., Letunic, I., Jensen, L.J., Bork, P., The SIDER database of drugs and side effects (2016) Nucleic Acids Res, 44, pp. D1075-D1079; Law, V., Knox, C., Djoumbou, Y., Jewison, T., Guo, A.C., Liu, Y., DrugBank 4.0: shedding new light on drug metabolism (2014) Nucleic Acids Res, 42, pp. D1091-D1097; Musen, M.A., The Protégé project: a look back and a look forward (2015) AI Matters, 1, pp. 4-12; Nasulewicz, A., Zimowska, W., Bayle, D., Dzimira, S., Madej, J., Rayssiguier, Y., Changes in gene expression in the lungs of Mg-deficient mice are related to an inflammatory process (2004) Magnes. Res, 17, pp. 259-263; Natsiavas, P., Maglaveras, N., Koutkias, V., "Evaluation of linked, open data sources for mining adverse drug reaction signals" (2017) Lecture Notes in Computer Science, , (Cham: Springer); Noy, N., Facilitating the Discovery of Public Datasets (2017) Google Res. Blogpost, , https://research.googleblog.com/2017/01/facilitating-discovery-of-public.html?m=1, (Accessed January 29 2018); Pal, S., Tanaka, D., (2017) Ibrutinib and Pneumonitis, WHO Pharmaceuticals Newsletter, , http://www.who.int/medicines/publications/PharmaNewsletter3_17/en/, World Health Organization (Accessed November 14 2017); Samwald, M., Jentzsch, A., Bouton, C., Kallesøe, C.S., Willighagen, E., Hajagos, J., Linked open drug data for pharmaceutical research and development (2011) J. Cheminform, 3, p. 19; Sanderson, R., Ciccarese, P., Young, B., (2017) Web Annotation Data Model, , http://www.w3.org/TR/annotation-model/, (Accessed September 8 2015); Shadbolt, N., Berners-Lee, T., Hall, W., The semantic web revisited (2006) IEEE Intell. Syst, 21, pp. 96-101; Souvignet, J., Declerck, G., Asfari, H., Jaulent, M.-C., Bousquet, C., OntoADR a semantic resource describing adverse drug reactions to support searching, coding, and information retrieval (2016) J. Biomed. Inform, 63, pp. 100-107; Stevens, R., Sattler, U., (2013) Post-Coordination: Making Things Up as You Go Along, , http://ontogenesis.knowledgeblog.org/1305, (Accessed December 9 2017); Suárez-Figueroa, M.C., Gómez-Pérez, A., Fernández-López, M., The NeOn methodology for ontology engineering (2012) Ontology Engineering in a Networked World, pp. 9-34. , eds M. C. Suárez-Figueroa, A. Gómez-Pérez, E. Motta, and A. Gangemi (Berlin; Heidelberg: Springer); Sultana, J., Cutroneo, P., Trifirò, G., Clinical and economic burden of adverse drug reactions (2013) J. Pharmacol. Pharmacother, 4, pp. S73-S77; Voss, E.A., Boyce, R.D., Ryan, P.B., van der Lei, J., Rijnbeek, P.R., Schuemie, M.J., Accuracy of an automated knowledge base for identifying drug adverse reactions (2017) J. Biomed. Inform, 66, pp. 72-81; Weaver, J., Tarjan, P., Facebook Linked data via the graph, API (2013) Semant. Web, 4, pp. 245-250; Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J.J., Appleton, G., Axton, M., Baak, A., The FAIR guiding principles for scientific data management and stewardship (2016) Sci. Data, 3; (2002) The Importance of Pharmacovigilance, , http://apps.who.int/medicinedocs/en/d/Js4893e/, World Health Organization (Accessed May 24 2017); Zaman, S., Sarntivijai, S., Abernethy, D., Use of biomedical ontologies for integration of biological knowledge for learning and prediction of adverse drug reactions (2017) Gene Regul. Syst. Bio, 11 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Signal detection and management is a key activity in pharmacovigilance (PV). When a new PV signal is identified, the respective information is publicly communicated in the form of periodic newsletters or reports by organizations that monitor and investigate PV-related information (such as the World Health Organization and national PV centers). However, this type of communication does not allow for systematic access, discovery and explicit data interlinking and, therefore, does not facilitate automated data sharing and reuse. In this paper, we present OpenPVSignal, a novel ontology aiming to support the semantic enrichment and rigorous communication of PV signal information in a systematic way, focusing on two key aspects: (a) publishing signal information according to the FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles, and (b) exploiting automatic reasoning capabilities upon the interlinked PV signal report data. OpenPVSignal is developed as a reusable, extendable and machine-understandable model based on Semantic Web standards/recommendations. In particular, it can be used to model PV signal report data focusing on: (a) heterogeneous data interlinking, (b) semantic and syntactic interoperability, (c) provenance tracking and (d) knowledge expressiveness. OpenPVSignal is built upon widely-accepted semantic models, namely, the provenance ontology (PROV-O), the Micropublications semantic model, the Web Annotation Data Model (WADM), the Ontology of Adverse Events (OAE) and the Time ontology. To this end, we describe the design of OpenPVSignal and demonstrate its applicability as well as the reasoning capabilities enabled by its use. We also provide an evaluation of the model against the FAIR data principles. The applicability of OpenPVSignal is demonstrated by using PV signal information published in: (a) the World Health Organization's Pharmaceuticals Newsletter, (b) the Netherlands Pharmacovigilance Centre Lareb Web site and (c) the U.S. Food and Drug Administration (FDA) Drug Safety Communications, also available on the FDA Web site. © 2018 Natsiavas, Boyce, Jaulent and Koutkias. ER - TY - CONF T1 - E-health interoperability landscape: Botswana A1 - Ndlovu, K A1 - Mogotlhwane, T A1 - Scott, R E A1 - Mars, M Y1 - 2016/// KW - Botswana KW - Developing Countries KW - Electronic health record KW - Interoperability KW - Mobile telemedicine KW - eHealth JF - Proceedings of the 4th IASTED International Conference on Health Informatics, AfricaHI 2016 SP - 202 EP - 207 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015404891&doi=10.2316%2FP.2016.837-010&partnerID=40&md5=1050491dbc60fa50cce3cecba51d83dd N1 - Export Date: 5 April 2017 Export Date: 10 September 2018 References: (2014) A Shared Nationwide Interoperability Roadmap, , Connecting Health and Care for the Nation, National Coordinator for Health Information Technology; MHealth: New Horizons for Mobile Health Through Mobile Technologies: Second Global Survey on E-health, , http://www.who.int/goe/publications/goe_mhealth_web.pdf, World Health Organization, accessed August 2016; Oliver, A., The veterans health administration: An American success story? (2007) Milbank Q, 85 (1), pp. 5-35. , Mar; https://ehr.meditech.com/ehr-solutions, Meditech-EHR Solutions, accessed July 2016; Zambrano, R., Novero-Belec, M., (2010) Report on the Global Meeting on Government Interoperability Frameworks, , 4-6 May 2010, Rio de Janeiro, Brazil; (2015) EHealth Strategy Document, Final Draft, , eHealth Cluster, Ministry of Health, Botswana; Littman-Quinn, R., Chandra, A., Schwartz, A., MHealth applications for telemedicine and public health intervention in Botswana (2011) Proceedings of the IST Africa Conference, pp. 1-11. , 11-13 May, Gaborone, Botswana; Thomson, R., Sordo, M., (2002) Introduction to Neural Networks in Healthcare, , http://www.openclinical.org/interoperability.html, OpenClinical: Knowledge Management for Medical Care, Harvard, accessed June 2016; (2005), http://www.himss.org/sites/himssorg/files/HIMSSorg/Content/files/AUXILIOHIMSSInteroperabilityDefined.pdf, HIMSS-Interoperability Definition and Background, accessed: April 2016; (2013) EU Activities in the Field of EHealth Interoperability and Standardisation: An Overview, , file:///C:/Users/Richard/Downloads/OverviewEUinteroperabilityactivitieseHealth.pdf, European Commission, accessed August 2016; (2012) EHealth Interoperability Framework v1.1, , Australian Digital Health Agency. April; (2013), file:///C:/Users/Richard/Downloads/2013-09-23-EvaluatingHITStandards-FINAL.pdf, HIMSS Health Information Standards Work Group Evaluating HIT Standards, July, accessed August 2016; (2014) Version 2.0, , National Health Normative Standards Framework for Interoperability in eHealth in South Africa, March, CSIR GWDMS Number: 24007; Iroju, O., Soriyan, A., Gambo, I., Olaleke, J., Interoperability in healthcare: Benefits, challenges and resolutions (2013) International Journal of Innovation and Applied Studies, 3 (1), pp. 262-270; (2016) Refined EHealth European Interoperability Framework, , http://ec.europa.eu/health/ehealth/docs/ev_20151123_co03_en.pdf, eHealth Network, accessed August RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: EHR N2 - Healthcare system interoperability remains a major challenge for most upcoming economies. In Botswana, just like most developing countries, the health information landscape is marred by discrete islands of information posing significant barriers to the effective sharing of information between healthcare participants. This becomes even more challenging when trying to understand and accurately report on what is really happening, to support population health surveillance, and to guide policy, service planning, innovation, and clinical and operational decision-making. There is a clear need to move away from the reliance on manual data collection to an environment where healthcare stakeholders can reliably and securely access and share health information in real time across geographic and health sector boundaries. Information and Communication Technologies (ICTs) for health (i.e. eHealth) have the ability to dramatically increase access to, and availability of life-enriching information and services. The Government of Botswana fully understands and appreciates the developmental importance of ICTs. Accordingly, the Botswana Ministry of Health is leveraging ICTs to attain a single health record for every Motswana which will enable the planning, management, and delivery of timely health services. Botswana has been experiencing an influx of well-intentioned health information system implementations in various health facilities which duplicated functionalities and were not interoperable, leading to fragmentation and potential misinformation. This has led to health systems interoperability being a major component of Botswana's eHealth strategy. This paper therefore seeks to outline global and local endeavours towards the attainment of interoperable eHealth solutions and suggest a possible eHealth interoperability framework direction for developing economies such as in Botswana. ER - TY - JOUR T1 - A case study in open source innovation: Developing the Tidepool Platform for interoperability in type 1 diabetes management A1 - Neinstein, A A1 - Wong, J A1 - Look, H A1 - Arbiter, B A1 - Quirk, K A1 - McCanne, S A1 - Sun, Y A1 - Blum, M A1 - Adi, S Y1 - 2016/// KW - Article KW - Blood glucose self-monitoring KW - Computerassisted KW - Decision making KW - Diabetes Mellitus, Type 1 KW - Diabetes mellitus type 1 KW - Humans KW - Insulin infusion systems KW - Mobile applications KW - Ownership KW - Software KW - Systems Integration KW - agile software development KW - agnostic cloud platform device KW - blip app KW - cloud computing KW - computer aided design KW - computer input device KW - computer program KW - computer security KW - data base KW - ecosystem KW - human KW - insulin dependent diabetes mellitus KW - javascript KW - methodology KW - modern web design KW - organization and management KW - rest api KW - small modular pieces KW - software KW - system analysis KW - tidepool platform KW - user centered design JF - Journal of the American Medical Informatics Association VL - 23 IS - 2 SP - 324 EP - 332 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Neinstein et al. - 2016 - A case study in open source innovation Developing the Tidepool Platform for interoperability in type 1 diabete.pdf N1 - Cited By :7 Export Date: 10 September 2018 References: (2014), Centers for Disease Control and Prevention; 2014 GA, Atlanta; Adi, S., Type 1 diabetes mellitus in adolescents (2010) Adolesc Med State Art Rev., 21 (1), pp. 86-102; Walsh, J.P., Wroblewski, D., Bailey, T.S., Insulin pump settings: a major source for insulin dose errors (2007), http://www.diabetesnet.com/pdfs/DiabTech2007Poster.pdf, Diabetes Technology Meeting [October 25; Meade, L.T., Rushton, W.E., Optimizing insulin pump therapy a quality improvement project (2013) Diabetes Educ., 39 (6), pp. 841-847; Klonoff, D.C., Blonde, L., Cembrowski, G., Consensus report: the current role of self-monitoring of blood glucose in non-insulin-treated type 2 diabetes (2011) J Diabetes Sci Technol, 5 (6), pp. 1529-1548; Pickup, J.C., Sutton, A.J., Severe hypoglycaemia and glycaemic control in Type 1 diabetes: meta-analysis of multiple daily insulin injections compared with continuous subcutaneous insulin infusion (2008) Diabet Med, 25 (7), pp. 765-774; Yeh, H.-C., Brown, T.T., Maruthur, N., Comparative effectiveness and safety of methods of insulin delivery and glucose monitoring for diabetes mellitus: a systematic review and meta-analysis (2012) Ann Intern Med, 157 (5), pp. 336-347; Control, D., Complications Trial Research, Group, The effect of intensive treatment of diabetes on the development and progression of longterm complications in insulin-dependent diabetes mellitus (1993) N Engl J Med, 329 (14), pp. 977-986; Training in flexible, intensive insulin management to enable dietary freedom in people with type 1 diabetes: dose adjustment for normal eating (DAFNE) randomised controlled trial (2002) BMJ, 325 (7367), p. 746; Beck, R.W., Tamborlane, W.V., Bergenstal, R.M., The T1D Exchange clinic registry (2012) J Clin Endocrinol Metab, 97 (12), pp. 4383-4389; Corriveau, E.A., Durso, P.J., Kaufman, E.D., Skipper, B.J., Laskaratos, L.A., Heintzman, K.B., Effect of Carelink, an internet-based insulin pump monitoring system, on glycemic control in rural and urban children with type 1 diabetes mellitus (2008) Pediatric Diabetes, 9 (4), pp. 360-366; Wong, J.C., Foster, N.C., Maahs, D.M., Real-time continuous glucose monitoring among participants in the T1D Exchange clinic registry (2014) Diabetes Care, 37 (10), pp. 2702-2709; Lawton, J., Rankin, D., Cooke, D., Patients' experiences of adjusting insulin doses when implementing flexible intensive insulin therapy: a longitudinal, qualitative investigation (2012) Diabetes Res Clin Pract, 98 (2), pp. 236-242; Picton, P.E., Yeung, M., Hamming, N., Desborough, L., Dassau, E., Cafazzo, J.A., Advancement of the Artificial Pancreas through the Development of Interoperability Standards (2013) J Diabetes Sci Technol, 7 (4), pp. 1066-1070; FDA Approval for Animas Vibe Insulin Pump with Dexcom G4 PLATINUM CGM (2014), http://www.medgadget.com/2014/12/fda-approval-for-animas-vibe-insulin-pump-with-dexcom-g4-platinumcgm-video.html, [cited April 15, 2015]; (2014) FDA Approval for Animas Vibe Insulin Pump with Dexcom G4 PLATINUM CGM, , MedGadget Editors, MedGadget, ed; (2013) Tandem Diabetes Care and Dexcom Expand Development and Commercialization Agreement to Include Recently Approved G4TM PLATINUM CGM Sensor, , Newswire P, ed; (2015), http://www.diasend.com/us/, Diasend, cited March 5; (2015), http://www.glooko.com, Glooko, cited March 5; (2015), http://www.sweetspotdiabetes.com, cited March 5; Announces Acquisition of SweetSpot Diabetes Care, Inc (2012), http://www.businesswire.com/news/home/20120223006633/en/DexCom-Announces-Acquisition-SweetSpot-Diabetes-Care-VS6EcpTF_rI, cited April 15, 2015; Rao, L., Glooko Raises $3.5M To Connect Glucose Meters To iPhones For Tracking Diabetes (2012), http://techcrunch.com/2012/01/30/glooko-raises-3-5m-to-connect-glucose-meters-to-iphonesfor-tracking-diabetes/, cited April 15, 2015; Baum, S., (2015) Glooko adds Medtronic as investor in $16.5M Series B, , News M, ed; Bergenstal, R.M., Ahmann, A.J., Bailey, T., Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP) (2013) Diabetes Technol Therapeutics, 15 (3), pp. 198-211; Health informatics-Personal health device communication - Part 20601: Application profile- Optimized Exchange Protocol, , IEEE; Health informatics-Personal health device communication - Part 10425: Device Specialization-Continuous Glucose Monitor (CGM), , standardsieeeorg. in press; Demidowich, A.P., Lu, K., Tamler, R., Bloomgarden, Z., An evaluation of diabetes self-management applications for Android smartphones (2012) J Telemed Telecare, 18 (4), pp. 235-238; El-Gayar, O., Timsina, P., Nawar, N., Eid, W., A systematic review of IT for diabetes self-management: are we there yet? (2013) Int J Med Inform., 82 (8), pp. 637-652; Eng, D.S., Lee, J.M., The promise and peril of mobile health applications for diabetes and endocrinology (2013) Pediatric Diabetes, 14 (4), pp. 231-238; Mulvaney, S.A., Ritterband, L.M., Bosslet, L., Mobile intervention design in diabetes: review and recommendations (2011) Curr Diab Rep, 11 (6), pp. 486-493; Dyer, J.S., Effects of consumer-facing technologies on patient engagement, behavior change, and type 2 diabetes-related health outcomes (2014) Diabetes Spectrum, 26 (2), pp. 98-101; A reality checkpoint for mobile health: three challenges to overcome (2013) PLoS Med., 10 (2), p. e1001395; Tomlinson, M., Rotheram-Borus, M.J., Swartz, L., Tsai, A.C., Scaling Up mHealth: where is the evidence? (2013) PLoS Med, 10 (2), p. e1001382; Gagne, K., Lake, M., CompuServe, Prodigy et al: what Web 2.0 can learn from Online 1.0 (2009), http://www.computerworld.com/article/2526547/networking/compuserve-prodigy-et-al-what-web-2-0-can-learn-from-online-1-0.html, Computerworldcom July 15, [cited February 3, 2015]; Leiner, B., Cerf, V., Clark, D., Brief History of the Internet. internetsocietyorg http://www.internetsociety.org/internet/what-internet/historyinternet/brief-history-internet, [cited]; http://tidepool.org/, [cited]; Estrin, D., Sim, I., Health care delivery. Open mHealth architecture: an engine for health care innovation (2010) Science, 330 (6005), pp. 759-760; Gentleman, R.C., Carey, V.J., Bates, D.M., Bioconductor: open software development for computational biology and bioinformatics (2004) Genome Biol, 5 (10), p. R80; Look, H., Tidepool License Update (2013), http://tidepool.org/2013/12/19/tidepool-license-update/, December 19, [cited March 6, 2015]; (2015), https://github.com/tidepool-org/platform-client, cited March 6; (2015), http://www.wordpress.com, cited March 5; Blank, S., (2013) Lean Launchpad for Life Sciences and Healthcare, , San Francisco, CA, September to December 2013; Weinberger, D., (2003) Small Pieces, Loosely Joined, , 1 edn. Basic Books: New York, NY; Fielding, R.T., Taylor, R.N., Principled design of the modern Web architecture (2002) ACM Transact Internet Technol (TOIT), 2 (2), pp. 115-150; (2014) Data for Individual Health: Agency for Healthcare Research and Quality, , JASON. (a committee/group), Agency for Healthcare Research and Quality, McLean, VA; (2015), http://developer.tidepool.io, cited March 6; Lawton, G., Developing software online with platform-as-a-service technology (2008) Computer, 41 (6), pp. 13-15; Rolim, C.O., Koch, F.L., Westphall, C.B., Werner, J., Fracalossi, A., Salvador, G.S., A cloud computing solution for patient's data collection in health care institutions (2010) Second International Conference on eHealth, Telemedicine, and Social Medicine, pp. 95-99. , IEEE; Armbrust, M., Fox, A., Griffith, R., A view of cloud computing (2010) Commun ACM, 53 (4), pp. 50-58; Schweitzer, E.J., Reconciliation of the cloud computing model with US federal electronic health record regulations (2011) JAMIA, 19 (2), pp. 161-165; Highsmith, J., Cockburn, A., Agile software development: the business of innovation (2001) Computer, 34 (9), pp. 120-127; McConnell, S., (1996) Chapter 7: Lifecycle Planning. O'Reilly, , Rapid Development: Taming Wild Software Schedules, Microsoft Press, Redmond, WA; van Mierlo, T., Fournier, R., Jean-Charles, A., Hovington, J., Ethier, I., Selby, P., I'll Txt U if I Have a Problem: How the SociétéCanadienne du Cancer in Quebec Applied Behavior-Change Theory, Data Mining and Agile Software Development to Help Young Adults Quit Smoking (2014) PLoS ONE, 9 (3), p. e91832; Wyatt, J.C., Liu, J.L.Y., Basic concepts in medical informatics (2002) J Epidemiol Commun Health, 56 (11), pp. 808-812; Schwaber, K., Scrum development process (1997) Business Object Design and Implementation, pp. 117-134. , Springer: New York, NY; McCurdie, T., Taneva, S., Casselman, M., mHealth consumer apps: the case for user-centered design (2012) Biomed Instrum Technol, pp. 49-56; Blank, S., Building a Company with Customer Data - Why Metrics Are Not Enough (2009), http://steveblank.com/2009/12/17/building-a-company-with-customer-data-metrics-are-not-enough/, cited April 21, 2015; (2001), csrcnistgov: Federal Information Processing Standards Publication No. 197; (2013) Security and Privacy Controls for Federal Information Systems and Organizations, , NIST Special Publication: National Institute of Standards and Technology, Gaithersburg, MD; Medical Device Interoperability (2012), p. 52. , A Safer Path Forward: AAMI-FDA Interoperability Summit; Herndon, VA; Bengtsson, M., Kock, S., "Coopetition" in business networks-to cooperate and compete simultaneously (2000) Ind Market Manage, 29 (5), pp. 411-426; Rossi, M.C.E., Nicolucci, A., Di Bartolo, P., Diabetes interactive diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: an open-label, international, multicenter, randomized study (2010) Diabet Care, 33 (1), pp. 109-115; Liang, X., Wang, Q., Yang, X., Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis (2011) Diabet Med, 28 (4), pp. 455-463; Lawson, P.J., Flocke, S.A., Teachable moments for health behavior change: a concept analysis (2009) Patient Educ Couns, 76 (1), pp. 25-30; Phillip, M., Battelino, T., Atlas, E., Nocturnal glucose control with an artificial pancreas at a diabetes camp (2013) N Engl J Med, 368 (9), pp. 824-833; Russell, S.J., El-Khatib, F.H., Sinha, M., Outpatient glycemic control with a bionic pancreas in type 1 diabetes (2014) N Engl J Med, 371 (4), pp. 313-325; Williams, A.J., Wilbanks, J., Ekins, S., Why open drug discovery needs four simple rules for licensing data and models (2012) PLoS Comput Biol., 8 (9), p. e1002706; (2014) A Trial Comparing Continuous Glucose Monitoring With and Without Routine Blood Glucose Monitoring in Adults With Type 1 Diabetes, , T1D Exchange Clinic Network Coordinating Center: Boston, MA; Barnard, K.D., Lloyd, C.E., Skinner, T.C., Systematic literature review: quality of life associated with insulin pump use in Type 1 diabetes (2007) Diabet Med, 24 (6), pp. 607-617; Mauras, N., Fox, L., Englert, K., Beck, R.W., Continuous glucose monitoring in type 1 diabetes (2013) Endocrine, 43 (1), pp. 41-50; Misso, M.L., Egberts, K.J., Page, M., O'Connor, D., Shaw, J., Continuous subcutaneous insulin infusion (CSII) versus multiple insulin injections for type 1 diabetes mellitus (2010) Cochrane Database Syst Rev, (1), p. CD005103; Phillip, M., Battelino, T., Rodriguez, H., Use of insulin pump therapy in the pediatric age-group: consensus statement from the European Society for Paediatric Endocrinology, the Lawson Wilkins Pediatric Endocrine Society, and the International Society for Pediatric and Adolescent Diabetes, endorsed by the American Diabetes Association and the European Association for the Study of Diabetes (2007) Diabet Care, 30 (6), pp. 1653-1662; Phillip, M., Danne, T., Shalitin, S., Use of continuous glucose monitoring in children and adolescents (2012) Pediatric Diabetes, 13 (3), pp. 215-228; Shalitin, S., Ben-Ari, T., Yackobovitch-Gavan, M., Using the Internetbased upload blood glucose monitoring and therapy management system in patients with type 1 diabetes (2013) Acta Diabetol, 51 (2), pp. 247-256; Baker, T.B., Gustafson, D.H., Shah, D., How can research keep up with eHealth? Ten strategies for increasing the timeliness and usefulness of eHealth research (2014) J Med Internet Res, 16 (2), p. e36; Chopra, P., The Ultimate Guide to A/B Testing (2010), http://www.smashingmagazine.com/2010/06/24/the-ultimate-guide-to-ab-testing/, cited May 29, 2014UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963734499&doi=10.1093%2fjamia%2focv104&partnerID=40&md5=e1a82dc7ecb8c334d3d746f2b5fbee9a RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. Materials and Methods An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. Results: Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. Discussion: By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. Conclusion: The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases. © The Author 2015. ER - TY - JOUR T1 - Applications and methods utilizing the Simple Semantic Web Architecture and Protocol (SSWAP) for bioinformatics resource discovery and disparate data and service integration. A1 - Nelson, Rex T A1 - Avraham, Shulamit A1 - Shoemaker, Randy C A1 - May, Gregory D A1 - Ware, Doreen A1 - Gessler, Damian Dg Y1 - 2010/// KW - Computational Biology KW - Health Resources KW - Semantics PB - BioMed Central JF - BioData mining VL - 3 IS - 1 SP - 3 EP - 3 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological databases, which makes the exchange of data between information resources difficult and labor intensive. A recently described semantic web protocol, the Simple Semantic Web Architecture and Protocol (SSWAP; pronounced "swap") offers the ability to describe data and services in a semantically meaningful way. We report how three major information resources (Gramene, SoyBase and the Legume Information System [LIS]) used SSWAP to semantically describe selected data and web services. METHODS We selected high-priority Quantitative Trait Locus (QTL), genomic mapping, trait, phenotypic, and sequence data and associated services such as BLAST for publication, data retrieval, and service invocation via semantic web services. Data and services were mapped to concepts and categories as implemented in legacy and de novo community ontologies. We used SSWAP to express these offerings in OWL Web Ontology Language (OWL), Resource Description Framework (RDF) and eXtensible Markup Language (XML) documents, which are appropriate for their semantic discovery and retrieval. We implemented SSWAP services to respond to web queries and return data. These services are registered with the SSWAP Discovery Server and are available for semantic discovery at http://sswap.info. RESULTS A total of ten services delivering QTL information from Gramene were created. From SoyBase, we created six services delivering information about soybean QTLs, and seven services delivering genetic locus information. For LIS we constructed three services, two of which allow the retrieval of DNA and RNA FASTA sequences with the third service providing nucleic acid sequence comparison capability (BLAST). CONCLUSIONS The need for semantic integration technologies has preceded available solutions. We report the feasibility of mapping high priority data from local, independent, idiosyncratic data schemas to common shared concepts as implemented in web-accessible ontologies. These mappings are then amenable for use in semantic web services. Our implementation of approximately two dozen services means that biological data at three large information resources (Gramene, SoyBase, and LIS) is available for programmatic access, semantic searching, and enhanced interaction between the separate missions of these resources. ER - TY - JOUR T1 - International harmonization of health monitoring A1 - Nicklas, W Y1 - 2012/// KW - Agents KW - Animal Shells KW - Animalia KW - Animals KW - Harmonization KW - Health reports KW - Health testing KW - Recommendations KW - Reporting KW - Rodentia KW - Sample size KW - Test methods JF - ILAR Journal VL - 53 IS - 3 SP - 338 EP - 346 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865813891&partnerID=40&md5=e210ef427a6983681640ab242bea3f62 N1 - Export Date: 5 April 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Proper health surveillance is vitally important to the evaluation of the microbial status of laboratory animals and the performance of standardized experiments with a minimum number of animals. Sufficient and reliable information about animals' health status has become even more important during the last decade with the rapid development and worldwide exchange of new genetically modified rodents. But a universal testing strategy for the assessment of pathogen status in rodent populations and internationally recognized standards and definitions of their quality do not exist, even though health data can provide consistent information only when based on systematic sampling and testing. Although there have been repeated calls for the development of international health monitoring standards and reporting, there are also objections. This article presents both the advantages and limitations of guidelines. After an overview of major factors to consider I discuss previous attempts to harmonize health monitoring procedures. The health monitoring recommendations for rodents issued by the Federation of European Laboratory Science Associations (FELASA) could serve as a model for global recommendations and for international harmonization. Given the increased significance of accurate health information when exchanging animals, research institutions and universities would benefit from universal standards, which would also help scientists as well as reviewers and readers of publications to better assess the validity of research results. ER - TY - CONF T1 - Validation of patient identification in an HL7 messages integrator for health data monitoring and portability A1 - Nogueira, A C A1 - Oliveira, R A1 - Cruz-Correia, R A1 - Vieira-Marquesa, P Y1 - 2019/// JF - Procedia Computer Science VL - 164 SP - 670 EP - 677 DO - 10.1016/j.procs.2019.12.234 N2 - ©2019 The Authors. Published by Elsevier B.V. Introduction: In the healthcare sector, data quality is a critical aspect with high impact in the clinical care process. The quality of patient identification prevents misidentifications and lack of information. Methods: In this work we used an integration engine to receive, process and route HL7 messages. By analysing these messages, we can provide the means to overcome the heterogeneity present in existing health information systems data models and architecture. The aim of this work was to create a validation solution for patient identification using HL7 messages as source. The solution accepts a patient name and returns information about their quality. Results: A total of 1.048.576 messages were gathered and processed by the solution. The performed tests identified erroneous patient names (n=40.699) and also systematic errors caused by some health information systems. It also provided a method to increase the visibility of these problems, and act accordingly to correct them. Discussion: In a production environment, the tests performed confirmed the solution's ability to identify common errors that happen across communications in a health institution network. Most common errors detected were related to the patient name field being used for other functions than those for which it was designed. ER - TY - CONF T1 - Improving nursing practice through interoperability and intelligence A1 - Oliveira, D A1 - Duarte, J A1 - Abelha, A A1 - Machado, J Y1 - 2017/// KW - Healthcare KW - Hospital Information System KW - Interoperability KW - Nursing Practice JF - Proceedings - 2017 5th International Conference on Future Internet of Things and Cloud Workshops, W-FiCloud 2017 VL - 2017-Janua SP - 194 EP - 199 CY - Deparment of Informatics, University of Minho, Braga, Portugal DO - 10.1109/FiCloudW.2017.92 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047248056&doi=10.1109%2FFiCloudW.2017.92&partnerID=40&md5=f295b7a271642cfe46029f4e7babeca0 N1 - Export Date: 14 June 2018 N2 - Hospital inpatient care compromises one of the most demanding services in health institutions when providing a careful and continuous healthcare assistance. Such demands require constant update of the patients' electronic health record allied with support systems responsible for monitoring their clinical information. In this context, this paper presents a new web platform for daily monitoring of patients, designed to be used by health professionals, especially nurses. The application is based on React, an open-source JavaScript library for building user interfaces. The developed tool incorporates two main features: the real-time visualization of the data, and the storage of the patient's historic during an inpatient care episode. The storage capability allows keeping the data updated among hospital shifts. Moreover, this work also highlights the required adaptability of this platform for each health units inside a hospital center according with its needs. © 2017 IEEE. ER - TY - JOUR T1 - HL7 ontology and mobile agents for interoperability in heterogeneous medical information systems A1 - Orgun, B A1 - Vu, J Y1 - 2006/// KW - Client server computer systems KW - Computer Communication Networks KW - Health Status KW - Health care KW - Health level seven KW - Heterogeneous medical information systems KW - Hospital data processing KW - Humans KW - Information Systems KW - Integrated Advanced Information Management Systems KW - Interoperability KW - Medical Informatics Applications KW - Medical Records Systems, Computerized KW - Medical computing KW - Mobile agents KW - Multi agent systems KW - Ontology KW - article KW - computer aided design KW - health care organization KW - health level 7 KW - human KW - medical information system KW - medical research KW - priority journal JF - Computers in Biology and Medicine VL - 36 IS - 7 SP - 817 EP - 836 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-33646842835&doi=10.1016%2Fj.compbiomed.2005.04.010&partnerID=40&md5=8ebe773f698c5099c51af2be91fc60a1 N1 - Cited By :83 Export Date: 10 September 2018 References: Grimson, W., Berry, D., Grimson, J., Stephens, G., Felton, E., Given, P., O'Moore, R., Federated healthcare record server-the synapses paradigm (1998) Int. J. Med. Inf., 52, pp. 3-27; Kashyap, V., Sheth, A., Semantics based information brokering (1994) Third International Conference on Information and Knowledge Management, pp. 363-370. , Gaithersburg, MD, USA; Silverman, B.G., Moidu, K., Clemente, B.E., Reis, L., Lang, L., Ravichander, D., Safran, C., HOLON: a web-based framework for fostering guideline applications (1997) American Medical Informatics Association Annual Fall Symposium, pp. 374-378. , Nashville, USA; Silverman, B.G., Sokolsky, O., Tannen, V., Wong, A., Lang, L., Khoury, A., Campbell, K., Sahuguet, A., HOLON/CADSE: integrating open software standards and formal methods to generate guideline-based decision support agents (1999) J. Am. Med. Inf. Assoc. (JAMIA), pp. 955-959; Lanzola, G., Falasconi, S., Stefanelli, M., Cooperative software agents for patient management (1995) Fifth Conference on Artificial Intelligence in Medicine Europe (AIME95), pp. 173-184; Lanzola, G., Falasconi, S., Stefanelli, M., Cooperating agents implementing distributed patient management (1996) Seventh European Workshop on Modelling Autonomous Agents in a Multi-Agent World, pp. 218-232; Lanzola, G., Falasconi, S., Stefanelli, M., Using ontologies in multi-agent systems (1996) 10th Knowledge Acquisition For Knowledge-Based Systems Workshop, pp. 28.1-28.20. , Banff, Canada; Ramesh, V., Canfield, K., Quirlogico, S., Silva, M., An intelligent agent-based architecture for interoperability among heterogenous medical databases (1996) The American Conference on Information Systems, pp. 549-551. , Phoenix, AZ; Karp, P., Riley, M., Paley, S., Pellegrini, A., Toole, EcoCyc: Encyclopedia of Eschercia coli genes and metabolism (1996) Nucleic Acids Res., 24, pp. 32-40; Obitko, M., Marik, V., Ontologies for multi-agent systems in manufacturing domain (2002) 13th International Workshop on Database and Expert Systems Applications, pp. 597-602. , Aix-en-Provence, France; Gangemi, A., Fisseha, F., Pettman, I., Pisanelli, D.M., Taconet, M., Keizer, J., A formal ontological framework for semantic interoperability in the fishery domain (2002) ECAI-02 Workshop on Ontologies and Semantic Interoperability, pp. 17-31. , Lyon, France; Lindberg, D., Humphreys, B., McCray, A., The Unified Medical Language System (UMLS) (1993) 1993 Yearbook of Medical Informatics, pp. 41-53. , VanBemmel J. (Ed), International Medical Informatics Association, Amsterdam; Finin, T., Labrou, Y., Mayfield, J., KQML as an agent communication language (1997) Software Agents, pp. 291-316. , Bradshaw J. (Ed), AAAI/MIT Press, Cambridge; Silverman, B.G., Andonyadis, C., Morales, A., Web-based health care agents: the case of reminders and todos, too (R2Do2) (1998) Artif. Intell. Med., 14, pp. 295-316; Cimino, J.J., Clayton, P.D., Hripcsack, G., Johnson, S.B., Knowledge-based approaches to the maintenance of a large controlled medical terminology (1994) J. Am. Med. Inf. Assoc., pp. 35-50; Rector, A.L., Solomon, W.D., Nowlan, W.A., Rush, T.W., A terminology server for medical language and medical information systems (1995) Methods Inf. Med., 34, pp. 147-157; Chaudhri, V.K., Farquhar, A., Fikes, R., Karp, P.D., Rice, J.P., OKBC: a programmatic foundation for knowledge base interoperability (1998) 15th National Conference on Artificial Intelligence, pp. 600-607. , Madison, Wisconsin; Rhodes, B.J., Maes, P., Just-in-time information retrieval agents (2000) IBM Systems J., 39, p. 685; RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Modern medical information management is a knowledge intensive activity requiring a high degree of interoperability across various health management entities. Ontology-based multi-agent systems provide a framework for interactions in a distributed medical systems environment without the limitations of a more traditional client server approach. In this paper, we describe electronic Medical Agent System (eMAGS) a multi-agent system with an ontology based on an accepted public health message standard, Health Level Seven (HL7), to facilitate the flow of patient information across a whole healthcare organisation. © 2005 Elsevier Ltd. All rights reserved. ER - TY - JOUR T1 - Electronic health record - public health (EHR-PH) system prototype for interoperability in 21st century healthcare systems. A1 - Orlova, A O A1 - Dunnagan, M A1 - Finitzo, T A1 - Higgins, M A1 - Watkins, T A1 - Tien, A A1 - Beales, S Y1 - 2005/// KW - Computer Communication Networks KW - Cooperative Behavior KW - Disease Notification KW - Feasibility Studies KW - Humans KW - Hydrogen-Ion Concentration KW - Immunization KW - Infant, Newborn KW - Information Systems KW - Medical Records Systems, Computerized KW - Neonatal Screening KW - Private Sector KW - Public Health Informatics KW - Public Sector KW - Regional Medical Programs KW - Registries KW - Systems Integration KW - article KW - computer network KW - cooperation KW - feasibility study KW - health care planning KW - human KW - immunization KW - infection control KW - information system KW - medical informatics KW - medical record KW - newborn KW - newborn screening KW - organization and management KW - register KW - standard KW - system analysis JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium SP - 575 EP - 579 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-39049176404&partnerID=40&md5=bd538864866696e86ebbf3881a1b1d35 N1 - Cited By :22 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Information exchange, enabled by computable interoperability, is the key to many of the initiatives underway including the development of Regional Health Information Exchanges, Regional Health Information Organizations, and the National Health Information Network. These initiatives must include public health as a full partner in the emerging transformation of our nation's healthcare system through the adoption and use of information technology.An electronic health record - public health (EHR-PH)system prototype was developed to demonstrate the feasibility of electronic data transfer from a health care provider, i.e. hospital or ambulatory care settings, to multiple customized public health systems which include a Newborn Metabolic Screening Registry, a Newborn Hearing Screening Registry, an Immunization Registry and a Communicable Disease Registry, using HL7 messaging standards. Our EHR-PH system prototype can be considered a distributed EHR-based RHIE/RHIO model - a principal element for a potential technical architecture for a NHIN. ER - TY - JOUR T1 - Empowering knowledge generation through international data network: The IMeCCHI-DATANETWORK A1 - Otero Varela, L A1 - Le Pogam, M.-A. A1 - Metcalfe, A A1 - Kristensen, P K A1 - Hider, P A1 - Patel, A A1 - Kim, H A1 - Carlini, E A1 - Perego, R A1 - Gini, R Y1 - 2020/// JF - International Journal of Population Data Science VL - 5 IS - 1 DO - 10.23889/ijpds.v5i1.1125 N2 - February 2020 ©The Authors. Open Access under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/deed.en) Introduction The International Methodology Consortium for Coded Health Information (IMeCCHI) is a collaboration of health services researchers who promote methodological advances in coded health information. The IMeCCHI-DATANETWORK initiative focuses on developing a multi-purpose distributed data infrastructure and common data model (CDM) to enable cross-border data sharing and international comparisons. Methods IMeCCHI consortium partners from six different countries - Canada, Denmark, Italy, New Zealand, South Korea, and Switzerland - used a questionnaire to describe their original databases which differ in size, structure, content and coding systems. To standardize these data, they agreed on a CDM and mapped their population-based databases to meet the CDM specifications. At the end of this process, local data had a more homogenous content and structure, which made them syntactically and semantically interoperable. Data transformation was performed using a common data management software called TheMatrix. Results The CDM encompasses four tables of structured data (person characteristics, hospitalizations, outpatient prescription medication and death), linked at the individual level through a person identifier. It can be used to answer research questions across countries using locally converted databases, which facilitates study replication in a distributed fashion. As a proof-of-concept study, an initial research question was addressed using an agreed protocol. Local data were transformed in csv files in the CDM structure and TheMatrix was tested to transform the standardized data from each partner into local analytical datasets. This allowed results to be shared between countries, whilst maintaining local control over each region's data. Conclusion The IMeCCHI-DATANETWORK, a model of a distributed data network, demonstrated that it is feasible to analyze international data using standardized analytical methods that enable independent analyses by regions, without relocating datasets thereby protecting local confidentiality obligations. The distributed data infrastructure can produce results that can be generalized to several countries, while facilitating cross-border data sharing and international comparisons. ER - TY - JOUR T1 - Rayyan — a web and mobile app for systematic reviews A1 - Ouzzani, Mourad A1 - Hammady, Hossam A1 - Fedorowicz, Zbys A1 - Elmagarmid, Ahmed Y1 - 2016/// JF - Systematic Reviews VL - 5 SP - 210 EP - 210 DO - 10.1186/s13643-016-0384-4 UR - https://rayyan.qcri.org ER - TY - JOUR T1 - Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics A1 - Pahl, C A1 - Zare, M A1 - Nilashi, M A1 - de Faria Borges, M A A1 - Weingaertner, D A1 - Detschew, V A1 - Supriyanto, E A1 - Ibrahim, O Y1 - 2015/// KW - Archetypes KW - Article KW - Brazil KW - Complex networks KW - Demographic data KW - Developing countries KW - Digital storage KW - Dual model KW - Dual model approach KW - Electronic Health Records KW - Electronic health KW - Europe KW - Female KW - Health KW - Health record KW - Health records KW - Hospital data processing KW - Hospitals KW - Humans KW - Information Storage and Retrieval KW - Information management KW - Information system KW - Information systems KW - Interoperability KW - Knowledge management KW - Managers KW - Medical Record Linkage KW - Models, Organizational KW - Obstetrics KW - Open source software KW - Patient-Specific Modeling KW - Population statistics KW - Programming Languages KW - Semantic interoperability KW - Semantics KW - Software KW - User-Computer Interface KW - Vocabulary, Controlled KW - automation KW - biological model KW - computer interface KW - computer language KW - consumer KW - controlled vocabulary KW - electronic health record KW - electronic medical record KW - feasibility study KW - female KW - hospital information system KW - human KW - information retrieval KW - knowledge base KW - medical documentation KW - medical informatics KW - medical record KW - nonbiological model KW - obstetrics KW - online system KW - organization and management KW - priority journal KW - procedures KW - process optimization KW - semantics KW - software JF - Journal of Biomedical Informatics VL - 55 SP - 174 EP - 187 N1 - Cited By :20 Export Date: 10 September 2018 References: Ahtonen, A., (2013) Economic governance: helping European healthcare systems to deliver better health and wealth?, , European Policy Centre, Brussel; Allan, J., Englebright, J., Patient-centered documentation: an effective and efficient use of clinical information systems (2000) J. Nurs. Admin., 30 (2), pp. 90-95; Allones, J.L., Taboada, M., Martinez, D., Lozano, R., Sobrido, M.J., SNOMED CT module-driven clinical archetype management (2013) J. Biomed. Inform., 46 (3), pp. 388-400; Anani, N., Chen, R., Moreira, T.P., Koch, S., Retrospective checking of compliance with practice guidelines for acute stroke care: a novel experiment using openEHR's guideline definition language (2014) BMC Med. Inform. Decis. Mak., 14 (1), p. 39; Atalag, K., Yang, H.Y., Tempero, E., Warren, J.R., Evaluation of software maintainability with openEHR-a comparison of architectures (2014) Int. J. Med. Inform., 83 (11), pp. 849-859; Beale, T., Archetypes: constraint-based domain models for future-proof information systems (2002) OOPSLA 2002 Workshop on Behavioural Semantics, 105. , November; Beale, T., Archetypes and the EHR (2003) Stud. Health Technol. Inform., pp. 238-246; Beale, T., Heard, S., openEHR Architecture: Architecture Overview (2008), London; Bernstein, K., Tvede, I., Petersen, J., Bredegaard, K., Can openEHR archetypes be used in a national context? The Danish archetype proof-of-concept project (2009) MIE, pp. 147-151; Bharath, R., Fast region of interest detection for fetal genital organs in B-mode ultrasound images (2014) Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC), pp. 1-5. , 5th ISSNIP-IEEE, IEEE, May; (2010) Seamless Care, Safe Care: The Challenges of Interoperability and Patient Safety in Health Care: Proceedings of the EFMI Special Topic Conference, June 2-4, 2010, Reykjavik, Iceland, 155. , IOS Press; Bose, R., Knowledge management-enabled health care management systems: capabilities, infrastructure, and decision-support (2003) Expert Syst. Appl., 24 (1), pp. 59-71; Braun, M., Brandt, A.U., Schulz, S., Boeker, M., Validating archetypes for the multiple sclerosis functional composite (2014) BMC Med. Inform. Decis. Mak., 14 (1), p. 64; Bright, T.J., Wong, A., Dhurjati, R., Bristow, E., Bastian, L., Coeytaux, R.R., Samsa, G., Lobach, D., Effect of clinical decision-support systems a systematic review (2012) Ann. Intern. Med., 157 (1), pp. 29-43; Buck, J., Garde, S., Kohl, C.D., Knaup-Gregori, P., Towards a comprehensive electronic patient record to support an innovative individual care concept for premature infants using the openEHR approach (2009) Int. J. Med. Inform., 78 (8), pp. 521-531; Buntin, M.B., Burke, M.F., Hoaglin, M.C., Blumenthal, D., The benefits of health information technology: a review of the recent literature shows predominantly positive results (2011) Health Aff., 30 (3), pp. 464-471; Ceusters, W., Smith, B., Strategies for referent tracking in electronic health records (2006) J. Biomed. Inform., 39 (3), pp. 362-378; Christensen, T., (2009) Bringing the GP to the Forefront of EHR Development, p. 165. , Norwegian University of Technology and Science, Trondheim; da Silva, G.F., Aidar, T., de Freitas, M.T.A., Qualidade do Sistema de Informações de Nascidos Vivos no estado do Paraná, 2000 a 2005 (2011) Rev Escola Enfermagem USP, 45 (1), pp. 79-86; Dogac, A., Interoperability in ehealth systems (2012) Proc. VLDB Endowment, 5 (12), pp. 2026-2027; Dogac, A., Yuksel, M., Avci, A., Ceyhan, B., Hulur, U., Eryilmaz, Z., Mollahaliloglu, S., Akdag, R., Electronic health record interoperability as realized in Turkey's national health information system (2011) Methods Inf. Med., 50 (2); Döring, N., Doupi, P., Glonti, K., Winkelmann, J., Warren, E., McKee, M., Knai, C., Electronic discharge summaries in cross-border care in the European Union: how close are we to making it happen? (2014) Int. J. Care Coordin., 17 (1-2), pp. 38-51; Eichelberg, M., Aden, T., Riesmeier, J., Dogac, A., Laleci, G.B., A survey and analysis of electronic healthcare record standards (2005) ACM Comput. Surv. (CSUR), 37 (4), pp. 277-315; Elder, N.C., Graham, D., Brandt, E., Hickner, J., Barriers and motivators for making error reports from family medicine offices: a report from the American Academy of Family Physicians National Research Network (AAFP NRN) (2007) J. Am. Board Family Med., 20 (2), pp. 115-123; Fialho, A.S., Cismondi, F., Vieira, S.M., Reti, S.R., Sousa, J.M., Finkelstein, S.N., Data mining using clinical physiology at discharge to predict ICU readmissions (2012) Expert Syst. Appl., 39 (18), pp. 13158-13165; Fitzpatrick, P.G., Butler, M., Pitsikoulis, C., Smith, K., Walden, L., The case for integrating healthcare management courses into the curricula of selected healthcare providers (2014) J. Manage., 15 (4), p. 93; Franz, B., Schuler, A., Helm, E., Analysis of clinical documents to enable semantic interoperability (2013) Database and Expert Systems Applications, pp. 466-473. , Springer, Berlin, Heidelberg; García-Lizana, F., Giorgo, F., The future of e-health, including telemedicine and telecare, in the European Union: from stakeholders' views to evidence based decisions (2012) J. Telemed. Telecare, 18 (6), pp. 365-366; Ge, Y., Ahn, D.K., Unde, B., Gage, H.D., Carr, J.J., Patient-controlled sharing of medical imaging data across unaffiliated healthcare organizations (2013) J. Am. Med. Inform. Assoc., 20 (1), pp. 157-163; Geraci, A., Katki, F., McMonegal, L., Meyer, B., Lane, J., Wilson, P., Radatz, J., Springsteel, F., (1991) IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries, , IEEE Press; German, E., Leibowitz, A., Shahar, Y., An architecture for linking medical decision-support applications to clinical databases and its evaluation (2009) J. Biomed. Inform., 42 (2), pp. 203-218; Goossen, W., Langford, L.H., Exchanging care records using HL7 V3 care provision messages (2014) J. Am. Med. Inform. Assoc., pp. e363-e368; Gray, K., Dattakumar, A., Maeder, A., Butler-Henderson, K., Chenery, H., Advancing Ehealth Education for the Clinical Health Professions (2014); Hammond, W.E., Jaffe, C., Cimino, J.J., Huff, S.M., Standards in biomedical informatics (2014) Biomedical Informatics, pp. 211-253. , Springer, London; Häyrinen, K., Saranto, K., Nykänen, P., Definition, structure, content, use and impacts of electronic health records: a review of the research literature (2008) International journal of medical informatics, 77 (5), pp. 291-304; Jian, W.S., Hsu, C.Y., Hao, T.H., Wen, H.C., Hsu, M.H., Lee, Y.L., Li, Y.C., Chang, P., Building a portable data and information interoperability infrastructure-framework for a standard Taiwan electronic medical record template (2007) Comput. Methods Programs Biomed., 88 (2), pp. 102-111; Kalra, D., Lewalle, P., Rector, A., Rodrigues, J.M., Stroetmann, K.A., Surjan, G., Ustun, B., Zanstra, P.E., Semantic Interoperability for Better Health and Safer Healthcare (2009), http://ec.europa.eu/information_society/ehealth, Research and Deployment Roadmap for Europe. SemanticHEALTH Project Report (January 2009), Published by the European Commission; Kazmer, M.M., Lustria, M.L.A., Cortese, J., Burnett, G., Kim, J.H., Ma, J., Frost, J., Distributed knowledge in an online patient support community: authority and discovery (2014) J. Assoc. Inform. Sci. Technol.; Kellermann, A.L., Jones, S.S., What it will take to achieve the as-yet-unfulfilled promises of health information technology (2013) Health Aff., 32 (1), pp. 63-68; Khan, W.A., Hussain, M., Afzal, M., Amin, M.B., Saleem, M.A., Lee, S., Personalized-detailed clinical model for data interoperability among clinical standards (2013) Telemed. e-Health, 19 (8), pp. 632-642; Kho, D.C., Pahl, C., Supriyanto, E., Myint, Y.M., Faudzi, A.A., Salim, M.I., Motorized Remote Control of Transesophageal Echocardiography (TEE) probe tip: Preliminary Testing (2014); Krist, A.H., Beasley, J.W., Crosson, J.C., Kibbe, D.C., Klinkman, M.S., Lehmann, C.U., Waldren, S.E., Electronic health record functionality needed to better support primary care (2014) J. Am. Med. Inform. Assoc.; Kuo, A.M.H., Opportunities and challenges of cloud computing to improve health care services (2011) J. Med. Internet Res., 13 (3); Lang, A., Mertes, A., E-health policy and deployment activities in Europe (2011) Telemed. e-Health, 17 (4), pp. 262-268; Leslie, H., Heard, S., Archetypes 101 (2006), p. 18. , in: HIC 2006 and HINZ 2006: Proceedings; Lezcano, L., Sicilia, M.A., Rodríguez-Solano, C., Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules (2011) J. Biomed. Inform., 44 (2), pp. 343-353; Ma, C., Frankel, H., Beale, T., Heard, S., EHR query language (EQL)-a query language for archetype-based health records (2007) Stud. health Technol. Inform., 129 (1), p. 397; Maglogiannis, I., Towards the adoption of open source and open access electronic health record systems (2012) J. Healthcare Eng., 3 (1), pp. 141-162; Maldonado, J.A., Costa, C.M., Moner, D., Menárguez-Tortosa, M., Boscá, D., Miñarro Giménez, J.A., Fernández-Breis, J.T., Robles, M., Using the researchEHR platform to facilitate the practical application of the EHR standards (2012) J. Biomed. Inform., 45 (4), pp. 746-762; Maldonado, J.A., Moner, D., Boscá, D., Fernández-Breis, J.T., Angulo, C., Robles, M., LinkEHR-Ed: a multi-reference model archetype editor based on formal semantics (2009) Int. J. Med. Inform., 78 (8), pp. 559-570; Maldonado, J.A., Moner, D., Tomás, D., Ángulo, C., Robles, M., Fernández, J.T., Framework for clinical data standardization based on archetypes (2007) Stud. Health Technol. Inform., 129 (1), p. 454; Martínez-Costa, C., Kalra, D., Schulz, S., Improving EHR Semantic Interoperability (2014), Future Vision and Challenges. In Proceedings of MIE; Martínez-Costa, C., Menárguez-Tortosa, M., Fernández-Breis, J.T., An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes (2010) J. Biomed. Inform., 43 (5), pp. 736-746; Martínez-Costa, C., Menárguez-Tortosa, M., Fernández-Breis, J.T., Maldonado, J.A., A model-driven approach for representing clinical archetypes for semantic web environments (2009) J. Biomed. Inform., 42 (1), pp. 150-164; McCoy, A.B., Wright, A., Eysenbach, G., Malin, B.A., Patterson, E.S., Xu, H., Sittig, D.F., State of the art in clinical informatics: evidence and examples (2013) Yearbook Med. Inform., 8, pp. 13-19; Menárguez-Tortosa, M., Fernández-Breis, J.T., OWL-based reasoning methods for validating archetypes (2013) J. Biomed. Inform., 46 (2), pp. 304-317; Ngouongo, S.M., Löbe, M., Stausberg, J., The ISO/IEC 11179 norm for metadata registries: does it cover healthcare standards in empirical research? (2013) J. Biomed. Inform., 46 (2), pp. 318-327; Nguyen, L.H., Public health approaches to protecting vulnerable populations: a public health response to data interoperability to prevent child maltreatment (2014) Am. J. Public Health, pp. e1-e5; Nilashi, M., Ibrahim, O.B., Ithnin, N., Hybrid recommendation approaches for multi-criteria collaborative filtering (2014) Expert Syst. Appl., 41 (8), pp. 3879-3900; Pahl, C., Supriyanto, E.E., Personalized Cervix Ultrasound Scan Based On Robotic Arm (2012) In International Conference on Systems and Electronic Engineering (ICSEE'2012), , December, 18-19; Pahl, C., Jeffree, A., Myint, Y., Supriyanto, E., Cervix Segmentation in Ultrasound Data Based on Numerical Technique (2013) Int. J. Biol. Biomed. Eng., 7 (4), pp. 157-163; Pahl, C., Supriyanto, E., Mahmood, N.H.B., Yunus, J., Cervix detection using squared error subtraction (2012) Modelling Symposium (AMS), pp. 121-125. , 2012 Sixth Asia, IEEE, May; Pahl, C., Zare, M., Ahmad, A.B., Detschew, V., Ammon, D., Lehnert, S., Supriyanto, E., Identification of quality parameters for an e-health platform in the federal State of Thuringia in Germany (2014) J. Soft Comput. Decis. Support Syst., 1 (1), pp. 17-23; Phaal, R., Public-Domain Roadmaps, Centre for Technology Management (2011), University of Cambridge; Reimer, S., Artmann, J., Stroetmann, K., Rechtliche Aspekte der Nutzung von elektronischen Gesundheitsdaten (2013) Datenschutz Datensicherheit, 37 (3), pp. 154-159; Santos, M.R., Bax, M.P., Kalra, D., Building a logical EHR architecture based on ISO 13606 standard and semantic web technologies (2009) Studies in health technology and informatics, 160, pp. 161-165; Schloeffel, P., Beale, T., Hayworth, G., Heard, S., Leslie, H., The relationship between CEN 13606, HL7, and openEHR (2006) HIC 2006 and HINZ 2006: Proceedings, p. 24; Scott, R., Mars, M., Hebert, M., How global is 'e-health 'and 'knowledge translation'? (2012) Technology Enabled Knowledge Translation for eHealth, pp. 339-357. , Springer, New York; Silva, G., Exploring Clinical Guidelines and the Representation of Their Clinical Statments using openEHR (2011); Sinaci, A.A., Erturkmen, G.B.L., A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains (2013) J. Biomed. Inform., 46 (5), pp. 784-794; Stroetmann, K.A., Health system efficiency and ehealth interoperability-how much interoperability do we need? (2014) New Perspectives in Information Systems and Technologies, 2, pp. 395-406. , Springer International Publishing; Sundvall, E., Scalability and Semantic Sustainability in Electronic Health Record Systems (2013); Tapuria, A., Kalra, D., Kobayashi, S., Contribution of clinical archetypes, and the challenges, towards achieving semantic interoperability for EHRs (2013) Healthcare Inform. Res., 19 (4), pp. 286-292; Wiig, S., Robert, G., Anderson, J.E., Pietikainen, E., Reiman, T., Macchi, L., Aase, K., Applying different quality and safety models in healthcare improvement work: boundary objects and system thinking (2014) Reliab. Eng. Syst. Safety, 125, pp. 134-144; Wollersheim, D., Sari, A., Rahayu, W., Archetype-based electronic health records: a literature review and evaluation of their applicability to health data interoperability and access (2009) Health Inform. Manage. J., 38 (2), p. 7; Yang, J., Dong, J., Ontology-based multi-agent cooperation EHR semantic interoperability pattern research (2014) Frontier and Future Development of Information Technology in Medicine and Education, pp. 343-351. , Springer, Netherlands; Yuksel, M., Dogac, A., Taskin, C., Yalcinkaya, A., A Case for Enterprise Interoperability in Healthcare IT (2014), p. 192. , Personal Health Record Systems, Revolutionizing Enterprise Interoperability Through Scientific FoundationsUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930734088&doi=10.1016%2fj.jbi.2015.04.004&partnerID=40&md5=a84596ea20ddb6adb951ce1807489f8e RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works. © 2015 Elsevier Inc. ER - TY - CONF T1 - Semantic interoperability for infectious diseases reporting system A1 - Pandiyan, M A1 - El Hassan, O A1 - Maamar, Z A1 - Rajasekaran, P Y1 - 2011/// KW - Coding standards KW - Communicable Diseases KW - Diseases KW - Health care KW - Health-care system KW - Healthcare system KW - Infectious disease KW - Information exchanges KW - Information systems KW - Interoperability KW - Medical computing KW - National level KW - Ontology KW - Ontology-based KW - Regulatory agencies KW - Reporting systems KW - Semantic Web KW - Semantic interoperability KW - Semantic rules KW - Semantics KW - Web services SP - 363 EP - 367 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-83155184692&partnerID=40&md5=8926a038efd80830baaf313848776659 L1 - file:///C:/Users/fernanda.dorea/Downloads/Semantic_Interoperability_for_Infectious_Disease_R.pdf N1 - Export Date: 10 September 2018 References: Smith, M.K., Welty, C., McGuinness, D., OWLWeb Ontology Language Guide (2011) W3C Recommendation, , http://www.w3.org/TR/owlguide/, May 14; (2004) Owl Web Ontology Language-reference, , http://www.w3.org/TR/owl-ref/, LSDIS Lab, University of Georgia; Iqbal, A.M., Shepherd, M., Abidi, S.S.R., An Ontology-Based Electronic Medical Record for Chronic Disease Management Jan. 2011 44th Hawaii International Conference, pp. 4-6; Sampalli, T., Shepherd, M., Duffy, J., A Patient Profile Ontology in the Heterogeneous Domain of Complex and Chronic Health Conditions Jan. 2011 System Sciences (HICSS), 2011 44th Hawaii International Conference, pp. 4-6; Arch-int, N., Arch-int, S., Semantic information integration for electronic patient records using ontology and web services model April. 2011 Information Science and Applications (ICISA), International Conference, pp. 3-5; (2011) International Classification of Diseases, , http://www.cdc.gov/nchs/icd/icd10.htm, May 14; (2011) International Classification of Diseases, , http://www.cdc.gov/nchs/icd/icd9.htm, Ninth Revision (ICD-9) May 24; (2011) Intersystems Cache, , http://www.intersystems.com/cache/, May 24; (2011) Business Objects, , http://www.sap.com/solutions/sapbusinessobjects/index.epx, May 24; (2011) Jena A Semantic Web Framework for Java., , http://jena.sourceforge.net/, May 14; El-Hassan, O., Fiadeiro, J.L., Heckel, R., Managing socio-technical interactions in healthcare systems 2008 Proceedings of the 2007 International Conference on Business Process Management; Khosravifar, B., Bentahar, J., Moazin, A., Maamar, Z., Thiran, P., Analyzing Communities vs. Single Agent-Based Web Services: Trust Perspectives July 2010 Services Computing (SCC), 2010 IEEE International Conference RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The healthcare setting is multifaceted, comprised of many different components including private, governmental, and regulatory agencies. There is always a necessity of timely and reliable information exchange among these agencies especially on "Infectious Disease" information due to their criticali-ty. The heterogeneity of the systems used by these agencies has led us into designing and developing an interoperable solution to exchange data effectively among several independent yet collaborating health authorities at both state and national levels. This research work articulates the efforts put into achieving an interoperable "Infectious Diseases Reporting System" that incorporates ontology-based semantic rules to align different infectious disease coding standards and to deploy Web services for collecting data from remote sources. This effort is a first step towards achieving a policy-based interoperable Infectious disease monitoring system which can be used across different yet collaborating regulatory agencies. © 2011 Polish Info Processing Soc. ER - TY - CONF T1 - Joined-up government: Current trends and applications in e-Government and eHealth A1 - Pappa, D D A1 - Stergioulas, L K Y1 - 2005/// KW - Administrative process KW - Customer interfaces KW - E-government services KW - Emerging architectures KW - Government data processing KW - Health care KW - Healthcare sectors KW - Healthcare services KW - Information management KW - Information technology KW - Interoperability KW - Public authorities KW - Service management VL - 1 N1 - Cited By :1 Export Date: 10 September 2018 References: e-Government Leadership: Realising the vision (2002), http://www.accenture.com/xd/xd.asp?it=enWeb&xd=industries%5Cgovernment%5Cgove_welcome.xml, Accenture, company report available at; Andersen, A., e-Government. Anwendung der neuen Informations- und Kommunikationstechnologien durch die öffentliche Hand (2001), company report; Boyer, C., Provost, M., Baujard, V., Highlights of the 8th HON Survey of Health and Medical Internet Users (2002), http://www.hon.ch/Survey/8th_HON_results.html, Health On the Net Foundation, retrieved November 24, 2005 from; Brynjolfsson, E., The Productivity Paradox of Information Technology (1993) Communication of ACM, 36 (12), pp. 67-77. , December; Chevallerau, F.X., eGovernment in the Member States of the European Union (2005), http://europa.eu.int/idabc/en/document/4370/254, IDABC eGovernment Observatory, retrieved November 24, 2005 from; e-Government's Next Generation (2002), http://www.deloitte.com, Deloitte Research, company report, retrieved November 24, 2005 from; At the Dawn of e- Government: The Citizen as customer (2000), http://www.deloitte.com, Deloitte Research, retrieved November 24, 2005 from; Dedrick, J., Gurbaxani, V., Kraemer, K., Information technology and economic performance: A critical review of the empirical evidence (2003), from ACM Computing Surveys; Government Working Group (2005), http://dublincore.org/groups/government/, Dublin Core Metadata Initiative (DCMI), home-page retrieved November 24, from; An Integrated Platform for Realising Online One-Stop Government www.egov-project.org, EGOV Project, project home-page available at; eEurope 2005, An Information Society For All Action Plan (2002), http://europa.eu.int/eurlex/en/com/cnc/2002/com2002_0263en01.pdf, European Commission, COM (02) 263 Final, retrieved November 24, 2005 from; eEurope 2002: Quality Criteria for Health related Websites (2002), http://europa.eu.int/information_society/eeurope/ehealth/index_en.htm, European Commission, retrieved November 24, 2005 from; The Role of e- Government for Europe's Future (2003), http://europa.eu.int/information_society/eeurope/2005/doc/all_about/egov_communication_en.pdf, European Commission, ; communication to the European Council COM(2003) 567 Final retrieved November 24, 2005 from; COMMISSION STAFF WORKING DOCUMENT (2003), http://europa.eu.int/idabc/en/document/3571/5665, European Comission, Linking up Europe: the importance of interoperability for egovernment services., retrieved November 24, 2005 from; Summary of EGovernment Interoperability Workshops "eGovernment Interoperability in the 2010 horizon - Addressing the Future IST RTD" (2003), http://europa.eu.int/information_society/activities/egovernment_research/doc/summary_interop_workshops.pdf, European Comission retrieved November 24, 2005 from; (2005), http://europa.eu.int/idabc/en/document/3473/5585, European Interoperability Framework for Pan- European E-Government Services. Final Version 1.0, retrieved November 24, from; Foster, I., The anatomy of the grid: enabling scalable virtual organizations (2001) International Journal of High Performance Computing Applications, 15, pp. 200-222. , http://www.globus.org/alliance/publications/papers/anatomy.pdf, retrieved November 24, 2005 from; Goble, C., De Roure, D., The Grid: An Application of the Semantic Web (2002) SIGMOD Record, 31 (4). , December; eHealth in 2010: Realising a Knowledge-based Approach to Healthcare in the EU. Challenges for the Ambient Care System (2004), IPTS Report; Leading the transformation to E-Government (2000), http://www.idt.unisg.ch/org/idt/ceegov.nsf/0/6905c2a1e9958b3dc1256c8c0051730d/$FILE/001000-Leading%20the%20Transformation%20to%20EGovernment.pdf, KPMG Consulting, company report, retrieved November 24, 2005 from; Lenk, K., Tranmüller, R., A Framework for Electronic Government (2000), pp. 271-277. , DEXA 2000, IEEE Press; Leitner, C., e-Government in Europe: the state of affairs (2003), http://www.eeuropeawards.org/, presented at the e- Government 2003 Conference, Como, Italy, 7-8 July, European Institute of Public Administration, retrieved November 24, 2005, from; Millard, J., Final Report to the European Comission 2004 (2005), http://europa.eu.int/information_society/activities/egovernment_research/doc/back_office_reorganisation_volume1_mainreport.pdf, Reorganisation of government back-offices for better electronic public services - European good practices, retrieved November 24; Annual Review 2005 "self-care: realising the vision http://www.pagb.co.uk/pagb/downloads/aboutpagb/Self_Care_Review_2005.pdf, PAGB, available at; Booklet 2.5 "E-Government: The next American Revolution" (2001), http://www.digitalgovernment.org/archive/library/pdf/wingo-egov.pdf, The Council for Excellence in Government, retrieved November 24, 2005 from; Transforming Governemet to serve Canadians better (2005), www.gol-ged.gc.ca, The government on-line advisory panel, Report to the president of the treasury board of Canada, 2002, retrieved November 24, from; e-Government Interoperability Framework (e-GIF) Version 6.1 (2005), http://www.govtalk.gov.uk/schemasstandards/egif_document.asp?docnum=949, The UK eGovernment Unit, retrieved November 24, from; Modernising Government (1999), UK Modernising Government secretariat, report presented to UK Parliament by the Prime Minister and the Minister for the Cabinet Office; Guidelines for UK government websites: Framework for local government (2003), http://www.cabinetoffice.gov.uk/egovernment/docs/localgov/pdf/localgov.pdf, U.K.Office of the e-Envoy, retrieved November 24, 2005 from; Wimmer, M., Tambouris, E., Online One-Stop Government: A working framework and requirements (2002) Proceedings of the IFIP World Computer Congress, , In, August 26-30, 2002, Montreal; Web Services Description Language (WSDL) 1.1 (2005), http://www.w3.org/TR/wsdl, World Wide Web Consortium (W3C), W3C note, retrieved November 24, from; Extensible Markup Language (XML) (2005), http://www.w3.org/TR/REC-xml, World Wide Web Consortium (W3C), W3C Recommendation retrieved November 24, fromUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84903640677&partnerID=40&md5=7f6ed37d7fa8c4250f34308fe4545e75 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Once only regarded as a means for modernising the public sector and increasing government productivity and efficiency, e-Government is presently recognised as a key enabler of citizencentric, cooperative, "seamless", but polycentric, modern governance. This implies not only a profound transformation in the way government interacts with the governed but also the reinvention of its internal processes and organisation. At the front end, i.e. the customer interface, this calls for joined-up services that are effective, simple to use, shaped around and responding to the needs of the users and are accessible through a variety of delivery channels. On the back office level the joining-up of public services raises a demand for interconnection and interoperability that goes beyond the mere technical linking of computer networks to include the sharing of information and the re-organisation of administrative processes to support the seamless delivery of e-Government services. This paper reviews the concept of joined-up government from the public authority's point of view and investigates the emerging architectures for service management and delivery. It also discusses the application of this approach in the healthcare sector for the online provision of healthcare services. ER - TY - CONF T1 - Semantic interoperability solution for multicentric breast cancer trials at the integrate EU project A1 - Paraiso-Medina, S A1 - Perez-Rey, D A1 - Alonso-Calvo, R A1 - Claerhout, B A1 - De Schepper, K A1 - Hennebert, P A1 - Lhaut, J A1 - Van Leeuwen, J A1 - Bucur, A Y1 - 2013/// KW - Breast Cancer KW - Breast Neoplasms KW - Breast cancer KW - Clinical trial KW - Clinical trials KW - Diseases KW - Experiments KW - HL7 KW - Health care KW - INTEGRATE project KW - Interoperability KW - Medical applications KW - SNOMED KW - Semantic interoperability KW - Semantics SP - 34 EP - 41 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877987237&partnerID=40&md5=e8eec4b6a5807b84d88ff2774645c136 N1 - Cited By :5 Export Date: 10 September 2018 References: Antonioletti, M., Malcolm, A., Baxter, R., Borley, A., Chue, N.P., Collins, B., Hardman, N., The design and implementation of grid database services in OGSA-DAI (2005) Concurrency and Computation: Practice and Experience, 17 (2-4), pp. 357-376; Baader, F., Lutz, C., Suntisrivaraporn, B., CEL - A polynomial. time reasoner for life science ontologies (2006) Lectures Notes in Computer Science, 4130, pp. 287-291. , 2006 DOI: 10.1007/11814771-25; Bizer, C., Cyganiak, R., D2R server - Publishing relational databases on the semantic web (2006) The 5th International Sematic Web Conference (ISWC); Brochhausen, M., Spear, A.D., Cocos, C., Weiler, G., Martin, L., Anguita, A., Stenzhorn, H., Tsinakis, M., The ACGT master ontology and its applications - Towards an ontology-driven cancer research and management system (2011) J Biomed Inform, 44 (1), pp. 8-25; Broekstra, J., Kampman, A., Van Harmelen, F., Sesame: An architecture for storing and querying RDF and RDF schema (2002) Proceedings of the First International Semantic Web Conference (ISWC2002), pp. 54-68. , Number 2342 in Lecture Notes in Computer Science (LNCS), Springer-Verlag 2002; Brown, E.G., Wood, L., Wood, S., The medical dictionary for regulatory activities (MedDRA) (1999) Drug Safety, 20 (2), pp. 109-117; Erling, O., Mikhailov, I., RDF support in the virtuso DBMS (2009) Studies in Computational Intelligence, 221, pp. 7-24. , 2009; Von Eschenbach, A., Buetow, K., Cancer informatic vision: Cabig (2006) Cancer Informatics, 2, pp. 22-24; Globus Toolkit from Globus Alliance, , http://www.globus.org/toolkit, [16 July 2012]; Reference Information Model, , http://www.hl7.org/implement/standards/rim.cfm, [16 July 2012]; INTEGRATE Driving Excellence in Integrative Cancer Research, , http://www.fp7-integrate.eu, [16 July 2012]; Kazakov, Y., Krötzsch, M., Simancik, F., Concurrent classification of EL ontologies (2011) Lectures Notes in Computer Science, 7031, pp. 305-320. , 2011; Kazakov, Y., Krötzsch, M., Simancík, F., ELK: A reasoner for OWL EL ontologies (2012) Tech. Rep; Kiryakov, A., Ognyanov, D., Manov, D., OWLIM - A pragmatic semantic repository for OWL (2005) Lectures Notes in Computer Science, 3807, pp. 182-192. , 2005; Lawley, M., Bousquet, C., Fast classification in protege: Snorocket as an OWL2 EL reasoner (2010) Australasian Ontology Workshop; Martin, L., Anguita, A., Graf, N., Tsinakis, M., Brochhausen, M., Rüping, S., Sfakianakis, S., Stenzhorn, H., ACGT: Advancing clinic-genomic trials on cancer - Four years of experience (2011) Stud Health Technol Inform, 169, pp. 734-738; McDonald, C.J., Huff, S.M., Suico, J.G., Hill, G., Leavelle, D., Aller, R., Forrey, A., Maloney, P., LOINC, a universal standard for identifying laboratory observations: A 5-year update (2003) Clinical Chemistry, 49 (4), pp. 624-633; McGuinness, D.L., Van Harmelen, F., OWL web ontology language overview (2004) W3C Recommendation, , http://www.w3.org/TR/owl-features, [16 July 2012]; Murphy Shawn, N., Weber, G., Mendis, M., Gainer, V., Chueh, H.C., Churchill, S., Kohane, I., Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) (2010) J Am Med Inform Assoc, 17, pp. 124-130. , 2010; Neo-Adjunvant Lapatinib and Trastuzumab Treatment Optimisation Trial, , http://www.alttotrials.com/neoaltto.php, Neo-ALTTO [16 July, 2012]; Parsia, B., Sirin, E., Pellet: An OWL DL reasoner (2004) ISWC 2004, , 2004. ISWC; Shearer, R., Motik, B., Horrocks, I., HermiT: A highly-efficient OWL reasoner (2008) Proceedings of the 5th International Workshop on OWL: Experiences and Directions (OWLED 2008), pp. 26-27; SNOMED Clinical Terms Core Content, , http://www.ihtsdo.org/snomed-ct, [16 July 2012]; Stang, P.E., Ryan, P.B., Racoosin, J.A., Overhage, J.M., Hartzema, A.G., Reich, C., Welebob, E., Woodcock, J., Advancing the science for active surveillance: Rationale and design for the observational medical outcomes partnership (2010) Ann Intern Med, 153 (9), pp. 600-606. , 2010 Nov 2; Tsarkov, D., Horrocks, I., Reasoner prototype: Implementing new reasoner with datatypes support (2003) WonderWeb Project Deliverable; Topoisomerase II Alpha Gene Amplification and Protein Overexpression Predicting Efficacy of Epirubicin (TOP), , http://clinicaltrials.gov/ct2/show/NCT00162812, TOP, Jules Bordet Institute [16 July, 2012] RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The introduction of -omic information within current clinical treatment is one of the main challenges to transfer the huge amount of genomic-based results. The number of potential translational clinical trials is therefore experiencing a dramatic increase, with the corresponding increment on patient variability. Such scenario requires a larger population to recruit a minimum set of patients that may involve multi-centric trials, with associated challenges on heterogeneous data integration. To ensure sustainability on clinical trial management, semantic interoperability is one of the main goals addressed by international initiatives such as the EU funded INTEGRATE project: "Driving Excellence in Integrative Cancer Research". This paper describes the approach adopted within an international research initiative, providing a homogeneous platform to manage clinical information from patients on breast cancer clinical trials. Following the project "leitmotif" of reusing standards supported by a large community, we have developed a solution providing a common data model (i.e. HL7 RIM-based), a biomedical domain vocabulary (i.e. SNOMED) as core dataset and resources from the semantic web community adapted for the biomedical domain. After one year and a half of collaboration, the INTEGRATE consortium has been able to develop a solution providing the reasoning capabilities required to solve clinical trial patient recruitment. The next challenge will be to extend the current solution to support a cohort selection tool allowing prospective analysis and predictive modeling. ER - TY - JOUR T1 - Semantic normalization and query abstraction based on SNOMED-CT and HL7: Supporting multicentric clinical trials A1 - Paraiso-Medina, S A1 - Perez-Rey, D A1 - Bucur, A A1 - Claerhout, B A1 - Alonso-Calvo, R Y1 - 2015/// KW - Abstracting KW - Abstracting and Indexing as Topic KW - Abstraction mechanism KW - Biomarkers KW - Biomedical information KW - Biomedical vocabularies KW - Clinical Trials as Topic KW - Data integration KW - Data representations KW - Electronic Health Records KW - Humans KW - Medical applications KW - Normalization process KW - Population statistics KW - Query languages KW - Semantic Web KW - Semantic Web technology KW - Semantic interoperability KW - Semantic knowledge KW - Semantics KW - Systematized Nomenclature of Medicine KW - clinical trial (topic) KW - documentation KW - electronic medical record KW - human KW - standards JF - IEEE Journal of Biomedical and Health Informatics VL - 19 IS - 3 SP - 1061 EP - 1067 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929327432&doi=10.1109%2FJBHI.2014.2357025&partnerID=40&md5=826cdd20ec7542e3429c6afc217ab622 N1 - Cited By :10 Export Date: 10 September 2018 References: McShane, L.M., Cavenagh, M.M., Lively, T.G., Eberhard, D.A., Bigbee, W.L., Williams, P.M., Conley, B.A., Criteria for the use of omics-based predictors in clinical trials (2013) Nature, 502 (7471), pp. 317-320; Hodge, Jr.J.G., Gostin, L.O., Jacobson, P.D., Legal issues concerning electronic health information (1999) J. Amer. Med. Assoc., 282 (15), pp. 1466-1471; Anguita, A., Martin, L., Pérez-Rey, D., Maojo, V., A review of methods and tools for database integration in biomedicine (2010) Curr. Bioinformat., 5, pp. 253-269; Claerhout, B., Forgó, N., Krügel, T., Arning, M., De Moor, G., A data protection framework for trans-European genetic research projects (2008) Stud. Health Technol. Informat., 141, pp. 67-72; Oeffinger, K.C., Ford, J.S., Moskowitz, C.S., Diller, L.R., Hudson, M.M., Chou, J.F., Robison, L.L., Breast cancer surveillance practices among women previously treated with chest radiation for a childhood cancer (2009) J. Amer. Med. Assoc., 301 (4), pp. 404-414; Pakhomov, S., Weston, S.A., Jacobsen, S.J., Chute, C.G., Meverden, R., Roger, V.L., Electronic medical records for clinical research: Application to the identification of heart failure (2007) Amer. J. Managed Care, 13 (6), pp. 281-288; Hersh, W.R., Adding value to the electronic health record through secondary use of data for quality assurance, research, and surveillance (2007) Clin. Pharmacol. Therapeutics, 81, pp. 126-128; Stang, P.E., Ryan, P.B., Racoosin, J.A., Overhage, J.M., Hartzema, A.G., Reich, C., Woodcock, J., Advancing the science for active surveillance: Rationale and design for the observational medical outcomes partnership (2010) Ann. Internal Med., 153 (9), pp. 600-606; Murphy, S.N., Weber, G., Mendis, M., Gainer, V., Chueh, H.C., Churchill, S., Kohane, I., Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) (2010) J. Amer. Med. Informat. Assoc., 17 (2), pp. 124-130; Oster, S., Langella, S., Hastings, S., Ervin, D., Madduri, R., Phillips, J., Saltz, J., Cagrid 1.0: An enterprise grid infrastructure for biomedical research (2008) J. Amer. Med. Informat. Assoc., 15 (2), pp. 138-149; (2013) Driving Excellence in In-tegrative Cancer Research, , http://www.fp7-integrate.eu/index.php/project, Fp7-integrate.eu. (Dec. 31; (2013) Enabling Information Re-Use by Linking Clinical Research and Care, , http://eurecaproject.eu/, eurecaproject.eu. (Dec. 31; Antonioletti, M., Atkinson, M., Baxter, R., Borley, A., Chue Hong, N.P., Collins, B., Westhead, M., The design and implementation of grid database services in OGSA-DAI (2005) Concurrency Comput.: Practice Experience, 17 (2-4), pp. 357-376; Moratilla, J.M., Alonso-Calvo, R., Molina-Vaquero, G., Paraiso-Medina, S., Perez-Rey, D., Maojo, V., A data model based on semantically enhanced HL7 RIM for sharing patient data of breast cancer clinical trials (2012) Stud. Health Technol. Informat., 192, pp. 971-971; Kalra, D., Beale, T., Heard, S., The openEHR foundation (2005) Stud. Health Technol. Informat., 115, pp. 153-173; Fridsma, D.B., Evans, J., Hastak, S., Mead, C.N., The BRIDG project: A technical report (2008) J. Amer. Med. Informat. Assoc., 15 (2), pp. 130-137; Kuchinke, W., Aerts, J., Semler, S.C., Ohmann, C., CDISC standard-based electronic archiving of clinical trials (2009) Methods Inf. Med., 48 (5), pp. 408-413; Benson, T., (2012) Principles of Health Interoperability HL7 and SNOMED, , New York NY USA: Springer; Beeler, G.W., HL7 Version 3-An object-oriented methodology for collaborative standards development (1998) Int. J. Med. Informat., 48 (1), pp. 151-161; Aso, S., Perez-Rey, D., Alonso-Calvo, R., Rico-Diez, A., Bucur, A., Claerhout, B., Maojo, V., Analyzing SNOMED CT and HL7 terminology binding for semantic interoperability on post-genomic clinical trials (2012) Stud. Health Technol. Informat., 192, pp. 980-980; Bos, L., SNOMED-CT: The advanced terminology and coding system for eHealth (2006) Stud. Health Technol. Informat., 121, pp. 279-290; Seal, R.L., Gordon, S.M., Lush, M.J., Wright, M.W., Bruford, E.A., Genenames.org: The HGNC resources in 2011 (2011) Nucleic Acids Res., 39, pp. D514-D519; McDonald, C.J., Huff, S.M., Suico, J.G., Hill, G., Leavelle, D., Aller, R., Maloney, P., LOINC, a universal standard for identifying laboratory observations: A 5-year update (2003) Clin. Chem., 49 (4), pp. 624-633; Paraiso-Medina, S., Perez-Rey, D., Alonso-Calvo, R., Claerhout, B., De Schepper, K., Hennebert, P., Lhaut, J., Bucur, A., Semantic interoperability solution for multicentric breast cancer trials at the integrate EU project (2013) Proc. Int. Conf. Health Informat., (1), pp. 34-41; Bucur, A., Van Leeuwen, J., Perez-Rey, D., Calvo, R.A., Claerhout, B., De Schepper, K., Identifying the semantics of eligibility criteria of clinical trials based on relevant medical ontologies (2012) Proc. IEEE 12th Int. Conf. Bioinformat. Bioeng, pp. 413-421. , Nov; (1992) The ICD-10 Classification of Mental and Behavioural Disorders: Clinical Descriptions and Diagnostic Guidelines, 1. , World Health Organization, Geneva, Switzerland; Sioutos, N., Coronado, S.D., Haber, M.W., Hartel, F.W., Shaiu, W.L., Wright, L.W., NCI thesaurus: A semantic model integrating cancer-related clinical and molecular information (2007) J. Biomed. Informat., 40 (1), pp. 30-43; Noy, N.F., Shah, N.H., Whetzel, P.L., Dai, B., Dorf, M., Griffith, N., Musen, M.A., BioPortal: Ontologies and integrated data resources at the click of a mouse (2009) Nucleic Acids Res., 37, pp. W170-W173; Cheetham, E.H., Dolin, R., Markwell, D., Curry, J., Gabriel, D., Hausam, R., Knight, B., Townend, I., (2008) Using SNOMED CT in HL7 v3 Implementation Guide, , Release 1.5; (2013) Topoisomerase II Alpha Gene Amplification and Protein Overexpression Predicting Efficacy of Epirubicin (TOP), , http://clinicaltrials.gov/ct2/show/NCT00162812, TOP, Jules Bordet Institute. (Dec. 31; Goldhirsch, A., Wood, W.C., Coates, A.S., Gelber, R.D., Thürlimann, B., Senn, H.J., Strategies for subtypes-Dealing with the diversity of breast cancer: Highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2011 (2011) Ann. Oncol., 22 (8), pp. 1736-1747 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Advances in the use of omic data and other biomarkers are increasing the number of variables in clinical research. Additional data have stratified the population of patients and require that current studies be performed among multiple institutions. Semantic interoperability and standardized data representation are a crucial task in the management of modern clinical trials. In the past few years, different efforts have focused on integrating biomedical information. Due to the complexity of this domain and the specific requirements of clinical research, the majority of data integration tasks are still performed manually. This paper presents a semantic normalization process and a query abstraction mechanism to facilitate data integration and retrieval. A process based on well-established standards from the biomedical domain and the latest semantic web technologies has been developed. Methods proposed in this paper have been tested within the EURECA EU research project, where clinical scenarios require the extraction of semantic knowledge from biomedical vocabularies. The aim of this paper is to provide a novel method to abstract from the data model and query syntax. The proposed approach has been compared with other initiatives in the field by storing the same dataset with each of those solutions. Results show an extended functionality and query capabilities at the cost of slightly worse performance in query execution. Implementations in real settings have shown that following this approach, usable interfaces can be developed to exploit clinical trial data outcomes. © 2014 IEEE. ER - TY - CONF T1 - Building a time-saving and adaptable tool to report adverse drug events A1 - Parès, Y A1 - Declerck, G A1 - Hussain, S A1 - Ng, R A1 - Jaulent, M.-C. Y1 - 2013/// KW - Adverse Drug Events Reporting KW - Adverse Drug Reaction Reporting Systems KW - Documentation KW - Electronic Health Records KW - France KW - Information Storage and Retrieval KW - Medical Record Linkage KW - Secondary Use ofEHR KW - Semantic Interoperability KW - Semantics KW - Software KW - Software Design KW - User-Computer Interface KW - Workload KW - computer interface KW - computer program KW - devices KW - documentation KW - drug surveillance program KW - electronic medical record KW - information retrieval KW - medical record KW - organization and management KW - procedures KW - semantics KW - workload VL - 192 IS - 1 SP - 903 EP - 907 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894334563&doi=10.3233%2F978-1-61499-289-9-903&partnerID=40&md5=2ac5670e26a6cca536e27451c92767ea N1 - Cited By :3 Export Date: 10 September 2018 References: Hazell, L., Shakir, S.A., Under-reporting of adverse drug reactions: A systematic review (2006) Drug Safety, 29 (5), pp. 385-396; Van Der Heijden, P.G., Puijenbroek, E.P., Van Buuren, S., Van De Hofstede, J.W., On the assessment of adverse drug reactions from spontaneous reporting systems: The influence of under-reporting on odds ratios (2002) Stat Med, 21, pp. 2027-2044; Bates, D.W., Evans, R.S., Murff, H., Stetson, P.D., Pizziferri, L., Hripcsak, G., Detecting adverse events using information technology (2003) Journal of the American Medical Informatics Association, 10 (2), pp. 115-128; Cullen, D.J., Bates, D.W., Small, S.D., Cooper, J.B., Nemeskal, A.R., Leape, L.L., The incident reporting system does not detect adverse drug events: A problem for quality improvement (1995) Jt. Comm. J. Qual. Improv, 21, pp. 541-548; Linder, J.A., Haas, J.S., Iyer, A., Labuzetta, M.A., Ibara, M., Celeste, M., Getty, G., Bates, D.W., Secondary use of electronic health record data: Spontaneous triggered adverse drug event reporting (2010) Pharmacoepidemiol Drug Saf, 19 (12), pp. 1211-1215; Declerck, G., Hussain, S., Parès, Y., Daniel, C., Jaulent, M.C., Laleci, G.B., Semantic-sensitive extraction of ehr data to support adverse drug events reporting (2012) Proceedings of the Semantic Web Application and Tools for Life Science Workshop, Paris, France; Scalable, Standard Based Interoperability Framework for Sustainable Proactive Post Market Safety Studies [Internet], , http://www.salusproject.eu; Brajovic, S., Piazza-Hepp, T., Swartz, L., Dal Pan, G., Quality assessment of spontaneous triggered adverse event reports received by the food and drug administration (2012) Pharmacoepidemiol Drug Saf, 21 (6), pp. 565-570; (2010) Technical Framework Supplement Drug Safety Content Profile (DSC), Integrating the Healthcare Enterprise (IHE), , IHE Quality, Research and Public Health (QRPH) , Trial Implementation Supplement, Aug; (2011) IHE IT Infrastructure Technical Framework Supplement, Retrieve Form for Data Capture (RFD), Trial Implementation, , Aug. 19; (2001) ICH Guideline E2B (R2), Electronic Transmission of Individual Case Safety Reports-Message Specification, , ICH ICSR DTD Version 2.1, Final Version 2.3, Document Revision Feb. 1; Laleci, G.B., Yuksel, M., Dogac, A., Providing semantic interoperability between clinical care and clinical research domains IEEE TITB, , http://www.srdc.com.tr/publications/2012/SALUSSemanticInteroperability. pdf; Zdun, U., Concepts for model-driven design and evolution of domain-specific languages (2005) Proceedings of the International Workshop on Software Factories at OOPSLA 2005, San Diego, CA, USA, pp. 1-6; (2012) Pilot Application Scenario and Requirement Specifications of the Pilot Application, , http://www.salusproject.eu, May 28. Available in the Public Document section RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The difficult task of detecting adverse drug events (ADEs) and the tedious process of building manual reports of ADE occurrences out of patient profiles result in a majority of adverse reactions not being reported to health regulatory authorities. The SALUS individual case safety report (ICSR) reporting tool, a component currently developed within the SALUS project, aims to support semi-automatic reporting of ADEs to regulatory authorities. In this paper, we present an initial design and current state of of our ICSR reporting tool that features: (i) automatic pre-population of reporting forms through extraction of the patient data contained in an Electronic Health Record (EHR); (ii) generation and electronic submission of the completed ICSRs by the physician to regulatory authorities; and (iii) integration of the reporting process into the physician's work-flow to limit the disturbance. The objective is to increase the rates of ADE reporting and the quality of the reported data. The SALUS interoperability platform supports patient data extraction independently of the EHR data model in use and allows generation of reports using the format expected by regulatory authorities. © 2013 IMIA and IOS Press. ER - TY - JOUR T1 - A semantic problem solving environment for integrative parasite research: identification of intervention targets for Trypanosoma cruzi. A1 - Parikh, Priti P A1 - Minning, Todd A A1 - Nguyen, Vinh A1 - Lalithsena, Sarasi A1 - Asiaee, Amir H A1 - Sahoo, Satya S A1 - Doshi, Prashant A1 - Tarleton, Rick A1 - Sheth, Amit P Y1 - 2012/// KW - Problem Solving KW - Semantics KW - Trypanosoma KW - Trypanosoma congolense KW - Trypanosoma cruzi PB - Public Library of Science JF - PLoS neglected tropical diseases VL - 6 IS - 1 SP - e1458 EP - e1458 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external databases. Reconciling the different forms of heterogeneity and effectively integrating data from disparate sources is a nontrivial task for biologists and requires a dedicated informatics infrastructure. Thus, we developed an integrated environment using Semantic Web technologies that may provide biologists the tools for managing and analyzing their data, without the need for acquiring in-depth computer science knowledge. METHODOLOGY/PRINCIPAL FINDINGS We developed a semantic problem-solving environment (SPSE) that uses ontologies to integrate internal lab data with external resources in a Parasite Knowledge Base (PKB), which has the ability to query across these resources in a unified manner. The SPSE includes Web Ontology Language (OWL)-based ontologies, experimental data with its provenance information represented using the Resource Description Format (RDF), and a visual querying tool, Cuebee, that features integrated use of Web services. We demonstrate the use and benefit of SPSE using example queries for identifying gene knockout targets of Trypanosoma cruzi for vaccine development. Answers to these queries involve looking up multiple sources of data, linking them together and presenting the results. CONCLUSION/SIGNIFICANCE The SPSE facilitates parasitologists in leveraging the growing, but disparate, parasite data resources by offering an integrative platform that utilizes Semantic Web techniques, while keeping their workload increase minimal. ER - TY - JOUR T1 - Electronic health records implementation in Morocco: Challenges of silo efforts and recommendations for improvements A1 - Parks, R A1 - Wigand, R T A1 - Othmani, M B A1 - Serhier, Z A1 - Bouhaddou, O Y1 - 2019/// JF - International Journal of Medical Informatics VL - 129 SP - 430 EP - 437 DO - 10.1016/j.ijmedinf.2019.05.026 N2 - ©2019 Elsevier B.V. Objective: Electronic Health Records (EHRs) interventions hold the promise for enabling better healthcare. However, the implementation of EHR systems has been scarce in developing countries. The objective of this study is to investigate the state of EHRs implementation in Morocco; and draw insights for potential improvements. Materials and methods: University Medical Centers, known by locals in French as Centres Hospitalier Universitaires (CHU), are the largest and most advanced public healthcare centers in Morocco. A two-phase qualitative study was conducted in four out of the five CHUs. Phase One involved data collection through semi-structured interviews with 27 clinician champions, administrators, and medical directors. Phase Two included a brainstorming session during a health informatics conference held in Fes, Morocco. The data were analyzed using inductive analysis. Results: We identified five main categories of challenges due to silo strategies: (1) EHRs selection and weak bargaining power, (2) identical errors repeated across silos, (3) a lack of interoperability standards, (4) insufficient human and financial, and (5) missed cooperation and collaboration opportunities. Discussion: While identifying these silo challenges is an important milestone, proposing guidelines to address these challenges can bring Morocco and similar developing countries a step closer to improving healthcare through the use of health informatics and EHRs. Our recommendations for public healthcare organizations are threefold: (1) recognize the power of partnerships among all CHUs, (2) establish an e-health framework, and (3) seek national and international collaborations to drive and shape the eHealth agenda. Furthermore, we align our recommendations with the World Health Organization toolkit for an eHealth strategy to further benefit developing countries. Conclusion: This study identifies the challenges faced by the Moroccan EHRs implementation silo-ed strategy, and it proposes practical and fundamental guidelines to address these challenges and develop an interoperable and sustainable national eHealth system in Morocco and similar developing countries. ER - TY - JOUR T1 - Automated mapping of laboratory tests to LOINC codes using noisy labels in a national electronic health record system database A1 - Parr, S K A1 - Shotwell, M S A1 - Jeffery, A D A1 - Lasko, T A A1 - Matheny, M E Y1 - 2018/// JF - Journal of the American Medical Informatics Association VL - 25 IS - 10 SP - 1292 EP - 1300 DO - 10.1093/jamia/ocy110 N2 - ©Published by Oxford University Press on behalf of the American Medical Informatics Association 2018. This work is written by US Government employees and is in the public domain in the US. Objective Standards such as the Logical Observation Identifiers Names and Codes (LOINC ®) are critical for interoperability and integrating data into common data models, but are inconsistently used. Without consistent mapping to standards, clinical data cannot be harmonized, shared, or interpreted in a meaningful context. We sought to develop an automated machine learning pipeline that leverages noisy labels to map laboratory data to LOINC codes. Materials and Methods Across 130 sites in the Department of Veterans Affairs Corporate Data Warehouse, we selected the 150 most commonly used laboratory tests with numeric results per site from 2000 through 2016. Using source data text and numeric fields, we developed a machine learning model and manually validated random samples from both labeled and unlabeled datasets. Results The raw laboratory data consisted of >6.5 billion test results, with 2215 distinct LOINC codes. The model predicted the correct LOINC code in 85% of the unlabeled data and 96% of the labeled data by test frequency. In the subset of labeled data where the original and model-predicted LOINC codes disagreed, the model-predicted LOINC code was correct in 83% of the data by test frequency. Conclusion Using a completely automated process, we are able to assign LOINC codes to unlabeled data with high accuracy. When the model-predicted LOINC code differed from the original LOINC code, the model prediction was correct in the vast majority of cases. This scalable, automated algorithm may improve data quality and interoperability, while substantially reducing the manual effort currently needed to accurately map laboratory data. ER - TY - JOUR T1 - The State of Population Health Surveillance Using Electronic Health Records: A Narrative Review A1 - Paul, Margaret M. A1 - Greene, Carolyn M. A1 - Newton-Dame, Remle A1 - Thorpe, Lorna E. A1 - Perlman, Sharon E. A1 - McVeigh, Katherine H. A1 - Gourevitch, Marc N. Y1 - 2015/06// PB - Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA JF - Population Health Management VL - 18 IS - 3 SP - 209 EP - 216 DO - 10.1089/pop.2014.0093 UR - http://online.liebertpub.com/doi/10.1089/pop.2014.0093 N2 - Abstract Electronic health records (EHRs) are transforming the practice of clinical medicine, but the extent to which they are being harnessed to advance public health goals remains uncertain. Data extracted from integrated EHR networks offer the potential for almost real-time determination of the health status of populations in care, for targeting interventions to vulnerable populations, and for monitoring the impact of such initiatives over time. This is especially true in ambulatory care settings, which are uniquely suited for monitoring population health indicators including risk factors and disease management indicators associated with chronic diseases. As efforts gather steam to integrate health data across delivery systems, large networks of electronic patient information are increasingly emerging. Few of the national population health surveillance systems that rely on EHR data have progressed beyond laying groundwork to launch and maintain EHR-based surveillance, but a limited number of more focus... ER - TY - JOUR T1 - Development and evaluation of an interoperable system based on the semantic web to enhance the management of patients’ tuberculosis data A1 - Pellison, Felipe Carvalho A1 - Lopes Rijo, Rui Pedro Charters A1 - Lima, Vinícius Costa A1 - de Lima, Ricardo Roberto A1 - Cruz Correia, Ricardo João A1 - Alves, Domingos Y1 - 2017/01// PB - Elsevier JF - Procedia Computer Science VL - 121 SP - 791 EP - 796 DO - 10.1016/J.PROCS.2017.11.102 UR - https://www.sciencedirect.com/science/article/pii/S1877050917323049?via%3Dihub L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Pellison et al. - 2017 - Development and evaluation of an interoperable system based on the semantic web to enhance the management of(2).pdf N2 - Tuberculosis (TB), despite all the efforts and progress made in the last decade, continues to be very relevant in Brazil as well as in other Portuguese-speaking countries, so there is the need to join efforts for increasing the effectiveness of the fight against TB. Therefore, the epidemiological surveillance system of TB requires, not only the implementation of basic prevention and care actions, but also the strengthening of the integration between the different health services, programs and levels of care, whose resolvability varies according to financial, technical and human resources, as well as service infrastructure that comprise the network of attention. The deepening and broadening of data management techniques must constantly be carried out to achieve, at a higher level, integration and integrity of the ideal and desirable health care. Then, the goal of this article is to describe the research methods used to develop an information system using systems interoperability techniques based on the Semantic Web paradigm that will contribute to the activities of epidemiological surveillance and the follow-up of TB patients. ER - TY - JOUR T1 - Meaningful integration of data from heterogeneous health services and home environment based on ontology A1 - Peng, C A1 - Goswami, P Y1 - 2019/// JF - Sensors (Switzerland) VL - 19 IS - 8 DO - 10.3390/s19081747 N2 - ©2019 by the authors. Licensee MDPI, Basel, Switzerland. The development of electronic health records, wearable devices, health applications and Internet of Things (IoT)-empowered smart homes is promoting various applications. It also makes health self-management much more feasible, which can partially mitigate one of the challenges that the current healthcare system is facing. Effective and convenient self-management of health requires the collaborative use of health data and home environment data from different services, devices, and even open data on the Web. Although health data interoperability standards including HL7 Fast Healthcare Interoperability Resources (FHIR) and IoT ontology including Semantic Sensor Network (SSN) have been developed and promoted, it is impossible for all the different categories of services to adopt the same standard in the near future. This study presents a method that applies Semantic Web technologies to integrate the health data and home environment data from heterogeneously built services and devices. We propose a Web Ontology Language (OWL)-based integration ontology that models health data from HL7 FHIR standard implemented services, normal Web services and Web of Things (WoT) services and Linked Data together with home environment data from formal ontology-described WoT services. It works on the resource integration layer of the layered integration architecture. An example use case with a prototype implementation shows that the proposed method successfully integrates the health data and home environment data into a resource graph. The integrated data are annotated with semantics and ontological links, which make them machine-understandable and cross-system reusable. ER - TY - JOUR T1 - The caCORE Software Development Kit: streamlining construction of interoperable biomedical information services. A1 - Phillips, Joshua A1 - Chilukuri, Ram A1 - Fragoso, Gilberto A1 - Warzel, Denise A1 - Covitz, Peter A Y1 - 2006/// KW - Information Services KW - Semantics KW - Software PB - BioMed Central JF - BMC medical informatics and decision making VL - 6 SP - 2 EP - 2 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. RESULTS The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for caBIG. CONCLUSION The caCORE SDK substantially lowers the barrier to implementing systems that are syntactically and semantically interoperable by providing workflow and automation tools that standardize and expedite modeling, development, and deployment. It has gained acceptance among developers in the caBIG program, and is expected to provide a common mechanism for creating data service nodes on the data grid that is under development. ER - TY - JOUR T1 - SemanticDB: A semantic Web infrastructure for clinical research and quality reporting A1 - Pierce, C D A1 - Booth, D A1 - Ogbuji, C A1 - Deaton, C A1 - Blackstone, E A1 - Lenat, D Y1 - 2012/// KW - Clinical data KW - Clinical research KW - Electronic medical records KW - Inference KW - Internet KW - Ontology KW - Quality reporting KW - RDF KW - Semantic web KW - article KW - bioinformatics KW - clinical data repository KW - clinical research KW - computer interface KW - computer program KW - electronic medical record KW - factual database KW - health care quality KW - human KW - information processing KW - priority journal KW - semantics JF - Current Bioinformatics VL - 7 IS - 3 SP - 267 EP - 277 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866679963&doi=10.2174%2F157489312802460730&partnerID=40&md5=6964d6956f5c31f3fb02fdbb725d4bb9 N1 - Cited By :6 Export Date: 10 September 2018 References: Blackstone, E.H., Lenat, D.B., Ishwaran, H., Learning what works: Infrastructure required for comparative effectiveness research workshop summary (2011), 123, p. 144. , Washington DC, The National Academy Press In: Olsen L, Grossmann C, McGinnis JM, Eds; Klyne, G., Carroll, J.J., McBride, B., World Wide Web Consortium Resource Description Framework (RDF): Concepts and Abstract Syntax, , http://www.w3.org/TR/rdf-concepts/, Accessed July 22, 2011; Berners-Lee, T., Connolly, D., World Wide Web Consortium Notation3 (N3): A readable RDF syntax, , http://www.w3.org/-TeamSubmission/n3/, Accessed July 22, 2011; The Cyc Knowledge Server, , http://www.cyc.com-/cyc/technology/whatiscyc, Cycorp, Inc, Accessed July 22, 2011; Ontology (information science), , http://en.wikipedia.org/wiki/Ontology_%28information_science%29, Wikipedia. org, Accessed July 22, 2011; Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D., World Wide Web Consortium OWL Web Ontology Language Reference, , http://www.w3.org/TR/owl-ref/, Accessed July 22, 2011; Wood, D., Ogbuji, C., A Role for Semantic Web Technologies in Patient Record Data Collection (2010) Linking Enterprise Data, pp. 241-261. , Springer; Bray, T., Paoli, J., Sperberg-McQueen, M., Maler, E., Yergeau, F., World Wide Web Consortium Extensible Markup Language (XML), , http://www.w3.org/TR/xml/, 1.0 (Fifth Edition), Accessed July 22, 2011; Boyer, J., World Wide Web Consortium XForms 1.1., , http://-www.w3.org/TR/xforms11/, Accessed July 22, 2011; Clark, J., World Wide Web Consortium XSL Transformations (XSLT) Version 1.0, , http://www.w3.org/TR/xslt, Accessed July 22, 2011; A Python library for working with RDF, , http://code.google.com/p/rdflib/, rdflib. net. RDFLib, Accessed July 22, 2011; Prud'hommeaux, E., Seaborne, A., SPARQL Query Language for RDF, , http://www.w3.org/TR/rdf-sparql-query/, Accessed October 29, 2011; Elliott, B., Cheng, E., Thomas-Ogbuji, C., Ozsoyoglu, Z.M., A complete translation of SPARQL into efficient SQL (2009) IDEAS Proceedings, 31, p. 42; Oracle Spatial and Oracle Locator, , http://tinyurl.com/-3lk53ne, Oracle, Inc, Accessed July 22, 2011; Rete Algorithm, , http://en.wikipedia.org/wiki/-Rete_algorithm, Wikipedia. org, Accessed July 22, 2011; The Cyc Knowledge Base(TM), , http://cyc.com/cyc/technology/technology/whatiscyc_dir/whatsincyc, Cycorp, Inc., Accessed July 22, 2011; The Syntax of CycL, , http://www.cyc.com/cycdoc/-ref/cycl-syntax.html, Cycorp, Inc, Accessed July 22, 2011; 4Suite and related projects at SourceForge, , http://foursuite.sourceforge.net/, SourceForge. net, Accessed July 22, 2011; FuXi 1.0: A Python-based, bi-directional logical reasoning system, , http://code.google.com/p/fuxi/, Google, Accessed July 22, 2011; MySQL-Python, , http://mysql-python.sourceforge.net/, SourceForge. net., Accessed July 22, 2011; Exhibit: Publishing Framework for Data-Rich Interactive Web Pages, , http://www.-simile-widgets.org/exhibit/, Massachusetts Institute of Technology, Accessed July 22, 2011; Mozilla Firefox Web Browser, , http://www.-mozilla.com/en-US/firefox/new/, Mozilla Foundation, Accessed July 22, 2011; Callimachus, , http://callimachusproject.-org/(AccessedJuly22,2011); Viaduct(TM), , http://www.bridgeforwardsoftware.com/-viaduct.php, iSoft, Inc, Accessed July 22, 2011; Ogbuji, C., Blackstone, E., Pierce, C., World Wide Web Consortium Case study: A Semantic Web content repository for clinical research, , http://www.w3.org/2001/sw/sweo/public/UseCases/ClevelandClinic/, Accessed July 22, 2011 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Semantic Web technologies offer the potential to revolutionize management of health care data by increasing interoperability and reusability while reducing the need for redundant data collection and storage. From 1998 through 2010, Cleveland Clinic sponsored a project designed to explore and develop this potential. The product of this effort, SemanticDB, is a suite of software tools and knowledge resources built to facilitate the collection, storage and use of the diverse data needed to conduct clinical research and health care quality reporting. SemanticDB consists of three main components: 1) a content repository driven by a meta-model that facilitates collection and integration of data in an XML format and automatically converts the data to RDF; 2) an inference-mediated, natural language query interface designed to identify patients who meet complex inclusion and exclusion criteria; and 3) a data production pipeline that uses inference to generate customized views of the repository content for statistical analysis and reporting. Since 2008, this system has been used by the Cleveland Clinic's Heart and Vascular Institute to support numerous clinical investigations, and in 2009 Cleveland Clinic was certified to submit data produced in this manner to national quality monitoring databases sponsored by the Society of Thoracic Surgeons and the American College of Cardiology. © 2012 Bentham Science Publishers. ER - TY - JOUR T1 - MESCO (MEat Supply Chain Ontology): An ontology for supporting traceability in the meat supply chain A1 - Pizzuti, T A1 - Mirabelli, G A1 - Grasso, G A1 - Paldino, G Y1 - 2017/// KW - Description logic KW - Meat KW - Meat supply chain KW - Ontology KW - Traceability KW - Web ontology language JF - Food Control VL - 72 SP - 123 EP - 133 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994246593&doi=10.1016%2Fj.foodcont.2016.07.038&partnerID=40&md5=599e80b01c3a2976e0818226b83e31c9 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Pizzuti et al. - 2017 - MESCO (MEat Supply Chain Ontology) An ontology for supporting traceability in the meat supply chain.pdf N1 - Cited By :5 Export Date: 10 September 2018 References: Baclawski, K., Kokar, M.M., Waldinger, R., Consistency checking of semantic web ontologies (2002) Lecture Notes in Computer Science, 2342, pp. 454-459; Badia-Melis, R., Mishra, P., Ruiz-García, L., Food traceability: New trends and recent advances. A review (2015) Food Control, 57, pp. 393-401; Bechhofer, S., van Harmelen, F., Hendler, J., McGuinness, D.L., Patel-Schneider, P.F., Stein, L.A., (2004) OWL web ontology language reference, , http://www.w3.org/TR/owl-ref/, W3C Dean Mike Schreiber Guus Retrieved from; Blakeley, C., RDF views of SQL data (declarative SQL schema to RDF mapping) (2007), OpenLink Software; Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Poggi, A., Rodriguez-Muro, M., The MASTRO system for ontology-based data access (2011) Semantic Web Journal, 2 (1), pp. 43-53; Chifi, V.R., Salomie, I., Chifu, E.S., Ontology-enhanced description of traceability services (2007) Presented at the IEEE International Conference on Intelligent Computer Communication and Processing, pp. 1-8. , http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4352135, Retrieved from; De Cindio, B., Longo, F., Mirabelli, G., Pizzuti, T., Modelling a traceability system for a food supply Chain: Standards, technologies and software tools (2011) MAS2011, pp. 488-494. , (Rome, Italy); Feng, J., Fu, Z., Wang, Z., Xu, M., Zhang, X., Development and evaluation on a RFID-based traceability system for cattle/beef quality safety in China (2013) Food Control, 31 (2), pp. 314-325; Fernández-López, M., Gómez-Pérez, A., Juristo, N., Methontology: From ontological art towards ontological engineering (1997), AAAI Technical Report; McGrann, J., Wiseman, H., Animal traceability across national frontiers in the European Union (2001) Rev. Sci. Tech.-Off. Int. Epizoot., 20, pp. 406-419; Golan, E., Krissoff, B., Kuchler, F., Food traceability: One ingredient in a safe and efficient food supply (2004); Golik, W., Dameron, O., Bugeon, J., Fatet, A., Hue, I., Hurtaud, C., ATOL: The multi-species livestock trait ontology (2012) Metadata and semantics research, pp. 289-300. , http://link.springer.com/chapter/10.1007/978-3-642-35233-1_28, Springer Retrieved from; Lavelli, V., High-warranty traceability system in the poultry meat supply chain: A medium-sized enterprise case study (2013) Food Control, 33 (1), pp. 148-156; Liang, W., Cao, J., Fan, Y., Zhu, K., Dai, Q., Modeling and implementation of cattle/beef supply chain traceability using a distributed RFID-based framework in China (2015) PLoS ONE, 10 (10), p. e0139558. , http://doi.org/10.1371/journal.pone.0139558; Parsia, B., Sirin, E., Pellet: An owl dl reasoner (2004) Third international semantic web conference-poster, p. 18. , http://iwayan.info/Research/Ontology/Papers_Research/Reasoner/Parsia_PelletOWLDLReasoner.pdf, Retrieved from; Pizzuti, T., Mirabelli, G., FTTO: An example of food ontology for traceability purpose (2013) IDAACS2013, pp. 281-286. , (Berlin, Germany); Pizzuti, T., Mirabelli, G., The global track & trace system for food: General framework and functioning principles (2015) Journal of Food Engineering, 159, pp. 16-35; Pizzuti, T., Mirabelli, G., Future technology in tracing animals on the food chain (2016) Advances in food traceability techniques and technologies: Improving quality throughout the food chain, , Espiñeira & Santaclara; Pizzuti, T., Mirabelli, G., Goméz-González, F., Sanz-Bobi, M.A., A BPMN general framework for managing traceability in a Food Supply Chain (2012) MAS2012, , (Vienna, Austria); Pizzuti, T., Mirabelli, G., Sanz-Bobi, M.A., Goméz-González, F., Food Track&Trace Ontology for helping the food traceability control (2014) Journal of Food Engineering, 120, pp. 17-30. , January; Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., Rosati, R., Linking data to ontologies (2008) Journal on Data Semantics X, pp. 133-173; Rahmati, S., Julkapli, N.M., Yehye, W.A., Basirun, W.J., Identification of meat origin in food products–A review (2016) Food Control, 68, pp. 379-390; Trojczak, R., Trypuz, R., Gradzki, P., Wierzbicki, J., Wozniak, A., Evaluation of beef production and consumption ontology and presentation of its actual and potential applications (2013) Computer science and information systems (FedCSIS), 2013 federated conference on, pp. 275-278. , http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6644012, IEEE Retrieved from; Zhang, J., Bhatt, T., A guidance document on the best practices in food traceability: Best practices in food traceability (2014) Comprehensive Reviews in Food Science and Food Safety, 13 (5), pp. 1074-1103; Zhang, X., Lv, S., Xu, M., Mu, W., Applying evolutionary prototyping model for eliciting system requirement of meat traceability at agribusiness level (2010) Food Control, 21 (11), pp. 1556-1562 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Traceability plays an important role in the food industry because it is directly connected with food quality and safety. Safety, in fact, can only be guaranteed by following food products along the entire supply chain. In the last years, a series of food safety scandals have invested the meat sector, highlighting the lack of common standards for information encoding and management and the inability to link food products with the elements involved in their transformation process. This paper describes the MEat Supply Chain Ontology (MESCO), an ontology developed for supporting the management of meat traceability along the whole supply chain. In particular, in this paper the authors instantiate MESCO to take the problem of meat traceability from the farmer to the final consumer. The article describes the main features of MESCO, illustrating the different steps followed for its development and some example of application. MESCO has been validated and interrogated through the formulation of several queries expressed in Description Logic (DL), executed using the Pellet reasoner, to deal with different scenarios and problems of traceability. The results show that MESCO is able to represent all the knowledge and information related to the meat traceability domain into a single ontology, enabling interoperability among different systems and allowing for integrating the heterogeneous databases adopted by each actor involved in the supply chain. One of the main advantages in using MESCO is the facility in obtaining essential data, fundamental in case of food outbreak disease, addressing the key issues that makes the job of food safety agents frustrating. © 2016 Elsevier Ltd ER - TY - JOUR T1 - Following Data as it Crosses Borders During the COVID-19 Pandemic A1 - Plasek, J M A1 - Tang, C A1 - Zhu, Y A1 - Huang, Y A1 - Bates, D W Y1 - 2020/// JF - Journal of the American Medical Informatics Association : JAMIA DO - 10.1093/jamia/ocaa063 N2 - ©The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com. Data changes the game in terms of how we respond to pandemics. Global data on disease trajectories and the effectiveness and economic impact of different social distancing measures are essential to facilitate effective local responses to pandemics. COVID-19 data flowing across geographic borders are extremely useful to public health professionals for many purposes such as accelerating the pharmaceutical development pipeline, and for making vital decisions about intensive care unit rooms, where to build temporary hospitals, or where to boost supplies of personal protection equipment, ventilators, or diagnostic tests. Sharing data enables quicker dissemination and validation of pharmaceutical innovations, as well as improved knowledge of what prevention and mitigation measures work. Even if physical borders around the globe are closed, it is crucial that data continues to transparently flow across borders to enable a data economy to thrive which will promote global public health through global cooperation and solidarity. ER - TY - JOUR T1 - 'Real-life' information on pulmonary arterial hypertension: The iPHnet Project A1 - Poscia, R A1 - Ghio, S A1 - D'Alto, M A1 - Vitulo, P A1 - Mulè, M A1 - Albera, C A1 - Parisi, F A1 - Badagliacca, R A1 - Fedele, F A1 - Vizza, C D Y1 - 2014/// KW - Corticotropin-Releasing Hormone KW - Database KW - Databases, Factual KW - Health record KW - Humans KW - Hypertension, Pulmonary KW - Italy KW - Medical Records Systems, Computerized KW - Pulmonary Artery KW - Pulmonary arterial hypertension KW - Registries KW - electronic medical record KW - factual database KW - human KW - register JF - Current Medical Research and Opinion VL - 30 IS - 12 SP - 2409 EP - 2414 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84914166237&doi=10.1185%2F03007995.2014.960514&partnerID=40&md5=316dd9be32feeaaf774a23cfde59eaf3 N1 - Export Date: 10 September 2018 References: Malenfant, S., Margaillan, G., Loehr, J.E., The emergence of new therapeutic targets in pulmonary arterial hypertension: From now to the near future (2013) Expert Rev Respir Med, 7, pp. 43-55; Galiè, N., Ghofrani, A.H., New horizons in pulmonary arterial hypertension therapies (2013) Eur Respir Rev, 22, pp. 503-514; Peacock, A., Pulmonary hypertension (2013) Eur Respir Rev, 22, pp. 20-25; Sutendra, G., Michelakis, E.D., Pulmonary arterial hypertension: Challenges in translational research and a vision for change (2013) Sci Transl Med, 5, p. 208sr5; McGoon, M.D., Benza, R.L., Escribano-Subias, P., Pulmonary arterial hypertension: Epidemiology and registries (2013) J Am Coll Cardiol, 62, pp. D51-D59; Peacock, A.J., Murphy, N.F., McMurray, J.J., An epidemiological study of pulmonary arterial hypertension (2007) Eur Respir J, 30, pp. 104-109; Silverman, S.L., From randomized controlled trials to observational studies (2009) Am J Med, 122, pp. 114-120; Gomberg-Maitland, M., Michelakis, E.D., A global pulmonary arterial hypertension registry: Is it needed? Is it feasible? Pulmonary vascular disease: The global perspective (2010) Chest, 137, pp. 95-101S; Marceglia, S., Mazzola, L., Bonacina, S., A comprehensive e-prescribing model to allow representing, comparing, and analyzing available systems (2013) Methods Inf Med, 52, pp. 199-219; Baptista, R., Meireles, J., Agapito, A., Pulmonary hypertension in portugal: First data from a nationwide registry (2013) Biomed Res Int, 2013, p. 489574; Humbert, M., Update in pulmonary arterial hypertension 2007 (2008) Am J Respir Crit Care Med, 177, pp. 574-579; Humbert, M., Sitbon, O., Chaouat, A., Pulmonary arterial hypertension in france: Results from a national registry (2006) Am J Respir Crit Care Med, 173, pp. 1023-1030; ESC, Galiè, N., Hoeper, M.M., Humbert, M., Guidelines for the diagnosis and treatment of pulmonary hypertension (2009) Eur Respir J, 34, pp. 1219-1263; Badesch, D.B., Raskob, G.E., Elliott, C.G., Pulmonary arterial hypertension: Baseline characteristics from the reveal registry (2010) Chest, 137, pp. 376-387; Escribano-Subias, P., Blanco, I., López-Meseguer, M., Survival in pulmonary hypertension in spain: Insights from the spanish registry (2012) Eur Respir J, 40, pp. 596-603; D'Alonzo, G.E., Barst, R.J., Ayres, S.M., Survival in patients with primary pulmonary hypertension. Results from a national prospective registry (1991) Ann Intern Med, 115, pp. 343-349; Thenappan, T., Shah, S.J., Rich, S., A usa-based registry for pulmonary arterial hypertension: 1982-2006 (2007) Eur Respir J, 30, pp. 1103-1110; Humbert, M., Sitbon, O., Chaouat, A., Survival in patients with idiopathic, familial, and anorexigen-associated pulmonary arterial hypertension in the modern management era (2010) Circulation, 122, pp. 156-163; Benza, R.L., Miller, D.P., Gomberg-Maitland, M., Predicting survival in pulmonary arterial hypertension: Insights from the registry to evaluate early and long-term pulmonary arterial hypertension disease management (reveal) (2010) Circulation, 122, pp. 164-172; Benza, R.L., Gomberg-Maitland, M., Miller, D.P., The reveal registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension (2012) Chest, 141, pp. 354-362; Kane, G.C., Maradit-Kremers, H., Slusser, J.P., Integration of clinical and hemodynamic parameters in the prediction of long-term survival in patients with pulmonary arterial hypertension (2011) Chest, 139, pp. 1285-1293; Frost, A.E., Badesch, D.B., Barst, R.J., The changing picture of patients with pulmonary arterial hypertension in the united states: How reveal differs from historic and non-us contemporary registries (2011) Chest, 139, pp. 128-137; Fuster, V., Steele, P.M., Edwards, W.D., Primary pulmonary hypertension: Natural history and the importance of thrombosis (1984) Circulation, 70, pp. 580-587; Rich, S., Kaufmann, E., Levy, P.S., The effect of high doses of calcium-channel blockers on survival in primary pulmonary hypertension (1992) N Engl J Med, 327, pp. 76-81; Olsson, K.M., Delcroix, M., Ghofrani, H.A., Anticoagulation and survival in pulmonary arterial hypertension: Results from the compera registry (2014) Circulation, 129, pp. 57-65 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: The aim of this study is to present the Italian Pulmonary Hypertension Network (iPHnet) Project, a database used to collect health records on patients with PAH that can also be used for research purposes to retrieve ad hoc information. Results: iPHnet presents various characteristics such as facilitated access, data sharing and interoperability, update, patient's anonymity and data integrity. The system also enables the creation of patients' electronic health records (EHRs), the exportation and personalization of data and the possibility to design clinical report forms (CRFs) and collect information usable in clinical trials. In addition, it is possible to analyze the information present in the registry, creating graphs or other immediately available charts to evaluate the trends of a specific data and perform therapeutic or clinic adjustments. Treatment of data in the iPHnet database complies with FDA requirements, backup and disaster recovery policies and patients' privacy. Conclusions: iPHnet is a flexible tool that integrates the capabilities of an EHR for PAH patients with those of a PAH registry. The ability to retrieve relevant information-although with all the limitations of any registry-based analysis-and to create appropriate CRFs will facilitate the development of prospective and retrospective trials aimed at providing new 'real-life' evidence on PAH. Background: Over the last two decades the development and analysis of a number of registries have enhanced the knowledge of the epidemiology, presentation, natural history, and pathophysiology of pulmonary arterial hypertension (PAH). The understanding of the effectiveness of available treatments has also been greatly improved. However, most of the registries present some methodological issues, such as differences in the classification of patients and presence of confounding factors or missing values, that can impact on the generalizability of the results. © 2014 All rights reserved: reproduction in whole or part not permitted. ER - TY - JOUR T1 - A health analytics semantic ETL service for obesity surveillance A1 - Poulymenopoulou, M A1 - Papakonstantinou, D A1 - Malamateniou, F A1 - Vassilacopoulos, G Y1 - 2015/// KW - Big data KW - Humanism KW - Humanities KW - Humans KW - Obesity KW - Semantics KW - health analytics KW - obesity KW - public health surveillance KW - semantics JF - Studies in Health Technology and Informatics VL - 210 SP - 840 EP - 844 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The increasingly large amount of data produced in healthcare (e.g. collected through health information systems such as electronic medical records - EMRs or collected through novel data sources such as personal health records - PHRs, social media, web resources) enable the creation of detailed records about people's health, sentiments and activities (e.g. physical activity, diet, sleep quality) that can be used in the public health area among others. However, despite the transformative potential of big data in public health surveillance there are several challenges in integrating big data. In this paper, the interoperability challenge is tackled and a semantic Extract Transform Load (ETL) service is proposed that seeks to semantically annotate big data to result into valuable data for analysis. This service is considered as part of a health analytics engine on the cloud that interacts with existing healthcare information exchange networks, like the Integrating the Healthcare Enterprise (IHE), PHRs, sensors, mobile applications, and other web resources to retrieve patient health, behavioral and daily activity data. The semantic ETL service aims at semantically integrating big data for use by analytic mechanisms. An illustrative implementation of the service on big data which is potentially relevant to human obesity, enables using appropriate analytic techniques (e.g. machine learning, text mining) that are expected to assist in identifying patterns and contributing factors (e.g. genetic background, social, environmental) for this social phenomenon and, hence, drive health policy changes and promote healthy behaviors where residents live, work, learn, shop and play. ER - TY - JOUR T1 - Integrating social and behavioral determinants of health into population health analytics: A conceptual framework and suggested road map A1 - Predmore, Z A1 - Hatef, E A1 - Weiner, J P Y1 - 2019/// JF - Population Health Management VL - 22 IS - 6 SP - 488 EP - 494 DO - 10.1089/pop.2018.0151 N2 - ©Copyright 2019, Mary Ann Liebert, Inc., publishers 2019. There is growing recognition that social and behavioral risk factors impact population health outcomes. Interventions that target these risk factors can improve health outcomes. This study presents a review of existing literature and proposes a conceptual framework for the integration of social and behavioral data into population health analytics platforms. The authors describe several use cases for these platforms at the patient, health system, and community levels, and align these use cases with the different types of prevention identified by the Centers for Disease Control and Prevention. They then detail the potential benefits of these use cases for different health system stakeholders and explore currently available and potential future sources of social and behavioral domains data. Also noted are several potential roadblocks for these analytic platforms, including limited data interoperability, expense of data acquisition, and a lack of standardized technical terminology for socio-behavioral factors. ER - TY - JOUR T1 - The development of an international, common, prospective, cardiology database. Report of the joint G8 Cardio-Associazione Nazionale Medici Cardiologi Ospedalieri (ANMCO)-Societéé Française de Cardiologie (SFC) database committee A1 - Pristipino, C A1 - Danchin, N A1 - Lablanche, J M A1 - Komajda, M A1 - Tubaro, M A1 - Maseri, A A1 - Cianflone, D Y1 - 2009/// KW - Cardiology KW - Database Management Systems KW - Europe KW - France KW - Heart Diseases KW - Humans KW - International Cooperation KW - Italy KW - Prevention KW - Reproducibility of Results KW - Societies, Medical KW - United States KW - article KW - cardiology KW - classification KW - clinical trial KW - comparative study KW - conference paper KW - consensus development KW - data base KW - database KW - health care policy KW - heart disease KW - human KW - international cooperation KW - medical society KW - multicenter study KW - organization and management KW - patient care KW - priority journal KW - reproducibility KW - standardization JF - Acute Cardiac Care VL - 11 IS - 2 SP - 113 EP - 120 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-70249094370&doi=10.1080%2F17482940802699213&partnerID=40&md5=966b7000f6abf6bc7b4fe467532bfff4 N1 - Export Date: 10 September 2018 References: Loan, E.M., Yusuf, S., Emerging approaches in preventing cardiovascular disease (1999) British Medical Journal, 318 (7194), pp. 1337-1341; Gibbons, R.J., Smith, S., Antman, E., American College of Cardiology/American Heart Association clinical practice guidelines: Part I. Where do they come from? (2003) Circulation, 107 (23), pp. 2979-2986. , DOI 10.1161/01.CIR.0000063682.20730.A5; Canto, J.G., Kiefe, C.I., Williams, D., Barron, H.V., Rogers, W.J., Comparison of outcomes research with clinical trials using preexisting data (1999) American Journal of Cardiology, 84 (8), pp. 923-927. , DOI 10.1016/S0002-9149(99)00467-1, PII S0002914999004671; Danchin, N., Vaur, L., Genes, N., Etienne, S., Angioi, M., Ferrieres, J., Cambou, J.-P., Treatment of acute myocardial infarction by primary coronary angioplasty or intravenous thrombolysis in the 'real world'. One-year results from a nationwide French survey (1999) Circulation, 99 (20), pp. 2639-2644; Sharpe, N., Clinical trials and the real world: Selection bias and generalisability of trial results (2002) Cardiovascular Drugs and Therapy, 16 (1), pp. 75-77. , DOI 10.1023/A:1015327801114; Victora, C.G., Habicht, J.-P., Bryce, J., Evidence-based public health: Moving beyond randomized trials (2004) American Journal of Public Health, 94 (3), pp. 400-405; Baltussen, R., Leidl, R., Ament, A., Real world designs in economic evaluation: Bridging the gap between clinical research and policy-making (1999) PharmacoEconomics, 16 (I5), pp. 449-458. , DOI 10.2165/00019053-199916050-00003; Brindis, R.G., Fitzgerald, S., Anderson, H.V., The American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR): Building a national clinical data repository (2001) J Am Coll Cardiol, 37, pp. 2240-5; Welke, K.F., Ferguson Jr., T.B., Coombs, L.P., Dokholyan, R.S., Murray, C.J., Schrader, M.A., Peterson, E.D., Validity of the Society of Thoracic Surgeons National Adult Cardiac Surgery Database (2004) Annals of Thoracic Surgery, 77 (4), pp. 1137-1139. , DOI 10.1016/j.athoracsur.2003.07.030, PII S0003497503018629; Shaw, R.E., Anderson, H.V., Brindis, R.G., Krone, R.J., Klein, L.W., McKay, C.R., Block, P.C., Weintraub, W.S., Development of a risk adjustment mortality model using the American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR) experience: 1998-2000 (2002) Journal of the American College of Cardiology, 39 (7), pp. 1104-1112. , DOI 10.1016/S0735-1097(02)01731-X, PII S073510970201731X; Klein, L.W., Block, P., Brindis, R.G., McKay, C.R., McCallister, B.D., Wolk, M., Weintraub, W., Percutaneous coronary interventions in octogenarians in the American College of Cardiology-National Cardiovascular Data Registry: Development of a nomogram predictive of in-hospital mortality (2002) Journal of the American College of Cardiology, 40 (3), pp. 394-402. , DOI 10.1016/S0735-1097(02)01992-7, PII S0735109702019927; Shaw, R.E., Anderson, H.V., Brindis, R.G., Krone, R.J., Klein, L.W., McKay, C.R., Block, P.C., Weintraub, W.S., Updated Risk Adjustment Mortality Model Using the Complete 1.1 Dataset from the American College of Cardiology National Cardiovascular Data Registry (ACC - NCDR) (2003) Journal of Invasive Cardiology, 15 (10), pp. 578-580; Klein, L.W., Shaw, R.E., Krone, R.J., Brindis, R.G., Anderson, H.V., Block, P.C., McKay, C.R., Weintraub, W.S., Mortality after emergent percutaneous coronary intervention in cardiogenic shock secondary to acute myocardial infarction and usefulness of a mortality prediction model (2005) American Journal of Cardiology, 96 (1), pp. 35-41. , DOI 10.1016/j.amjcard.2005.02.040, PII S0002914905005746; Maseri, A., The fundamental role of clinical research (2000) Ital Heart J, 1, pp. 13-6; Tunstall-Pedoe, H., Kuulasmaa, K., Mahonen, M., Tolonen, H., Ruokokoski, E., Amouyel, P., Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA Project populations (1999) Lancet, 353 (9164), pp. 1547-1557. , DOI 10.1016/S0140-6736(99)04021-0; Sekikawa, A., Satoh, T., Hayakawa, T., Coronary heart disease mortality among men aged 35-44 years by prefecture in Japan in 1995-1999 compared with that among white men aged 35-44 by state in the United States in 1995-1998: Vital statistics data in recent birth cohort (2001) Jpn Circ J., 65, pp. 887-92; Ezzati, M., How can cross-country research on health risks strengthen interventions? Lessons from INTERHEART (2004) Lancet, 364 (9438), pp. 912-914. , DOI 10.1016/S0140-6736(04)17035-9, PII S0140673604170359; Blanchard, D., Chevalier, B., Danchin, N., Groupe Atherome et Cardiologie interventionnelle de la Societe francaise de cardiologie. National observational study of diagnostic and interventional cardiac catheterization by the French Society of Cardiology: List and definition of basic data (2002) Arch Mal Coeur Vaiss, 95, pp. 843-9; Demolombe, R., Database validity and completeness: Another approach and its formalisation in modal logick (1999) Proceedings of the 6th International Workshop on Knowledge Representation Meets Data Bases, , In: , eds. E. Franconi and M. Kifer, editors; Flynn, M.R., Barrett, C., Cosio, F.G., Gitt, A.K., Wallentin, L., Kearney, P., Lonergan, M., Simoons, M.L., The Cardiology Audit and Registration Data Standards (CARDS), European data standards for clinical cardiology practice (2005) European Heart Journal, 26 (3), pp. 308-313. , DOI 10.1093/eurheartj/ehi079 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: Sharing and comparing health data at the international level is made difficult by heterogeneity in real world databases. Aim: Our primary objective was to field-test the implementation of the first common database developed conjointly by different national cardiological societies. Methods: Based upon G8-Cardio feasibility projects, the Italian Society of Hospital Cardiologists and the French Society of Cardiology joined together to standardize a cardiological, patient-oriented database, created by means of consensus agreement for sharing data in a common server. Quantification of standardization was obtained by analysing each dataset according to the possibility of merging corresponding fields. Data merging from national centres was completed in the common server and after proper data integration in the common database; a comparison was performed between French and Italian populations. Results: Standardization of contents allowed for 89% overall interoperability (merged fields) to be achieved with only 11% divergent fields. All (100%) merged homogeneous data on the first 2717 patients from peripheral centres were selected consecutively from the common database and analysed successfully. Relevant differences between the two populations were outlined. Conclusions: The international standardization and sharing/merging of databases is feasible. This model opens the way to important applications in internationally shared health care policies. © 2009 Informa UK Ltd All rights reserved. ER - TY - JOUR T1 - Big data hurdles in precision medicine and precision public health A1 - Prosperi, M A1 - Min, J S A1 - Bian, J A1 - Modave, F Y1 - 2018/// JF - BMC Medical Informatics and Decision Making VL - 18 IS - 1 DO - 10.1186/s12911-018-0719-2 N2 - ©2018 The Author(s). Background: Nowadays, trendy research in biomedical sciences juxtaposes the term 'precision' to medicine and public health with companion words like big data, data science, and deep learning. Technological advancements permit the collection and merging of large heterogeneous datasets from different sources, from genome sequences to social media posts or from electronic health records to wearables. Additionally, complex algorithms supported by high-performance computing allow one to transform these large datasets into knowledge. Despite such progress, many barriers still exist against achieving precision medicine and precision public health interventions for the benefit of the individual and the population. Main body: The present work focuses on analyzing both the technical and societal hurdles related to the development of prediction models of health risks, diagnoses and outcomes from integrated biomedical databases. Methodological challenges that need to be addressed include improving semantics of study designs: medical record data are inherently biased, and even the most advanced deep learning's denoising autoencoders cannot overcome the bias if not handled a priori by design. Societal challenges to face include evaluation of ethically actionable risk factors at the individual and population level; for instance, usage of gender, race, or ethnicity as risk modifiers, not as biological variables, could be replaced by modifiable environmental proxies such as lifestyle and dietary habits, household income, or access to educational resources. Conclusions: Data science for precision medicine and public health warrants an informatics-oriented formalization of the study design and interoperability throughout all levels of the knowledge inference process, from the research semantics, to model development, and ultimately to implementation. ER - TY - JOUR T1 - Coding and interoperability standards in eSalud: Projection evaluation amIHEALTH | Estándares de codificación e interoperabilidad en esalud: Evaluación del proyecto amIHEALTH A1 - Quiel, Y C A1 - Saavedra, A A1 - Villarreal, V Y1 - 2019/// JF - Revista Cubana de Informacion en Ciencias de la Salud VL - 30 IS - 3 DO - 10.36512/rcics.v30i3.1351 N2 - ©2019, Centro Nacional de Informacion de Ciencias Medicas. All rights reserved. In the health area, interoperability in information and communication technologies (TIC´s) is the ability of information systems to communicate, exchange data and use them in a health system. Interoperability standards in the health sector have created a parallel boom to the development of information systems, web and mobile applications, increasing the quality of assistance, experience and safety of the user or patient by allowing access to their clinical personal data from any point without exposure to risks of such information. This article describes the interoperability standards from the use in messaging, terminology and documentation as a fundamental point for the development of information systems in general, similarly presents aspects for the safety of patient data, users of such systems. Each one of the interoperability standards is individually broken down, so that one can know which one to use in a respective case. At the end of the writing, we carried out a general evaluation of the AmIHEALTH project, which allows for the control and monitoring of health data, using the Fast Healthcare Interoperability Resources standard as a basis for the exchange of user data on a Web platform together with a mobile application, without putting such data at risk. ER - TY - JOUR T1 - Leveraging electronic health records for clinical research A1 - Raman, S R A1 - Curtis, L H A1 - Temple, R A1 - Andersson, T A1 - Ezekowitz, J A1 - Ford, I A1 - James, S A1 - Marsolo, K A1 - Mirhaji, P A1 - Rocca, M A1 - Peterson, E D A1 - Hernandez, A F Y1 - 2018/// JF - American Heart Journal VL - 202 SP - 13 EP - 19 DO - 10.1016/j.ahj.2018.04.015 N2 - ©2018 Elsevier, Inc. Electronic health records (EHRs) can be a major tool in the quest to decrease costs and timelines of clinical trial research, generate better evidence for clinical decision making, and advance health care. Over the past decade, EHRs have increasingly offered opportunities to speed up, streamline, and enhance clinical research. EHRs offer a wide range of possible uses in clinical trials, including assisting with prestudy feasibility assessment, patient recruitment, and data capture in care delivery. To fully appreciate these opportunities, health care stakeholders must come together to face critical challenges in leveraging EHR data, including data quality/completeness, information security, stakeholder engagement, and increasing the scale of research infrastructure and related governance. Leaders from academia, government, industry, and professional societies representing patient, provider, researcher, industry, and regulator perspectives convened the Leveraging EHR for Clinical Research Now! Think Tank in Washington, DC (February 18-19, 2016), to identify barriers to using EHRs in clinical research and to generate potential solutions. Think tank members identified a broad range of issues surrounding the use of EHRs in research and proposed a variety of solutions. Recognizing the challenges, the participants identified the urgent need to look more deeply at previous efforts to use these data, share lessons learned, and develop a multidisciplinary agenda for best practices for using EHRs in clinical research. We report the proceedings from this think tank meeting in the following paper. ER - TY - JOUR T1 - Data standards for interoperability of care team information to support care coordination of complex pediatric patients A1 - Ranade-Kharkar, P A1 - Narus, S P A1 - Anderson, G L A1 - Conway, T A1 - Del Fiol, G Y1 - 2018/// JF - Journal of Biomedical Informatics VL - 85 SP - 1 EP - 9 DO - 10.1016/j.jbi.2018.07.009 N2 - ©2018 Elsevier Inc. Objective: Seamless access to information about the individuals and organizations involved in the care of a specific patient (“care teams”) is crucial to effective and efficient care coordination. This is especially true for vulnerable and complex patient populations such as pediatric patients with special needs. Despite wide adoption of electronic health records (EHR), current EHR systems do not adequately support the visualization and management of care teams within and across health care organizations. Electronic health information exchange has the potential to address this issue. In the present study, we assessed the adequacy of available health information exchange data standards to support the information needs related to care coordination of complex pediatric patients. Methods: We derived data elements from the information needs of clinicians and parents to support patient care teams; and mapped them to data elements in the Health Level Seven (HL7) Consolidated Clinical Document Architecture (C-CDA) standard and in the HL7 Fast Healthcare Interoperability Resources (FHIR) standard. We also identified additional C-CDA data elements and FHIR resources that include patients' care team members. Results: Information about care team members involved in patient care is generally well-represented in the C-CDA and FHIR specifications. However, there are gaps related to patients' non-clinical events and care team actions. In addition, there is no single place to find information about care team members; rather, information about practitioners and organizations may be available in several different types of C-CDA data elements and FHIR resources. Conclusion: Through standards-based electronic health information exchange, it appears to be feasible to build patient care team representations irrespective of the location of patient care. In order to gather care team information across disparate systems, exchange of multiple C-CDA documents and/or execution of multiple FHIR queries will be necessary. This approach has the potential to enable comprehensive patient care team views that may help improve care coordination. ER - TY - CONF T1 - An informal method for identifying standards to enable meaningful exchange of public health records A1 - Rao, R R A1 - Makkithaya, K Y1 - 2013/// KW - Electronic health record KW - Health care providers KW - Health records KW - Hospitals KW - Information science KW - Interoperability KW - Maternal healths KW - Meaningful use KW - Medical conditions KW - Primary healthcare KW - Public health KW - Public health informatics KW - Standards KW - electronic health records KW - interoperability KW - maternal health KW - public health informatics KW - standards SP - 2037 EP - 2042 N1 - Cited By :2 Export Date: 10 September 2018 References: Kukafka, R., Ancker, J.S., Chan, C., Chelico, J., Khan, S., Mortoti, S., Natarajan, K., Stephens, K., Redesigning electronic health record systems to support public health (2007) Journal of Biomedical Informatics, 40, pp. 398-409. , July; Koppar, A.R., Sridhar, V., A workflow solution for electronic health records to improve healthcare delivery efficiency in rural india (2009) International Conference on EHealth, Telemedicine, and Social Medicine, Cancun, ETELEMED '09., pp. 227-232. , Feb; Lewis, G.A., Morris, E., Simanta, S., Wrage, L., Why standards are not enough to guarantee end-to-end interoperability (2008) Seventh International Conference on Composition-Based Software Systems, pp. 164-173. , Madrid, ICCBSS; Zhang, Y., Xu, Y., Shang, L., Rao, K., An investigation into health informatics and related standards in China (2007) International Journal of Medical Informatics, 76, pp. 614-620; Bouhaddou, O., Cromwell, T., Davis, M., Maulden, S., Hsing, N., Carlson, D., Cockle, J., Fischetti, L., Translating standards into practice: Experience and lessons learned at the department of veterans affairs (2012) Journal of Biomedical Informatics, 45, pp. 813-823; Sartipi, K., Yarmand, M.H., Standard-based Data and Service Interoperability in eHealth Systems (2008) IEEE International Conference on Software Maintenance, pp. 187-196. , Beijing, ICSM, Sept. 2008; Kim, H.S., Tran, T., Cho, H., A clinical document architecture (CDA) to generate clinical documents within a hospital information system for e-healthcare services (2006) The Sixth IEEE International Conference on Computer and Information Technology, pp. 254-254. , Seoul, CIT'06, Sept; Gaion, S., Mininel, S., Vatta, F., Ukovich, W., Design of a domain model for clinical engineering within the hl7 reference information model (2010) IEEE Workshop on Health Care Management, pp. 1-6. , Venice, WHCM, Feb; http://www.hl7.org/index.cfm, Health Level Seven International, [ May 2013]UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891948029&doi=10.1109%2fICACCI.2013.6637495&partnerID=40&md5=8509512ebafc5c7d1c0e52e9602dff3a RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The key challenges in the area of public health informatics are, the identification of relevant health data sets, its representation and meaningful use of the information for decision making. To make effective use of data represented in Public Health Records, the data needs to be 'seamlessly' shared or be interoperable among health care providers. It is believed that adoption of health care standards will help achieve interoperability. However, analyzing and identifying the standard most suitable for the organization is not a trivial task. The authors propose a simple, informal method to identify the appropriate standard, based on requirements, to achieve interoperability. The method is applied to a real world case study of a Primary Health Care provider in India. A scenario, where an expecting mother needs to be referred to the hospital for a pregnancy related medical condition is considered. The authors model data, analyze and identify standards relevant for interoperable transfer of maternal health information between public health centres and hospitals. © 2013 IEEE. ER - TY - CONF T1 - Ontology based semantic representation for Public Health data integration A1 - Rao, R R A1 - Makkithaya, K A1 - Gupta, N Y1 - 2014/// KW - Data integration KW - Data representations KW - Electronic health record KW - Health care KW - Health care providers KW - Healthcare facility KW - Knowledge based systems KW - Medical terminologies KW - Ontology KW - Ontology evaluation KW - Ontology evaluations KW - Patient treatment KW - Public health KW - Records management KW - Semantic representation KW - Semantics KW - Terminology KW - Unique patient identifiers SP - 357 EP - 362 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949922167&doi=10.1109%2FIC3I.2014.7019701&partnerID=40&md5=8c1977c55f9d733c2b3909b8a35b2863 N1 - Cited By :1 Export Date: 10 September 2018 References: http://www.himss.org/files/HIMSSorg/content/files/Code%20180%20MITRE%20Key%20Components%20of%20an%20EHR.pdf, Electronic Health Records Overview, [September 1st, 2014]; Hayrinen, K., Saranto, K., Nykanen, P., Definition, structure, content, use and impacts of electronic health records: A review of the research literature (2008) International Journal of Medical Informatics, 7, pp. 291-304. , May; Kukafka, R., Ancker, J.S., Chan, C., Chelico, J., Khan, S., Mortoti, S., Natarajan, K., Stephens, K., Redesigning electronic health record systems to support public health (2007) Journal of Biomedical Informatics, 40, pp. 398-409. , July; Lenz, R., Beyer, M., Kuhn, K.A., Semantic integration in healthcare networks (2007) International Journal of Medical Informatics, 76, pp. 201-207; Lasierr, N., Alesanco, A., Guillén, S., García, J., A three stage ontologydriven solution to provide personalized care to chronic patients at home (2013) Journal of Biomedical Informatics, 46, pp. 516-529; Pathak, J., Kiefer, R.C., Chute, C.G., Applying linked data principles to represent patient-s electronic health records at mayo clinic: A case report (2012) Proc. 2nd ACM SIGHIT International Health Informatics Symposium; Alexander, Methods in biomedical ontology (2006) Journal of Biomedical Informatics, 39, pp. 252-266; Liaw, S.T., Rahimi, A., Ray, P., Taggart, J., Dennis, S., De Lusignan, S., Jalaludina, B., Talaei-Khoei, A., Towards an ontology for data quality in integrated chronic disease management: A realist review of the literature (2013) International Journal of Medical Informatics, 82, pp. 10-24; Dieng-Kuntz, R., Minier, D., Ružicka, M., Corby, F., Corby, O., Alamarguy, L., Building and using a medical ontology for knowledge management and cooperative work in a health care network (2006) Computers in Biology and Medicine, 36, pp. 871-892; http://protege.stanford.edu/publications/ontology_development/ontology101.pdf, Ontology 101, [September 1st 2014]; Astrova, I.B., Korda, N., Kalja, A., Rule-based transformation of SQL relational databases to OWL ontologies (2007) Proc. 2nd International Conference on Metadata & Semantics Research; Hlomani, H., Stacey, D., Approaches, methods, metrics, measures, and subjectivity in ontology evaluation: A survey Semantic Web-Interoperability, Usability, Applicability An IOS Press Journal, in Press; Tartir, S., Arpinar, I.B., Sheth, A.P., Ontology evaluation and validation (2010) Theory and Applications of Ontology: Computer Applications, pp. 115-130; Tartir, S., Arpinar, B.I., Ontology evaluation and ranking using ontoqa (2007) Proc. International Conference on Semantic Computing, pp. 185-192; Gangemi, A., Catenacci, C., Ciaramita, M., Lehmann, J., (2005) A Theoretical Framework for Ontology Evaluation and Validation''; Electronic Health Record Standards for India, , http://www.nhp.gov.in/electronic-health-record-standards, [1st Oct 2014]; Bonacina, S., Marceglia, S., Bertoldi, M., Pinciroli, F., Modelling, designing, and implementing a family-based health record prototype (2010) Computers in Biology and Medicine, 40, pp. 580-590. , April RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Many health care providers have adopted Electronic Health Records to represent patient's health conditions. A patient visits many health care facilities like hospitals, private practices or primary health care centres for treatment of different ailments. There is a need to integrate the patient's health data from various sources, to provide a comprehensive view of the patient's health status. This data integration has to be seamless and unaffected by technology issues related to the data representation or exchange. The authors modeled data requirements and designed a Public Health Ontology to represent domain knowledge. The relational health data was mapped into instances of the Public Health Ontology to form a knowledge base of health records. The quality of the ontology and the knowledge base was analyzed using a metric based approach. The semantic representation enables interoperability and results prove that the knowledge base is rich in detail and diversity. The Public Health Ontology uses standardized medical terminology and unique patient identifiers to enable data integration which can enable a complete new level of reasoning over health data. However the public health knowledge base is fairly isolated and it needs to be connected to well-known ontology for meaningful use of the public health knowledge base. © 2014 IEEE. ER - TY - JOUR T1 - A minimal e-referral for meaningful share of maternal health information in public health scenarios A1 - Rao, R R A1 - Makkithaya, K A1 - Kamath, V G A1 - Cordeiro, R Y1 - 2015/// KW - E-referral KW - Electronic healthcare KW - HISs KW - Health information systems KW - Humanism KW - Humanities KW - Humans KW - Interoperability KW - Maternal Welfare KW - Pregnancy KW - Public health informatics KW - Referral and Consultation KW - female KW - health center KW - hospital information system KW - human KW - human experiment KW - markup language KW - maternal welfare KW - patient information KW - patient referral KW - pregnancy KW - public health KW - quantitative study JF - International Journal of Electronic Healthcare VL - 8 IS - 2 SP - 142 EP - 162 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962262817&doi=10.1504%2FIJEH.2015.075328&partnerID=40&md5=5b9fb339063a1a40de6e248884234d1d N1 - Export Date: 10 September 2018 References: Bondale, N., Kimbahune, S., Pande, A., mHEALTHPHC: An ICT tool for primary healthcare in India (2013) IEEE Technology and Society Magazine, 32 (3), pp. 31-38; Cannataro, M., Talia, D., Tradigo, G., Trunfio, P., Veltri, P., SIGMCC: A system for sharing meta patient records in a peer-to-peer environment (2008) Future Generation Computer Systems, 24 (3), pp. 222-234; Chatfield, A., Javetski, G., Lesh, N., (2013) CommCare Evidence Base, , https://confluence.dimagi.com/display/commcarepublic/CommCare+Evidence+Base, (Accessed 25 June, 2015); DeRenzi, B., Sims, C., Jackson, J., Borriello, G., Lesh, N., A framework for case-based community health information systems (2011) GHTC: Proceedings of the 2011 IEEE Conference on Global Humanitarian Technology Conference, pp. 377-382. , Seattle, WA; Dunning, W.E., Lewis, A.M., Malhotra, S., Nicholson, T.S., Wiygul, A.B., Tawney, B.E., Bennett, R.M., Design and development of a medical specialist referral system for the indigent population in Richmond (2005) 2005 IEEE Systems and Information Engineering Design Symposium, pp. 205-214; Ferrari, S., Wyse, P.H., Hu, Y., Analysis of time cost for alternatives to enhance efficiency within the medical emergency referral system in Alberta (2010) CCECE: Proceedings of the 2010 23rd Canadian Conference on Electrical and Computer Engineering, pp. 2-5. , Calgary, AB; Gainer, A., Roth, M., Strong, P., Davis, J., A standards-based open source application to gather health assessment data in developing countries (2012) GHTC: Proceedings of the 2012 IEEE Global Humanitarian Technology Conference, pp. 293-298. , Seattle, WA; Ginsburg, M., Pediatric electronic health record interface design: The PedOne system (2007) Proceedings of the 40th Annual Hawaii International Conference on System Sciences, p. 139. , Waikoloa, HI; Heimly, V., (2009) Electronic Referrals in Healthcare: A Review, , Medical Informatics in a United and Healthy Europe; Heitmann, K.U., Schweiger, R., Dudeck, J., Discharge and referral data exchange using global Standards - The SCIPHOX project in Germany (2003) International Journal of Medical Informatics, 70 (2-3), pp. 195-203; Huang, X.W., Liou, D., Implementation of an electronic emergency referral document system (2010) ICETC: Proceedings of the 2010 2nd International Conference on Education Technology and Computer, 2, pp. 93-96; Hysong, S.J., Esquivel, A., Sittig, D.F., Paul, L.A., Espadas, D., Singh, S., Singh, H., (2011) Towards Successful Coordination of Electronic Health Record Based-Referrals: A Qualitative Analysis, , http://www.implementationscience.com/content/6/1/84, (Accessed 25 June, 2015); Koong, K.S., Ngafeeson, M.N., Liu, L.C., Meaningful use and meaningful curricula: A survey of health informatics programmes in the USA (2012) Int. J. Electronic Healthcare, 7 (1), pp. 1-18; Koppar, A.R., Kshema - A unified healthcare management solution for improving efficiency of the healthcare delivery system in rural India (2009) ICM: Proceedings of the 2009 International Conference on Microelectronics, pp. 132-137. , Marrakech; Koppar, A.R., Sridhar, V., Workflow solution for electronic health records to improve healthcare delivery efficiency in rural India (2009) Proceedings of the International Conference on EHealth, Telemedicine, and Social Medicine, pp. 227-232. , Cancun; Kukafka, R., Ancker, J., Chan, C., Chelico, J., Khan, S., Mortoti, S., Natarajan, K., Stephens, K., Redesigning electronic health record systems to support public health (2007) Journal of Biomedical Informatics, 40, pp. 398-409; Lenz, R., Beyer, M., Kuhn, K., Semantic integration in healthcare networks (2012) International Journal of Medical Informatics, 76, pp. 201-207; Liu, C.T., Long, A., Li, Y., Tsai, K., Kuo, H., Sharing patient care records over the world wide web (2001) International Journal of Medical Informatics, 61, pp. 189-205; Masseroli, M., Marchente, M., X-PAT: A multiplatform patient referral data management system for small healthcare institution requirements (2008) IEEE Transactions on Information Technology in Biomedicine, 12 (4), pp. 424-432; Mondal, P., Desai, P., Ghosh, S.K., Mukherjee, J., An efficient SMS-based framework for public health surveillance (2013) PHT: Proceedings of the 2013 IEEE Point-of-Care Healthcare Technologies, pp. 244-247. , Bangalore; Mukherjee, C., Gupta, K., Nallusamy, R., A system to provide primary maternity healthcare services in developing countries (2012) SRII: Proceedings of the 2012 Annual SRII Global Conference, pp. 24-27. , San Jose, CA; Mykkanen, J.A., Tuomainen, M.P., An evaluation and selection framework for interoperability standards (2008) Information and Software Technology, 50 (3), pp. 176-197; Rao, R.R., Makkithaya, K., An informal method for identifying standards to enable meaningful exchange of public health records (2013) International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013, pp. 2037-2042. , 22-25 August, Mysore; Rassinoux, A.N., Lovis, C., Baud, R., Geissbuhler, A., XML as standard for communicating in a document based electronic patient record: A 3 years experiment (2003) International Journal of Medical Informatics, 70, pp. 109-115; Regnier, V., (2014) Post Implementation Benefit Evaluation Report EReferral Service, , https://www.infoway-inforoute.ca/en/component/edocman/resources/reports/benefits-evaluation/2078-canadian-dental-association-post-implementation-benefits-evaluation-report, (Accessed 25 June, 2014); Routledge, N., Bird, L., Goodchild, A., UML and XML schema (2002) Proceedings of the 13th Australasian Database Conference, pp. 157-166. , Melbourne, Victoria, Australia; Schweiger, R., Brumhard, M., Hoelzer, S., Dudeck, J., Implementing health care systems using XML standards (2005) International Journal of Medical Informatics, 74, pp. 267-277; Sittig, D.F., Gandhi, T.K., Franklin, M., Turetsky, M., Sussman, A.J., Fairchild, D.G., Bates, D.W., Teich, J.M., A computer-based outpatient clinical referral system (1999) International Journal of Medical Informatics, 55 (2), pp. 149-158; Sudhamony, S., Nandakumar, K., Binu, P.J., Niwas, S.I., Telemedicine and tele-health services for cancer-care delivery in India (2008) IET Communications, 2 (2), pp. 231-236; Vittorini, P., Tarquinio, A., Orio, F., XML technologies for the Omaha system: A data model, a Java tool and several case studies supporting home healthcare (2009) Computer Methods and Programs in Biomedicine, 93 (3), pp. 297-312; Waidyanatha, N., Sampath, C., Dubrawski, A., Sabhnani, M., Chen, L., T-Cube web interface as a tool for detecting disease outbreaks in real-time: A pilot in India and Sri Lanka (2010) RIVF: Proceedings of the 2010 IEEE RIVF International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, pp. 1-4. , Hanoi; Woolman, P.S., XML for electronic clinical communications in Scotland (2001) International Journal of Medical Informatics, 64 (2), pp. 379-383; Electronic Health for India Helpdesk, , http://www.nhp.gov.in/data-privacy-and-security, (Accessed 25 June, 2015); Levels of Information Systems Interoperability (LISI), , http://www.eng.auburn.edu/~hamilton/security/DODAF/LISI.pdf, (Accessed 1 January, 2015) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Primary health centres (PHCs) across India provide antenatal, delivery and postnatal healthcare to expecting mothers. In case the expecting mother suffers from a pregnancy-related medical condition that cannot be treated at the PHC, she is referred to the nearest specialist or secondary hospital. The objective of this paper is to present a minimal, affordable and interoperable extensible markup language (XML)-based electronic referral (e-referral) prototype. The e-referral system transfers patient information from the PHC to a specialist at any hospital, for pregnancy-related medical problems. A subject matter expert (SME) panel was formed to identify the minimal dataset and an optimal format for e-referrals in the maternal use case. The data quality of the proposed e-referral information was measured. The e-referral data structures were proven to be complete. The interoperability level achieved by the e-referral prototype was quantified. The minimal e-referral is human processable or syntactically interoperable. The XML-based e-referral data can be very easily integrated with existing hospital information systems. Copyright © 2015 Inderscience Enterprises Ltd. ER - TY - JOUR T1 - Representation of rare diseases in health information systems: The orphanet approach to serve a wide range of end users A1 - Rath, A A1 - Olry, A A1 - Dhombres, F A1 - Brandt, M M A1 - Urbero, B A1 - Ayme, S Y1 - 2012/// KW - Classification KW - Computational Biology KW - Databases, Factual KW - Drug Industry KW - Health Information Systems KW - Humans KW - Information Dissemination KW - Information Systems KW - International Classification of Diseases KW - Interoperability KW - Nosology KW - Online Systems KW - Ontology KW - Rare Diseases KW - Rare diseases KW - Relational database KW - Terminology as Topic KW - article KW - classification KW - congenital adrenal hyperplasia KW - disease classification KW - factual database KW - human KW - information dissemination KW - medical information system KW - medical terminology KW - nomenclature KW - online system KW - orphan drug KW - priority journal KW - rare disease KW - reference database KW - semantics KW - standard JF - Human Mutation VL - 33 IS - 5 SP - 803 EP - 808 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864358886&doi=10.1002%2Fhumu.22078&partnerID=40&md5=bee0ddb3cc9a0489b3450653cfe04c67 N1 - Cited By :106 Export Date: 10 September 2018 References: Amberger, J., Bocchini, C., Hamosh, A., A new face and new challenges for online Mendelian inheritance in man (OMIM) (2011) Hum Mutat, 32, pp. 564-567; Ayme, S., Urbero, B., Oziel, D., Lecouturier, E., Biscarat, A., Information on rare diseases: the Orphanet project (1998) Rev Med Interne, 19, pp. 376-377; Blomberg, N., Ecker, G., Kidd, R., Mons, B., Williams-Jones, B., Knowledge driven discovery goes semantic (2011) Eur Fed Med Chem Yearbook, pp. 39-43; Bodenreider, O., Biomedical ontologies in action: role in knowledgemanagement, data integration and decision support (2008) Yearb Med Inform, pp. 67-79; Dhombres, F., Vandenbussche, P-Y., Rath, A., Olry, A., Hanauer, M., Urbero, B., Charlet, J., Onto Orpha: an ontology to support edition and audit of rare diseases knowledge in Orphanet (2011) Proceedings of the 2nd International Conference on Biomedical Ontology (ICBO-2011), pp. 241-243. , Buffalo, NY, USA: Olivier Bodenreider, Maryann E. Martone, Alan Ruttenberg (eds.); Landais, P., Messiaen, C., Rath, A., Le Mignot, L., Dufour, E., Ben Said, M., Jais, J.P., Bodemer, C., CEMARA task force (2010) CEMARA an information system for rare diseases. Stud Health Technol Inform, 160, pp. 481-485; Lindblom, A., Robinson, P.N., Bioinformatics for human genetics: promises and challenges (2011) Hum Mutat, 32, pp. 495-500; Messiaen, C., Le Mignot, L., Rath, A., Richard, J.B., Dufour, E., Ben Said, M., Jais, J.P., Gerard-Blanluet, M., CEMARA: a Web dynamic application within a N-tier architecture for rare diseases (2008) Stud Health Technol Inform, 136, pp. 51-56; Miličić Brandt, M., Rath, A., Devereau, A., Ayme, S., Mapping Orphanet terminology to UMLS (2011) Proceedings of the 13th Conference on Artificial Intelligence in Medicine, pp. 194-203. , Berlin, Heidelberg: Springer-Verlag; Webb, A.J., Thorisson, G.A., Brookes, A.J., An informatics project and online "Knowledge Centre" supporting modern genotype-tophenotype research (2011) Hum Mutat, 32, pp. 543-550. , GEN2PHEN Consortium RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Rare disorders are scarcely represented in international classifications and therefore invisible in information systems. One of the major needs in health information systems and for research is to share and/or to integrate data coming from heterogeneous sources with diverse reference terminologies. ORPHANET (www.orpha.net) is a multilingual information portal on rare diseases and orphan drugs. Orphanet information system is supported by a relational database built around the concept of rare disorders. Representation of rare diseases in Orphanet encompasses levels of increasing complexity: lexical (multilingual terminology), nosological (multihierarchical classifications), relational (annotations-epidemiological data-and classes of objects-genes, manifestations, and orphan drugs-integrated in a relational database), and interoperational (semantic interoperability). Rare disorders are mapped to International Classification of Diseases (10th version), SNOMED CT, MeSH, MedDRA, and UMLS. Genes are cross-referenced with HGNC, UniProt, OMIM, and Genatlas. A suite of tools allow for extraction of massive datasets giving different views that can be used in bioinformatics to answer complex questions, intended to serve the needs of researchers and the pharmaceutical industry in developing medicinal products for rare diseases. An ontology is under development. The Orphanet nomenclature is at the crossroads of scientific data repositories and of clinical terminology standards, and is suitable to be used as a standard terminology. © 2012 Wiley Periodicals, Inc. ER - TY - CONF T1 - Improving disease surveillance capabilities in ihe health information exchanges A1 - Renly, S R A1 - Kaufman, J H A1 - Ram, R Y1 - 2009/// KW - Bi-directional KW - Computer science KW - Data exchange KW - Data transfer KW - Disease surveillance KW - Electronic standards KW - Food borne disease KW - Health KW - Health informations KW - Health-care system KW - Information dissemination KW - Information systems KW - Interoperability KW - Large amounts of data KW - Lower cost KW - Monitoring KW - Open source tools KW - PUblic health KW - Pro actives KW - Public health KW - Security KW - Standards KW - Surveillance KW - Terminology SP - 92 EP - 98 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955601951&partnerID=40&md5=c0e3ef070d2deea53c12812ace91c90f N1 - Export Date: 5 April 2018 N2 - Public health programs faithfully collect large amounts of data and create a standard set of monitoring level reports that may be rarely accessed outside their programs. Pervasively challenged by incomplete and untimely data transfers, many programs lack the capacity and funding to drastically redefine their way of operation. New efforts to build interoperable healthcare systems are providing an opportunity to break data out of proprietary silos and evolve new bi-directional information flows that drastically improves surveillance and creates timely pro-active communication between vested communities. Leveraging new open source tools, we succeeded in demonstrating several promising benefits for food borne disease surveillance when electronic standards-based data exchange is achieved within an IHE Health Information Exchange. Bringing together efforts to standardize on terminology, data exchange structuring, security, and confidentiality, we can build a better and lower cost foundation that enables redefining the work achieved within public health programs. © 2009 IADIS. ER - TY - JOUR T1 - Accelerating Public Health Situational Awareness through Health Information Exchanges: An Annotated Bibliography A1 - Revere, Debra A1 - Stevens, Kevin Y1 - 2010/// KW - Washington KW - biosurveillance KW - electronic laboratory reporting KW - health KW - information exchange KW - notifiable diseases KW - situational awareness JF - Online Journal of Public Health Informatics VL - 2 IS - 2 SP - 1 EP - 10 UR - http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/ojphi/article/view/3212 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In 2008, the Centers for Disease Control and Prevention awarded contracts to health information exchanges in Indiana, New York and Washington/Idaho to accelerate public health situational awareness. Awardees in each state have disseminated their findings and lessons at professional conferences and in peer-reviewed journals. The dissemination formats ranged from papers, oral presentations, posters, panels and demonstrations at interoperability showcases. With a focus on health information exchange and public health, topics included biosurveillance, electronic laboratory reporting, broadcast messaging, and notifiable disease surveillance. Each presentation is summarized in this bibliography, and the authors affiliated with each site are highlighted. Keywords: biosurveillance, situational awareness, electronic laboratory reporting, health information exchange, notifiable diseases ER - TY - JOUR T1 - Semantic querying of relational data for clinical intelligence: A semantic web services-based approach A1 - Riazanov, Alexandre A1 - Klein, Artjom A1 - Shaban-Nejad, Arash A1 - Rose, Gregory W A1 - Forster, Alan J A1 - Buckeridge, David L A1 - Baker, Christopher J O Y1 - 2013/// KW - Intelligence KW - Semantics JF - Journal of Biomedical Semantics VL - 4 IS - 1 SP - 1 EP - 19 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND: Clinical Intelligence, as a research and engineering discipline, is dedicated to the development of tools for data analysis for the purposes of clinical research, surveillance, and effective health care management. Self-service ad hoc querying of clinical data is one desirable type of functionality. Since most of the data are currently stored in relational or similar form, ad hoc querying is problematic as it requires specialised technical skills and the knowledge of particular data schemas.\n\nRESULTS: A possible solution is semantic querying where the user formulates queries in terms of domain ontologies that are much easier to navigate and comprehend than data schemas. In this article, we are exploring the possibility of using SADI Semantic Web services for semantic querying of clinical data. We have developed a prototype of a semantic querying infrastructure for the surveillance of, and research on, hospital-acquired infections.\n\nCONCLUSIONS: Our results suggest that SADI can support ad-hoc, self-service, semantic queries of relational data in a Clinical Intelligence context. The use of SADI compares favourably with approaches based on declarative semantic mappings from data schemas to ontologies, such as query rewriting and RDFizing by materialisation, because it can easily cope with situations when (i) some computation is required to turn relational data into RDF or OWL, e.g., to implement temporal reasoning, or (ii) integration with external data sources is necessary. ER - TY - JOUR T1 - Heterogeneous but "standard" coding systems for adverse events: Issues in achieving interoperability between apples and oranges A1 - Richesson, R L A1 - Fung, K W A1 - Krischer, J P Y1 - 2008/// KW - Adverse Drug Reaction Reporting Systems KW - Adverse effects KW - Biomedical Research KW - Biomedical research KW - Clinical Trials as Topic KW - Forms and Records Control KW - Forms and records control KW - Human Experimentation KW - Humans KW - Informatics KW - Medical Informatics Computing KW - Medical Record Linkage KW - Medical Records Systems, Computerized KW - Systematized Nomenclature of Medicine KW - Terminology KW - Terminology as Topic KW - Unified Medical Language System KW - Vocabulary, Controlled KW - adverse drug reaction KW - article KW - clinical research KW - coding KW - concept analysis KW - drug monitoring KW - information processing KW - intermethod comparison KW - medical informatics KW - medical information system KW - reference database KW - standard KW - systematized nomenclature of medicine JF - Contemporary Clinical Trials VL - 29 IS - 5 SP - 635 EP - 645 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-49749090086&doi=10.1016%2Fj.cct.2008.02.004&partnerID=40&md5=8d94c099d931e745930183e390f96b94 N1 - Cited By :11 Export Date: 10 September 2018 References: Friedman, L.M., Furberg, C.D., DeMets, D.L., Assessing and reporting adverse events (1998) Fundamentals of Clinical Trials. Third ed., pp. 170-184. , Springer-Verlag, New York; Richesson, R.L., Krischer, J.P., Data standards in clinical research: gaps, overlaps, challenges and future directions (2007) J Am Med Inform Assoc, 14 (6), pp. 687-696; Souza, T., Kush, R., Evans, J.P., Global clinical data interchange standards are here! (2007) Drug Discov Today, 12 (3-4), pp. 174-181; Levin, R., Data Standards for Regulated Clinical Trials: FDA Perspective (2004) CDISC, , http://www.cdisc.org/pdf/2004_06_14_cdisc.pdf, [Presented DIA Annual Meeting, June 14]. Available at: http://www.cdisc.org/pdf/2004_06_14_cdisc.pdf. Accessed July 21, 2006; Brown, E.G., Wood, L., Wood, S., The Medical Dictionary for Regulatory Activities (MedDRA) (1999) Drug Safety, 20 (2), pp. 109-117; MSSO, (2006) MedDRA Introductory Guide V9.1: Maintenance and Support Services Organization (MSSO); Spackman, K.A., Campbell, K.E., Cote, R.A., SNOMED RT: a reference terminology for health care (1997) Paper presented at: American Medical Informatics Association Fall Symposium; Spackman KA. SNOMED CT milestones: endorsements are added to already-impressive standards credentials. Healthc Inform. Sep 2004;21(9):54, 56; CAP. SNOMED Clinical Terms® Guide. Abstract logical models and representational forms. January 2006 CMWG revision, version 5. 2006 [November]. Accessed January 8, 2007; Spackman, K.A., Campbell, K.E., Compositional concept representation using SNOMED: towards further convergence of clinical terminologies (1998) Proc AMIA Symp., pp. 740-744; CHI, (2004) CHI Executive Summaries: Consolidated Health Informatics, , http://www.whitehouse.gov/omb/egov/documents/CHIExecSummaries.doc, http://www.whitehouse.gov/omb/egov/documents/CHIExecSummaries.doc; Tang, P.C., Position paper. AMIA advocates national health information system in fight against national health threats (2002) J Am Med Inform Assoc, 9 (2), pp. 123-124; American medical informatics association and American health information management association terminology and classification policy task force (2006) Healthcare Terminologies and Classifications: An Action Agenda for the United States, , http://www.amia.org/inside/initiatives/docs/terminologiesandclassifications.pdf, AMIA 2006.http://www.amia.org/inside/initiatives/docs/terminologiesandclassifications.pdf; FDA, FDA news. FDA advances federal E-health effort (2006) Services USDoHaH, ed. Vol P06-61, , U.S. Food and Drug Administration; Trotti, A., The need for adverse effects reporting standards in oncology clinical trials (2004) J Clin Oncol, 22 (1), pp. 19-22; Bodenreider, O., Burgun, A., Botti, G., Fieschi, M., Le Beux, P., Kohler, F., Evaluation of the Unified Medical Language System as a medical knowledge source (1998) J Am Med Inform Assoc, 5 (1), pp. 76-87; NLM, (2000) Fact Sheet Unified Medical Language System, , U.S. National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894 Last updated: 19 April 2000. Accessed 3-2001; Bodenreider, O., The Unified Medical Language System (UMLS): integrating biomedical terminology (2004) Nucleic Acids Res, 32 (Database issue), pp. D267-D270; NLM. Fact Sheet. UMLS ® Metathesaurus. National Library of Medicine. January 13, 2003. Available at: http://www.nlm.nih.gov/pubs/factsheets/umlsmeta.html. Accessed February 6, 2003; Cimino, J.J., Desiderata for controlled medical vocabularies in the twenty-first century (1998) Methods Inf Med, 37 (4-5), pp. 394-403; Almenoff, J., Tonning, J.M., Gould, A.L., Perspectives on the use of data mining in pharmaco-vigilance (2005) Drug Safety, 28 (11), pp. 981-1007; Mozzicato, P., Find more like this. Standardised MedDRA queries: their role in signal detection (2007) Drug Safety, 30 (7), pp. 617-619; Bousquet, C., Lagier, G., Lillo-Le Lou, A., Le Beller, C., Venot, A., Jaulent, M.C., Appraisal of the MedDRA conceptual structure for describing and grouping adverse drug reactions (2005) Drug Safety, 28 (1), pp. 19-34; Segal, E.S., Valette, C., Oster, L., Risk management strategies in the postmarketing period: safety experience with the US and European bosentan surveillance programmes (2005) Drug Safety, 28 (11), pp. 971-980; NCI. caBIG. Cancer Biomedical Informatics Grid. Data Standards. National Cancer Institute. January 4, 2008. Available at: https://cabig.nci.nih.gov/workspaces/VCDE/Data_Standards/index_html/. Accessed May 25, 2006; Haber, M.W., Kisler, B.W., Lenzen, M., Wright, L.W., Controlled terminology for clinical research: a collaboration between CDISC and NCI enterprise vocabulary services (2007) Drug Inf J, 41, pp. 405-412; Cimino, J.J., Review paper: coding systems in health care (1996) Methods Inf Med, 35 (4-5), pp. 273-284; NCI, List of codes and values (2007) National Cancer Institute Cancer Therapuetics Evaluation Program (CTEP), , http://ctep.cancer.gov/guidelines/codes.html, Available at: http://ctep.cancer.gov/guidelines/codes.html. Accessed January 22, 2008; MSSO, (2006) Summary of MedDRA MSSO's Blue Ribbon Panel Meeting on CTCAE-MedDRA Mapping, , http://www.meddramsso.com/MSSOWeb/docs/8466-100, Northrop Grumman Corporation, MedDRA Maintenance and Support Services Organization (MSSO) Available at: http://www.meddramsso.com/MSSOWeb/docs/8466-100%20Summary%20BRP%20Apr2006.doc. Accessed January 22, 2008; Alecu, I., Bousquet, C., Jaulent, M.C., Mapping of the WHO-ART terminology on SNOMED-CT to improve grouping of related adverse drug reactions. (2006) Paper presented at: Stud Health Technol Inform. RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Monitoring adverse events (AEs) is an important part of clinical research and a crucial target for data standards. The representation of adverse events themselves requires the use of controlled vocabularies with thousands of needed clinical concepts. Several data standards for adverse events currently exist, each with a strong user base. The structure and features of these current adverse event data standards (including terminologies and classifications) are different, so comparisons and evaluations are not straightforward, nor are strategies for their harmonization. Three different data standards - the Medical Dictionary for Regulatory Activities (MedDRA) and the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) terminologies, and Common Terminology Criteria for Adverse Events (CTCAE) classification - are explored as candidate representations for AEs. This paper describes the structural features of each coding system, their content and relationship to the Unified Medical Language System (UMLS), and unsettled issues for future interoperability of these standards. © 2008 Elsevier Inc. All rights reserved. ER - TY - CONF T1 - Process mining to knowledge discovery in healthcare processes A1 - Riz, G A1 - Santos, E A P A1 - Loures, E.D.F.R. Y1 - 2016/// KW - Brazil KW - Business rules KW - Data mining KW - Health care KW - Health-care system KW - Healthcare KW - Healthcare process KW - Interdisciplinary cooperations KW - Knowledge discovery process KW - Organizational mining KW - Process interoperability KW - Process mapping KW - Process mining VL - 4 SP - 1019 EP - 1028 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84993158594&doi=10.3233%2F978-1-61499-703-0-1019&partnerID=40&md5=bd09927da0338acc40236b3d83138320 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Riz, Santos, Loures - 2016 - Process mining to knowledge discovery in healthcare processes.pdf N1 - Cited By :1 Export Date: 10 September 2018 References: Mans, R.S., Schonenberg, M.H., Song, M., Van Der Aalst, W.M.P., Rakker, P.J.M., Process mining in healthcare-A case study in healthcare-A case study in a Dutch hospital (2009) Biomedical Engineering Systems and Technologies-Communication in Computer and Information Science, 25, pp. 425-438; Kaymak, U., Mans, R., De S.T.Van, Dierks, M., On Process Mining in Health Care (2012) IEEE International Conference on Systems, Man, and Cybernetics, , October 14-17, Seoul, Korea; Azevedo Bittencourt, S., Bastos Camacho, L.A., Do Carmo Leal, M., Sistema, O., (2006) De Informação Hospitalar e Sua Aplicação Na Saúde Coletiva-Cad Saúde Pública, 22 (1). , Rio de Janeiro; Rebuge, A.J.S., (2012) Business Process Analysis in Healthcare Environments, , Master thesis, The Technical University of Lisboa; Aalst Der W.Van, Process mining: Overview and opportunities (2012) ACM Transactions of Management Information Systems (TMIS), 3 (2), p. 7; Song, M., Van Der Aalst, W.M.P., Towards comprehensive support for organization mining (2008) Decision Support Systems, 46 (1), pp. 300-317; Espadinha-Cruz, P., Gonçalves-Coelho, A., Mourão, A., Grilo, A., Re-design of an interoperable buyer-seller automotive relationship aided by computer simulation (2015) 9th International Conference on Axiomatic Design-ICAD; Van Der Aalst, W.M.P., Reijers, H.A., Song, M., Discovering social networks from event logs (2005) Computer Supported Cooperative Work (CSCW), 14 (6), pp. 549-593. , December RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Healthcare processes are complex and require a high-level of interdisciplinary cooperation among the different specialists and sectors involved in their delivery. Information flows among organizational entities, sectors, areas and employees represent possible low process interoperability risks as well as noncompliance risks between business rules and actual process deliveries. Besides this complexity, the Brazilian healthcare area has a notorious problem in its public and private health care systems. These problems are of structural, organizational and financial natures, reflecting the low value attributed to quality and to the actual services in recent surveys of Instituto Data Folha and the Brazilian Ministry of Health (Ministério da Saúde). This paper intends to propose an adaptation of Process Mining as an ancillary tool in knowledge discovery processes in healthcare in order to contribute to further improving this area in Brazil. In order to accomplish this, a case study was carried out in the Erasto Gaertner Hospital, located in Curitiba - PR, Brazil, a local reference in cancer treatments. © 2016 The authors and IOS Press. ER - TY - JOUR T1 - Biomedical informatics advancing the national health agenda: the AMIA 2015 year-in-review in clinical and consumer informatics A1 - Roberts, K A1 - Boland, M R A1 - Pruinelli, L A1 - Dcruz, J A1 - Berry, A A1 - Georgsson, M A1 - Hazen, R A1 - Sarmiento, R F A1 - Backonja, U A1 - Yu, K.-H. A1 - Jiang, Y A1 - Brennan, P F Y1 - 2017/// KW - Consumer Health Informatics KW - Humans KW - Informatics KW - Meaningful Use KW - Medical Informatics KW - Patient Participation KW - Public Health Informatics KW - Societies, Medical KW - United States KW - biomedical informatics KW - consumer engagement KW - consumer health informatics KW - electronic health records KW - human KW - learning health system KW - meaningful use criteria KW - medical informatics KW - medical society KW - patient participation KW - year in review JF - Journal of the American Medical Informatics Association : JAMIA VL - 24 SP - e185 EP - e190 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85019160724&doi=10.1093%2Fjamia%2Focw103&partnerID=40&md5=29e3be9e1a1f4808d9d59c2b127a08ac L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Roberts et al. - 2017 - Biomedical informatics advancing the national health agenda the AMIA 2015 year-in-review in clinical and consume.pdf N1 - Cited By :2 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The field of biomedical informatics experienced a productive 2015 in terms of research. In order to highlight the accomplishments of that research, elicit trends, and identify shortcomings at a macro level, a 19-person team conducted an extensive review of the literature in clinical and consumer informatics. The result of this process included a year-in-review presentation at the American Medical Informatics Association Annual Symposium and a written report (see supplemental data). Key findings are detailed in the report and summarized here. This article organizes the clinical and consumer health informatics research from 2015 under 3 themes: the electronic health record (EHR), the learning health system (LHS), and consumer engagement. Key findings include the following: (1) There are significant advances in establishing policies for EHR feature implementation, but increased interoperability is necessary for these to gain traction. (2) Decision support systems improve practice behaviors, but evidence of their impact on clinical outcomes is still lacking. (3) Progress in natural language processing (NLP) suggests that we are approaching but have not yet achieved truly interactive NLP systems. (4) Prediction models are becoming more robust but remain hampered by the lack of interoperable clinical data records. (5) Consumers can and will use mobile applications for improved engagement, yet EHR integration remains elusive. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com. ER - TY - JOUR T1 - Implementation of a web based universal exchange and inference language for medicine: Sparse data, probabilities and inference in data mining of clinical data repositories A1 - Robson, B A1 - Boray, S Y1 - 2015/// KW - Algorithms KW - Article KW - Artificial intelligence KW - Bayes KW - Bayes Theorem KW - Bayes theorem KW - Big data KW - Cognitive Computing KW - Cognitive computing KW - Computation theory KW - Computational linguistics KW - Cross-Sectional Studies KW - Data Mining KW - Data mining KW - Databases, Factual KW - Decision Support Systems, Clinical KW - Decision support systems KW - Diagnosis KW - Dirac notation KW - Electronic Health Records KW - Electronic document exchange KW - Electronic health record KW - Female KW - Health KW - Humans KW - Internet KW - Male KW - Medical Informatics KW - Medicine KW - Probability KW - Probability theory KW - Project management KW - Public Health KW - Public health KW - Public health reporting KW - Social networking (online) KW - Software KW - Surveys KW - Universal exchange language KW - Watson KW - Zeta function KW - algorithm KW - association constant KW - biostatistics KW - clinical data repository KW - clinical decision support system KW - computer program KW - data mining KW - decision support system KW - electronic health record KW - factual database KW - female KW - health care management KW - human KW - language KW - male KW - mass screening KW - maximum likelihood method KW - medical informatics KW - medical information KW - partition coefficient KW - priority journal KW - probability KW - procedures KW - public health KW - quantum mechanics KW - reliability KW - software KW - web browser JF - Computers in Biology and Medicine VL - 66 SP - 82 EP - 102 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84941884468&doi=10.1016%2Fj.compbiomed.2015.07.015&partnerID=40&md5=3889390331e662400e062d12484274b3 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Robson, Boray - 2015 - Implementation of a web based universal exchange and inference language for medicine Sparse data, probabilities a.pdf N1 - Cited By :6 Export Date: 10 September 2018 References: Robson, B., Caruso, T.P., Balis, U.G.J., Suggestions for a web based universal exchange and inference language for medicine (2013) Comput. Biol. Med., 43 (12), p. 2297; Robson, B., Caruso, T., Balis, U.G.J., Suggestions for a web based universal exchange and inference language for medicine. Continuity of patient care with PCAST disaggregation (2015) Comput. Biol. Med., 56, p. 51; Robson, B., Hyperbolic Dirac Nets for Medical Decision support. Theory, methods, and comparison with Bayes nets (2014) Comput. Biol. Med., 51, p. 183; Robson, B., POPPER, a simple programming language for probabilistic semantic inference in medicine (2015) Comput. Biol. Med., 56, p. 107; Pearl, J., (1985) Probabilistic Reasoning in Intelligent Systems, , Morgan Kaufmann, San Francisco, CA; Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A.A., Lally, A., Welty, C.S., Building Watson: an overview of the DeepQA project (2010) AI Mag., 31 (3), p. 59; Dirac, P.A.M., A new notation for quantum mechanics (1939) Math. Proc. Camb. Philos. Soc., 35 (3), p. 416; Dirac, P.A.M., (1930) The Principles of Quantum Mechanics, , Oxford University Press, Oxford; Robson, B., The new physician as unwitting quantum mechanic: is adapting dirac's inference system best practice for personalized medicine, genomics and proteomics? (2007) J. Proteome Res. (A. Chem. Soc.), 6 (8), p. 3114; Deckelman, S., Robson, B., Split-complex numbers and Dirac brakets (2015) Commun. Inf. Syst., 14, p. 135; http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast-health-it-report.pdf, (last accessed 30.03.13); http://en.wikipedia.org/wiki/Semantic_Web, (last accessed 30.03.13); http://en.wikipedia.org/wiki/Resource:Description_Framework, (last accessed 10.04.13); http://en.wikipedia.org/wiki/Triplestore, (last accessed 05.06.13); Prediou, L., Stuckenschmidt, H., (2009) Probabilistic models for the SW - a survey, , http://ki.informatik.uni-mannheim.de/fileadmin/, publication/Predoiu08Survey.pdf, (last accessed 4/29/2010); Greenes, R.A., (2006) Clinical Decision Support, , Academic Press, (Ed.); Buchanan, B., Shortliffe, E.H., Rule Based Expert Systems, The Mycin Experiments of the Stanford Heuristic Programming Project (1982), Addison-Wesley, Reading, MA; Robson, B., Analysis of the code relating sequence to conformation in globular proteins: theory and application of expected information (1974) Biochemistry, J141, p. 853; Garnier, J., Osguthorpe, D.J., Robson, B., Analysis of the accuracy and implications of simple methods for predicting the secondary structure of globular proteins (1978) J. Mol. Biol., 120, p. 97; Robson, B., Clinical and pharmacogenomic data mining: 3. Zeta theory as a general tactic for clinical bioinformatics (2005) J. Proteome Res. (Am. Chem. Soc.), 4 (2), pp. 445-455; Robson, B., Clinical and pharmacogenomic data mining: 4. The FANO program and command set as an example of tools for biomedical discovery and evidence based medicine (2008) J. Proteome Res., 7 (9), p. 3922; Mullins, I.M., Siadaty, M.S., Lyman, J., Scully, K., Garrett, G.T., Miller, G., Muller, R., Cohen, S., Data mining and clinical data repositories: insights from a 667,000 patient data set (2006) Comput. Biol. Med., 36 (12), p. 1351; Popper, K., (2002) The Logic of Scientific Discovery, , Routledge, London; Robson, B., The dragon on the gold: myths and realities for data mining in biotechnology using digital and molecular libraries (2004) J. Proteome Res. (Am. Chem. Soc.), 3 (6), p. 1113; Robson, B., Vaithiligam, A., (2010) Drug gold and data dragons: myths and realities of data mining, , John Wiley & Sons, K.V. Balakin (Ed.); Toulmin, S.E., (2003) The Uses of Argument, , Cambridge University Press; (2006) Arguing on the Toulmin Model. New Essays in Argument Analysis and Evaluation, , Springer, Dordrecht, D. Hitchcock, B. Verheij (Eds.); Shmueli, G., To explain or to predict? (2010) Stat. Sci., 25 (3), p. 289; Bayes, T., An Essay towards solving a problem in the Doctrine of Chances, (published posthumously and communicated by R. Price) (1763) Bull. Philos. Trans. R. Soc. Lond., 53, p. 370; Lehmnan, E.L., (2011) Fisher Neyman, and the Creation of Classical Statistics, , Springer-Verlag; (2014), http://caymanheartfund.com/contact-us/, (last accessed 09.09.14) ; http://yosemitemanifesto.org/, (last accessed 07.05.14); http://www.ehps-net.eu/article/intermediate-data-structure-ids-longitudinal-historical-microdata-version-4, (last accessed 01.05.14); Alter, G., Mandemakers, K., The Intermediate Data Structure (IDS) for longitudinal historical microdata, version 4. (2014) Hist. Life Course Stud., 1, pp. 1-26; Copi, R., A theoretical framework for data mining: the "information paradigm" (2002) Comp. Stat. Data Anal., 38, p. 501; Hastie, T., Tibshirani, R., Friedman, J., (2001) The elements of statistical learning: data mining, inference and prediction, , Springer-Verlag, New York; Heckeman, D., Bayesian networks for data mining (1997) J. Data Min. Knowl. Discov., 1, p. 79; http://www.nobelprize.org/nobel_prizes/physics/laureates/1933/dirac-speech.html; Strauss, S.E., Glasziou, P., Richardson, W.S., Haynes, R.B., (2011) Evidence-Based Medicine: How to Practice and Teach It, , Elsevier; Hoyt, R.E., Bailey, N., (2012) Health Informatics: Practical Guide For Healthcare And Information Technology Professionals, , http://www.lulu.com, fifth edition; (2013) Biomedical Informatics: Computer Applications in Health Care and Biomedicine (Health Informatics), , Springer, E.H. Shortliffe, J.J. Cimino (Eds.); Lloyd-Jones, D.M., Wilson, P.W.F., Larson, M.G., Beiser, A., Leip, E.P., D'Agostino, R.B., Levy, D., Framingham Risk Score and 20 Prediction of Lifetime Risk for Coronary Heart Disease (2004) Am. J. Cardiol., 94; Coiera, E., (1994) Question the assumptions, p. 61. , IOS Press, Amsterdam, P. Barahona, J.P. Christensen (Eds.); Miller, R.A., Medical diagnostic decision support systems--past, present, and future: a threaded bibliography and brief commentary (1994) J. Am. Med. Inform. Assoc. Mar.- 1, (2), p. 160; Perreault, L., Metzger, J., A pragmatic framework for understanding clinical decision support (1999) J. Healthc. Inf. Manage., 13 (2), p. 5; Wong, H.J., Legnini, M.W., Whitmore, H.H., The diffusion of decision support systems in healthcare: are we there yet? (2000) J. Healthc. Manage., 45 (4), p. 240. , (discussion); Trivedi, M.H., Kern, J.K., Marcee, A., Grannemann, B., Kleiber, B., Bettinger, T., Altshuler, K.Z., McClelland, A., Development and implementation of computerized clinical guidelines: barriers and solutions (2002) Methods Inf. Med., 41 (5), p. 435; Fieschi, M., Dufour, J.C., Staccini, P., Gouvernet, J., Bouhaddou, O., Medical decision support systems: old dilemmas and new paradigms? (2003) Methods Inf. Med., 42 (3), p. 190; Coiera, E., (2003) Clinical Decisison support Systems, The Guide to Health Informatics, , Arnold, London, (Chapter 5); Berlin, A., Sorani, M.M., Sim, I., A taxonomic description of computer-based clinical decision support systems (2006) J. Biomed. Inform., 39 (6), p. 656; Rochon, D., A bicomplex Riemann Zeta function (2004) Tokyo J. Math., 27 (2), p. 357; Buchholz, S., Sommer, G., (2000) A hyperbolic multilayer perceptron, p. 129. , IEEE Computer Society Press, S.-I. Amari, C.L. M. Giles, M. Gori, V. Piuri (Eds.); Nitta, T., Solving the XOR problem and the detection of symmetry using a single complex-valued neuron (2003) Neural Netw., 16 (8), p. 1101; Nitta, T., Bucholtz, S., On the decision boundaries of hyperbolic neurons (2008) Proceedings of the 2008 International Joint Conference on Neural Networks (IJCNN); Savitha, R.S., Suresh, S., Sundararajan, S., Saratchandran, P., A new learning algorithm with logarithmic performance index for complex-valued neural networks (2009) Neurocomputing, 72 (16-18), p. 3771; Kuroe, Y., Shinpei, T., Iima, H., Models of Hopfield-type clifford neural networks and their energy functions - hyperbolic and dual valued networks (2011) Lect. Notes Comput. Sci., 7062, p. 560; Hapt, S.E., Pasino, A., Marzban, C., (2008) Artificial Intelligence Methods in the Environmental Sciences, , Springer Science & Business Media; Khrenikov, A., (2000) Hyperbolic Quantum Mechanics, , arXiv:quant-ph/0101002v1, Cornell University Library; Khrennikov, A., Hyperbolic quantum mechanics (2003) Adv. Appl. Clifford Algebras, 13, p. 1; Khrennikov, A., (2009) Contextual Approach to Quantum Formalism, , Springer; Khrennikov, A., On quantum-like probabilistic structure of mental information (2004) Open Syst. Inf. Dyn., 11 (3), p. 267; Moldoveanu, F., (2013) Non Viability of Hyperbolic Quantum Mechanics as a Theory of Nature, , arXiv:1311.6461v2 [quant-ph], Cornell University Library; Kunegis, J., Gröner, G., Gottrron, T., On-Line Dating Recommender Systems, the Split Complex Number Approach, , http://userpages.uni-koblenz.de/~kunegis/paper/kunegis-online-dating-recommender-systems-the-split-complex-number-approach.pdf, (Like/Dislike, Similar/Disimilar) (last accessed 06.01.14); http://en.wikipedia.org/wiki/Bayesian_network, (last accessed 01.05.14); Mitchell, T., (1997) Machine Learning, , McGraw-Hill; Penrose, R., (1989) The Emperor's New Mind, , Oxford University Press; Borrelli, A., (2009) Quantum statistics, , Springer, D. Greenberger, K. Hentschel, F. Weinert (Eds.); Bogomolny, E., Chaotic dynamics (2007) Prog. Theor. Phys. Suppl., 166; Higgins, J.P.T., Green, S., (2008) Cochrane Handbook for Systematic Reviews of Interventions, , Wiley-Blackwell, (Eds.); (2014) Connecting Health and Care for the Nation: A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure, , http://healthit.gov/sites/default/files/ONC10yearInteroperabilityConceptPaper.pdf, (last accessed 06.02.15); Kohn, L.T., Corrigan, J.M., Donaldson, M.S., (1999) To Err is Human: Building a Safer Health System, , National Academy Press, Institute of Medicine, Washington, DC RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - We extend Q-UEL, our universal exchange language for interoperability and inference in healthcare and biomedicine, to the more traditional fields of public health surveys. These are the type associated with screening, epidemiological and cross-sectional studies, and cohort studies in some cases similar to clinical trials. There is the challenge that there is some degree of split between frequentist notions of probability as (a) classical measures based only on the idea of counting and proportion and on classical biostatistics as used in the above conservative disciplines, and (b) more subjectivist notions of uncertainty, belief, reliability, or confidence often used in automated inference and decision support systems. Samples in the above kind of public health survey are typically small compared with our earlier "Big Data" mining efforts. An issue addressed here is how much impact on decisions should sparse data have. We describe a new Q-UEL compatible toolkit including a data analytics application DiracMiner that also delivers more standard biostatistical results, DiracBuilder that uses its output to build Hyperbolic Dirac Nets (HDN) for decision support, and HDNcoherer that ensures that probabilities are mutually consistent. Use is exemplified by participating in a real word health-screening project, and also by deployment in a industrial platform called the BioIngine, a cognitive computing platform for health management. © 2015 Elsevier Ltd. ER - TY - JOUR T1 - Towards an ontology to support Semantics enabled diagnostic decision support systems A1 - Rodríguez-González, A A1 - Hernández-Chan, G A1 - Colomo-Palacios, R A1 - Gomez-Berbis, J M A1 - García-Crespo, Á A1 - Alor-Hernandez, G A1 - Valencia-Garcia, R Y1 - 2012/// KW - Diagnosis, Differential KW - Knowledge representation KW - Medical diagnosis KW - Ontology KW - article KW - clinical examination KW - computer KW - data base KW - decision support system KW - diagnostic test KW - diagnostic value KW - differential diagnosis KW - health care KW - medical diagnostic decision support system KW - medical informatics KW - medical information system KW - medical terminology KW - priority journal KW - semantic web KW - semantics KW - symptomatology JF - Current Bioinformatics VL - 7 IS - 3 SP - 234 EP - 245 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866643381&doi=10.2174%2F157489312802460721&partnerID=40&md5=58ff1753c9aa73b53567621576c09114 N1 - Cited By :9 Export Date: 10 September 2018 References: Wroe, C., Is Semantic Web technology ready for Healthcare? (2006) 3rd European Semantic Web Conference; Gruber, T.R., Toward principles for the design of ontologies used for knowledge sharing (1995) Intl J Human Comput Studies, 34 (5-6), pp. 907-928; Cohen, J., Bioinformatics-An introduction for computer scientists (2004) ACM Comput Surveys, 36 (2), pp. 122-158; London, S., DXplain: A Web-based diagnostic decision support system for medical students (1998) Med Ref Services Quarterly, 17 (2), pp. 17-28; Ramnarayan, P., Tomlinson, A., Rao, A., Coren, M., Winrow, A., Britto, J., ISABEL: A web-based differential diagnostic aid for paediatrics: Results from an initial performance evaluation (2003) Arch Disease Childhood, 88 (5), pp. 408-413; Ibrahim, M., AbdelRahman, S., Farag, I., IWSMD: An Intelligent Web Service based Medical Diagnosis System (2008) The 6th International Conference on Informatics and Systems; Le Beux, P., Rammal, M., Riou, C., Frangeul, C., Cador, F., Lenoir, P., ADM: A diagnostic aid knowledge base for general practitioners (1998) IMIA Intl Conf Med Inform Med Edu, pp. 223-229; Saito, K., Nakano, R., Medical diagnostic expert system based on PDP model (1988) IEEE Intl Conf Neuronal Networks, 255, p. 262; Berners-Lee, T., Hendler, J., Lassila, O., The semantic web (2001) Sci Am, 284 (5), pp. 34-43; Fensel, D., (2002) Ontologies: A silver bullet for knowledge management and electronic commerce, , Berlin: Springer; Mikroyannidis, A., Theodoulidis, B., Ontology management and evolution for business intelligence (2010) Intl J Inform Manag, 30 (6), pp. 559-566; García, R., Using the rhizomer platform for semantic decision support systems development (2010) Intl J Decision Support Syst Technol, 2 (1), pp. 60-80; Alani, H., Hall, W., O'Hara, K., Shadbolt, N., Szomszor, M., Chandler, P., Building a Pragmatic Semantic Web (2008) IEEE Int Syst, 23 (3), pp. 61-68; Fuentes-Lorenzo, D., Morato, J., Gómez-Berbís, J.M., Knowledge management in biomedical libraries: A semantic web approach (2009) Inform Syst Frontiers, 11 (4), pp. 471-480; Sicilia, J.J., Sicilia, M.A., Sánchez-Alonso, S., García-Barriocanal, E., Pontikaki, M., Knowledge Representation Issues in Ontology-based Clinical Knowledge Management Systems (2009) Intl J Technol Manag, 47 (1-3), pp. 191-206; Rodríguez-González, A., Labra-Gayo, J.E., Colomo-Palacios, R., Mayer, M.A., Gómez-Berbis, J.M., García-Crespo, A., SeDeLo: UsingSemantics and DescriptionLogicstosupportaidedclinicaldiagnosis (2011) J Med Syst, , http://dx.doi.org/10.1007/s10916-011-9714-1, in press; García-Crespo, A., Rodríguez, A., Mencke, M., Gómez-Berbís, J.M., Colomo-Palacios, R., ODDIN: Ontology-driven differential diagnosis based on logical inference and probabilistic refinements (2010) Expert Syst Appl, 37 (3), pp. 2621-2628; Rodríguez-González, A., García-Crespo, A., Colomo-Palacios, R., Labra-Gayo, J.E., Gómez-Berbís, J.M., Alor-Hernández, G., Automated Diagnosis throughOntologies and Logical Descriptions: The ADONIS approach (2011) Intl J Decision Support Syst Technol, 3 (1), pp. 21-39; Splendiani, A., Burger, A., Paschke, A., Romano, P., Marshall, M.S., Biomedical semantics in the Semantic Web (2011) J Biomed Semantics, 2 (1), pp. S1; Smith, B., Scheuermann, R.H., Ontologies for clinical and translational research: Introduction (2011) J Biomed Inform, 44 (1), pp. 3-7; Grenon, P., Smith, B., Goldberg, L., Biodynamic ontology: Applying bfo in the biomedical domain (2004) Studies Health Technol Inform, 102, pp. 20-38; Smith, B., The Basic Tools of Formal Ontology (2004) Formal Ontology in Information Systems, , In: Nicola Guarino (ed.), IOS Press; Smith, B., Ashburner, M., Rosse, C., The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration (2007) Nat Biotechnol, 25 (11), pp. 1251-1255; Smith, B., Ceusters, W., Klagges, B., Relations in biomedical ontologies (2005) Genome Biol, 6 (5), pp. R46; Corcho, O., Fernandez-Lopez, M., Gomez-Perez, A., Methodologies, tools and languages for building ontologies. Where is their meeting point? (2003) Data & Knowl Eng, 46, pp. 41-64; Sofia-Pinto, H., Gomez-Perez, A., Martins, J.P., Some Issues on Ontology Integration (1999) Proc. of IJCAI99's Workshop on Ontologies and Problem Solving Methods: Lessons Learned and Future Trends; Spackman, K.A., Campbell, K.E., SNOMED RT: A reference terminology for health care (1997) Proc AMIA Ann Symp, pp. 640-644; Stearns, M.Q., Price, C., Spackman, K.A., Wang, Y., SNOMED clinical terms: Overview of the development process and project status (2001) Proc AMIA Ann Symp, 662, p. 666; Rector, A., Rogers, J., Zanstra, P.E., van der Haring, E., OpenGALEN: Open Source Medical Terminology and Tools (2003) Proc AMIA Symp; (2010) World Health Organization: International Classification of Diseases, , http://www.who.int/classifications/icd/en/, Avalaible online at; Lipscomb, C.E., Medical Subject Headings (MeSH) (2000) Bull Med Library Assoc, 88 (2), pp. 265-266; SNOMED CT Hierarchies, , http://www.ihtsdo.org/snomed-ct/snomed-ct0/snomed-cthierarchies/, IHTSDO, Avalaible online at, Last accessed, December 8, (2010); Miller, R.A., Gardner, R.M., Johnson, K.B., Hripcsak, G., Clinical decision support and electronic prescribing systems: A time for responsible thought and action (2005) J Am Medical Inform Assoc, 12, pp. 403-409; Bizer, C., Heath, T., Berners-Lee, T., Linked Data-The Story So Far (2009) Intl J Semantic Web Inform Syst, 5 (3); Gruninger, M., Fox, M.S., Methodology for the design and evaluation of ontologies (1995) Proc Int'l Joint Conf AI Workshop on Basic Ontological Issues in Knowledge Sharing; Noy, N.F., Hafner, C.D., The State of the Art in Ontology Design: A Survey and Comparative Review (1997) AI Magazine, 18 (3); Maynard, D., Peters, W., Li, Y., Metrics for evaluation of Ontology-based Information Extraction (2006) Proc. of the EON 2006 Workshop; Brank, J., Grobelnik, M., Mladenić, D., A survey of ontology evaluation techniques (2005) Conference on Data Mining and Data Warehouses; Sutcliffe, A.G., Maiden, N.A.M., Minocha, S., Manuel, D., Supporting Scenario-Based Requirements Engineering (1998) IEEE Trans Software Eng, 24 (12), pp. 1072-1088; Thompson, S., Fueten, F., Bockus, D., Mineral identification using artificial neural networks and the rotating polarizer stage (2001) Comput & Geosci, 27 (9), pp. 1081-1089; Neches, R., Fikes, R.E., Finin, T., Enabling Technology for Knowledge Sharing (1991) AI Magazine, 12 (3); Nguyen, T.A., Perkins, W.A., Laffey, T.J., Pecora, D., Checking an expert systems knowledge base for consistency and completeness (1985) International Joint Conference on Artificial Intelligence-IJCAI, 375, p. 378; Noy, N.F., McGuinness, D.L., Ontology Development 101: A Guide to Creating Your First Ontology (2011) Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880; O'Reilly, C.A., Individuals and Information Overload in Organizations: Is More Necessarily Better? (1980) Acad Manag J, 23 (4), pp. 684-696; Maynard, D., Li, Y., Peters, W., NLP Techniques for Term Extraction and Ontology Population Proceeding of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Healthcare has played a main role in the Semantic Web (SW) field given the knowledge representation possibilities that SW is capable of addressing. Nowadays there are a large number of ontologies which can be used for several domains of healthcare (genetics, proteins, cellular components, anatomy, and specific diseases among others). However, in some cases, the definition and population of these ontologies are not enough to be used in concrete domains. In this paper we provide the design of a set of ontologies for their direct use in diagnostic decision support systems. We have designed an ontology modular architecture where main (root) ontology is created to define the main relations which can be found in the aforementioned domain. A set of subsumed ontologies has also been designed following some principles of OBO-Foundry and using SNOMED-CT terminology as the main interoperability component. These ontologies have been also designed trying to create them as light as possible. The evaluation of the designed ontology is based on a set of quantitative aspects which aims to show the main principles which should be followed in the process of design ontologies for the domain of differential diagnosis. © 2012 Bentham Science Publishers. ER - TY - JOUR T1 - Representing Knowledge Consistently Across Health Systems A1 - Rosenbloom, S T A1 - Carroll, R J A1 - Warner, J L A1 - Matheny, M E A1 - Denny, J C Y1 - 2017/// KW - Common Data Elements KW - Health Information Interoperability KW - Health Level Seven KW - Information Dissemination KW - Medical Informatics KW - Medical Records Systems, Computerized KW - common data elements KW - data interoperability KW - electronic medical record system KW - health level 7 KW - medical informatics KW - standards JF - Yearbook of medical informatics VL - 26 IS - 1 SP - 139 EP - 147 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041819854&doi=10.15265%2FIY-2017-018&partnerID=40&md5=2ac1c70904aabdf9c6115fd3463aa58f L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Rosenbloom et al. - 2017 - Representing Knowledge Consistently Across Health Systems.pdf N1 - Cited By :2 Export Date: 10 September 2018 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objectives: Electronic health records (EHRs) have increasingly emerged as a powerful source of clinical data that can be leveraged for reuse in research and in modular health apps that integrate into diverse health information technologies. A key challenge to these use cases is representing the knowledge contained within data from different EHR systems in a uniform fashion. Method: We reviewed several recent studies covering the knowledge representation in the common data models for the Observational Medical Outcomes Partnership (OMOP) and its Observational Health Data Sciences and Informatics program, and the United States Patient Centered Outcomes Research Network (PCORNet). We also reviewed the Health Level 7 Fast Healthcare Interoperability Resource standard supporting app-like programs that can be used across multiple EHR and research systems. Results: There has been a recent growth in high-impact efforts to support quality-assured and standardized clinical data sharing across different institutions and EHR systems. We focused on three major efforts as part of a larger landscape moving towards shareable, transportable, and computable clinical data. Conclusion: The growth in approaches to developing common data models to support interoperable knowledge representation portends an increasing availability of high-quality clinical data in support of research. Building on these efforts will allow a future whereby significant portions of the populations in the world may be able to share their data for research. Georg Thieme Verlag KG Stuttgart. ER - TY - JOUR T1 - Holistic health: Predicting our data future (from inter-operability among systems to co-operability among people) A1 - Rossi Mori, A A1 - Mazzeo, M A1 - Mercurio, G A1 - Verbicaro, R Y1 - 2013/// KW - Attention Points KW - Care pathways KW - Cooperative Behavior KW - Data quality KW - Digital storage KW - EHealth policies KW - Ecosystems KW - Ehealth KW - Health KW - Health records KW - Holistic Health KW - Holistic health KW - Humans KW - Information management KW - Long-term conditions KW - Medicine KW - Models, Organizational KW - Patient engagement KW - Policy-Oriented Health Record KW - Semantic interoperability KW - Semantics KW - Social care KW - Systems Integration KW - administrative personnel KW - article KW - caregiver KW - change management KW - clinical pathway KW - cultural anthropology KW - ecosystem KW - futurology KW - health care need KW - health care organization KW - health care personnel KW - health care planning KW - health care policy KW - health care quality KW - health care system KW - health practitioner KW - information system KW - interhospital cooperation KW - interpersonal communication KW - long term care KW - mandatory program KW - medical ethics KW - medical informatics KW - medical information system KW - medical record KW - medical technology KW - patient care KW - philosophy KW - priority journal KW - professional knowledge KW - residential home KW - society KW - standard KW - wellbeing JF - International Journal of Medical Informatics VL - 82 LA - English IS - 4 SP - e14 EP - e28 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875378600&doi=10.1016%2Fj.ijmedinf.2012.09.003&partnerID=40&md5=2115cd915ccfc264d13445102212ab9c L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Rossi Mori et al. - 2013 - Holistic health Predicting our data future (from inter-operability among systems to co-operability among peop.pdf N1 - Ehealth AND governance L52283660 2012-11-02 2013-04-08 Cited By :15 Export Date: 10 September 2018 References: http://www.oecd.org/sti/smarterhealth, OECD-NSF Workshop "Building a Smarter Health and Wellness Future", Washington. (accessed 15-16.02.11); Iakovidis, I., (2009) Introducing Information and Communication Technologies into Medicine: New Challenges for Research and Development, pp. 21-23. , The European File. eHealth in Europe; Rossi Mori, A., Towards a European roadmap for achieving eHealth interoperability (2007) eHealth Berlin Conference 2007-04-18, Special Interest Session II "Electronic Health Records and Interoperability", , http://www.eurorec.org/news_events/newsArchive.cfm%3FnewsID=142; Rossi Mori, A., RIDE D4. 3. 1 - "Policies and strategies" (2007) Deliverable of the EU Coordination Action "RIDE - A Roadmap for Interoperability of eHealth Systems in Support of COM 356 with Special Emphasis on Semantic Interoperability, , http://www.srdc.metu.edu.tr/webpage/projects/ride/modules.php%3Fname=DeliverablesRIDE-D4.3.1%20policies%20final%20v06a.doc; (2005) Building a Health Service Fit For the Future Volume 2: A Guide for the NHS, , http://www.scotland.gov.uk/Publications/2005/05/23141500/15035, Scottish Executive; (2011), http://ec.europa.eu/information_society/activities/einclusion/deployment/jpi/index_en.htm, European Commission. "More years, Better Lives - The Potential and Challenges of Demographic Change" Recommendation (2011/413/EU), (accessed 11.07.11); (2007), http://ec.europa.eu/employment_social/social_inclusion, Council of the European Union (2007). "Joint Report on Social Protection and Social Inclusion"; European Commission (2008) Telemedicine for the benefit of patients healthcare systems and society (2008) COM, p. 689; European Commission (2009) Telemedicine for the benefit of patients, healthcare systems and society (2009) Staff Working Paper SEC(2009)943; (2010) ICT Research. The Policy Perspective. Report from Information, , European Commission, Society & Media Unit; Rossi Mori, A., Mercurio, G., Verbicaro, R., Enhanced policies on Connected Health are essential to achieve accountable social and health systems (2012) Eur. J. ePractice, No. 15, , http://www.epractice.eu/en/journal/issues/, Special Issue on "Policy lessons from a decade of eGovernment, eHealth & eInclusion"; "Accelerating the Development of the eHealth Market in Europe" (2007) eHealth Taskforce report 2007, , http://ec.europa.eu/enterprise/policies/innovation/policy/lead-marketinitiative/eHealth/index_en.htm, European Commission; Rossi Mori, A., Freriks, G., A European perspective on the cultural and political context for EHR deployment (2005) Person-Centered Health Records - Toward Health-e-People. Health Informatics Series, , Springer Science+Business Media Inc. J.E. Demetriades, R.M. Kolodner, G.A. Christopherson (Eds.); Tamburis, O., Mangia, M., Contenti, M., Mercurio, G., Rossi Mori, A., The LITIS conceptual framework: measuring eHealth readiness and adoption dynamics across the Healthcare Organizations (2012) Health Technol., 2 (2), pp. 97-112. , http://rd.springer.com/article/10.1007/s12553-012-0024-5, June; eHealth ERA - Towards the Establishment of a European eHealth Research Area (2007) Deliverables, , http://www.ehealth-era.org/index.htm; Rossi Mori, A., Mazzeo, M., D'Auria, S., Deploying Connected Health among the Actors on Chronic Conditions (2009) Eur. J. ePractice, (8). , http://www.epractice.eu/files/European%20Journal%20epractice%20Volume%208_1.pdf, December; Centers for Medicare and Medicaid Services Medicare and medicaid programs (CMS) (2010) Electronic Health Record Incentive Program, , http://cms.gov/EHrIncentivePrograms/; Rossi Mori, A., Dandi, R., "The Influence of Technology on Long-Term Care Systems" (2012), http://www.ceps.be/category/book-series/enepri-policy-briefs, ENEPRI Policy Brief No. 10. European Network of Economic Policy Research Institutes, Bruxelles, February; Schmidt, A., Barbabella, F., Hoffmann, F., Lamura, G., "Analysis and Mapping of 52 ICT-based initiatives for family caregivers" (2011), CARICT Project, Deliverable 2.3, European Centre for Social Welfare Policy and Research; (2011) The technological solutions potentially involved in LTC activities", , ANCIEN Consortium. Deliverable D-IV.1; "The Content of the Electronic Health Record: Clinical Datasets for Continuity of Care and Pathology Networks," (2003), http://www.prorec.it/efmiStc/EFMI-STCrecommendations02c.doc, Recommendations agreed by the participants to the Special Topic Conference 2003 of the European Federation of Medical Informatics, Roma, 6th-7th October 2003; Rossi Mori, A., Consorti, F., Integration of clinical information across patient records: a comparison of mechanisms used to enforce semantic coherence (1998) IEEE Transactions on Information Technology in Biomedicine, 2 (4), pp. 243-253; Rossi Mori, A., Consorti, F., Galeazzi, E., Standards to support development of terminological systems for healthcare telematics (1998) Meth. Inform Med., 37, pp. 551-563; Rossi Mori, A., Consorti, F., Galeazzi, E., Merialdo, P., A second generation of terminological systems is coming (1997) Medical Informatics Europe '97, pp. 436-440. , IOS Press, Amsterdam, C. Pappas (Ed.); Rossi Mori, A., Consorti, F., Exploiting the terminological approach from CENTC251 to support interoperability of health record systems (1997) Int. J. Med. Inf., 48 (1-3), pp. 111-124; http://www.openehr.org/standards/cen.html, openEHR Foundation "EN13606 - a Standard for EHR System Communication"; http://wiki.hl7.org/index.php%3Ftitle=Detailed_Clinical_Models, [7HL] "Detailed Clinical Models"; "Realizing the Full Potential of Health Information Technology to Improve Healthcare for Americans: The Path Forward" (2011), http://ahier.blogspot.com/2011/01/pcast-report-workgroup-1-14-2011.html, PCAST Report Workgroup; http://en.wikipedia.org/wiki/Health_Level_7, Wikipedia "Health Level 7"; (2006) CEN TC251 "CONTSYS - A System of Concepts to Support Continuity of Care" EN 13940, , European Standardization Committee (CEN), Brussels; Hägglund, M., Chen, R., Koch, S., Modeling shared care plans using CONTsys and openEHR to support shared home care of elderly (2011) JAMIA, 18 (1), pp. 66-69. , 1; Hägglund, M., Henkel, M., Zdravkovic, J., Johannesson, P., Rising, I., Krakau, I., Koch, S., A new approach for goal-oriented analysis of healthcare processes (2010) Stud. Health Technol. Inform., 160, pp. 1251-1255; Hägglund, M., Scandurra, I., Koch, S., Scenarios to capture work processes in shared homecare - from analysis to application (2010) Int. J. Med. Inform., 79 (6), pp. e126-e134; Hägglund, M., Scandurra, I., Koch, S., Studying points of intersection - an analysis of information needs in shared homecare of elderly (2009) J. Inform. Technol. Healthcare, 7 (1), pp. 1-20; Rossi Mori, A., Cooperative development of the healthcare infostructure for Europe (2003) Connected Health. Thought Leaders. Essays from Health Innovators, , Premium Publishing, London, Kevin Dean (Ed.); Rossi Mori, A., EHealth deployment roadmap and roll-out planning: Guiding design principles (2008) Proceedings of the "eHealth Planning and Management Symposium 2008" - EuroRec Annual Conference 2008-11-03 Copenhagen in a joint meeting with EHTEL, , http://www.ehtel.org/forum/conferences/ehealth-planning; Rossi Mori, A., Mercurio, G., Palumbo, W., Paolini, I., Ruotolo, L., Focused profiles for chronic patients in integrated care and clinical governance (2008) 9th International HL7 Interoperability Conference - IHIC 2008, , http://www.hl7.org.gr/ihic2008/9o_congress/ihic_2008.html; http://en.wikipedia.org/wiki/Clinical_Document_Architecture, Wikipedia, "Clinical Document Architecture"; http://en.wikipedia.org/wiki/Continuity_of_Care_Document, Wikipedia, "Continuity of Care Document"; (2004) "Improving Chronic Disease Management", , http://www.dh.gov.uk/prod_consum_dh/groups/dh_digitalassets/@dh/@en/documents/digitalasset/dh_4075213.pdf, UK Department of Health; http://www.ehtel.org/activities/tasks-sources/task-force-sustainable-telemedicine-and-chronic-disease-management/, EHTEL - Task Force Sustainable Telemedicine & Chronic Disease Management; Wagner, E.H., Improving Chronic Illness Care: Translating Evidence Into Action (2002) JAMA, 288, p. 14. , October; (2006) Constitution of the World Health Organization" Basic Documents, , World Health Organization, WHO, Geneva, (Supplement) October; Østbye, T., Is there time for management of patients with chronic diseases in primary care? (2005) Ann. Fam. Med., 3 (3); Rigby, M., Health informatics as a tool to improve quality in non-acute care - new opportunities and a matching need for a new evaluation paradigm (1999) Int. J. Med. Inf., 56, pp. 141-150; (2011) "The WSD Programme Headlines Findings", , http://www.dh.gov.uk/dr_consum_dh/groups/dh_digitalassets/documents/digitalasset/dh_131689.pdf, UK Department of Health. December; "Map of medicine.", , http://www.mapofmedicine.com/, Map of Medicine Ldt; Consejeria de Salud, Junta de Andalucia. "Procesos Asistenciales Integrados", , http://www.juntadeandalucia.es/salud/servicios/procesos/; "Social Care Informatics meets Health Care Informatics - A Holistic Citizen-Centric Vision for Information and Communication Technologies to Support Personal Health" (2010), http://iig.umit.at/dokumente/n29.pdf, Declaration by the Members of the European Science Foundation Exploratory Workshop on Social Care Informatics and Holistic Health Care, Keele University, UK, July; Rigby, M., Hill, P., Koch, S., Keeling, D., Social care informatics as an essential part of holistic health care: a call for action (2011) IJMI, 80 (8), pp. 544-554; eHealth Initiative, "Centering on the Patient: How Electronic Health Records Enable Care Coordination" (2011), http://www.ehealthinitiative.org/issues/care-coordination/care-coordination-report.html; Rigby, M., Integrated record keeping as an essential aspect of a primary care led service (1998) Br. Med. J., 317, pp. 579-582; Rossi Mori, A., Integrating Care for Chronic Conditions through a lifelong EHR (2005) Proceedings of the International Conference "Improving Care for Chronic Conditions - the Added Value of eHealth", , http://www.ehtel.org/forum/conferences/event-2005-eHealth-added-value; Rossi Mori, A., Position Statement: "Connecting systems or connecting people?." Panel: "Ptolemaic vs. Copernican - How healthcare policies and re-organisation of care provision will influence the eHealth roadmaps" (2007) International Conference "Continuity, Collaboration, Communication: Challenges for Healthcare and Opportunities for eHealth", , http://www.ehtel.org/forum/conferences/roma-24-maggio-2007; Rossi Mori, A., Move Forwards with Continuity, Collaboration and Communication (2008) HIMSS-EMEA eMessenger, Issue of 2008-01-10, , http://emea.himss.org/eNewsletters/archive/2008/10_January.htm; Mori, R., Vision for a Europe-wide Semantically Interoperable eHealth Infrastructure. Deliverable RIDE D.3.2.1, 2006; Kaiser Permanente "HealthConnect® Electronic Health Record" http://xnet.kp.org/newscenter/aboutkp/healthconnect/index.html; "My Health-e-Vet", , http://www.myhealth.va.gov/, US Department of Veterans Affairs; http://www.maccabi-research.org/144.html, Maccabi Institute for Health Services Research. "The Information System As A Tool For Efficient Organizational Administration"; The Official Google Blog. (2011) "An update on Google Health and Google PowerMeter", , http://googleblog.blogspot.com/2011/06/update-on-google-health-and-google.html, (accessed 06.24.11); http://www.himss.org/StateDashboard/, HIMSS, "State HIT Dashboard"; "Health Information Exchange" http://en.wikipedia.org/wiki/Health_information_exchange, Wikipedia; Nace, D.K., Gartland, J., Providing accountability: accountable care concepts for providers (2011) Relay Health, , http://healthsystemcio.com/white-papers/providing-accountability-aco-concepts-for-providers/; http://www.ancien-longtermcare.eu/, ANCIEN Consortium, "A short introduction to ANCIEN - Assessing Needs of Care In European Nations"; Maggini, M., Raschetti, R., Rossi Mori, A., (2008) Requisiti informativi per un sistema di gestione integrata del diabete mellito di tipo 2 nell'adulto: documento di indirizzo, , http://www.epicentro.iss.it/igea/documenti/documentiIGEA.asp, Pensiero Scientifico Editore, Roma; Mazzeo, M., Agnello, P., Rossi Mori, A., "Role and Potential Influence of Technologies on the Most Relevant Challenges for Long-Term Care" (2012), http://www.ceps.be/category/bookseries/enepri-research-reports, ENEPRI Research Report No. 113. European Network of Economic Policy Research Institutes, Bruxelles, June; Rossi Mori, A., Ricci, F.L., "Report on Priority Topic Cluster One and recommendations: Patient Summary" (2007), http://www.ehealthera.%20org/publications/publications.htm, Deliverable D 2.3 of the European Project "eHealth ERA - Towards the Establishment of a European eHealth Research Area", Revision 1, FebruaryUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84875378600&doi=10.1016%2fj.ijmedinf.2012.09.003&partnerID=40&md5=2115cd915ccfc264d13445102212ab9c L52283660 2012-11-02 2013-04-08 L52283660 2012-11-02 2013-04-08 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Data depend on processes; processes depend on organizational models; organizational models depend on regulations and policies. This position paper envisages the future data scenarios and the related research needs by addressing this whole logical chain. A 'smarter health and wellness future' requires the proactive engagement of citizens and of their caregivers, and the cooperation of health professionals across care facilities, with intense usage of mobile communication and connected devices. This ecosystem of people and organizations is currently extremely fragmented. Technology offers the possibility to mediate among the different actors in order to build a functional care team around the specific needs of each individual, i.e. a 'virtual facility'.However, this requires policies and regulations in every jurisdiction that motivate providers and their organizations to collaborate among themselves and with citizens according to explicit individual plans of care provision, to share their goals and negotiate their respective roles with respect to each citizen. Once a collaborative organizational context is established within integrated care models, policy makers could identify a critical mass of relevant shared processes and isolate a set of 'Attention Points' with predictable actors, concerns, activities, and thus highly precise information needs. For each Attention Point, a template for a Context-Specific Profile of the patient could be produced, e.g. as an HL7-CDA schema that fully specifies the mandatory and optional (clinical) data useful to support the care processes and to manage governance indicators. In relation to these predictable Attention Points data sources can be aligned to achieve reasonable coherence and consistency. Attention to data quality can be improved in a context of systematic re-use of the same data by different actors in different contexts. From a collection of profiles it could be possible to set up the core of a multi-purpose "Policy-Oriented" Health Record (POHR), shared by the functional care team in the citizen's ecosystem. In fact, the shared management of selected clinical data should be no more based on the a posteriori extraction from the personal notes of each professional, but on the cooperative construction of a systemic resource, together with the administrative and organizational data, able to support the management of innovative, integrated care models. In addition, the policy-oriented focus on routine data within a set of predictable situations makes it possible to stratify an appropriate number of citizens into homogeneous classes and to produce timely indicators of processes and outcomes from routine data for governance purposes, e.g. to optimize the allocation of resources, to drive continuous education, or to promote epidemiological studies. © 2012 Elsevier Ireland Ltd. ER - TY - CONF T1 - A secure RBAC mobile agent access control model for healthcare institutions A1 - Santos-Pereira, C A1 - Augusto, A B A1 - Cruz-Correia, R A1 - Correia, M E Y1 - 2013/// KW - Access control models KW - Authentication KW - Bioinformatics KW - Diagnosis KW - Electronic data interchange KW - Health Information Systems (HIS) KW - Health care KW - Health care application KW - Health care providers KW - Health information systems KW - Healthcare institutions KW - Information Security KW - Interoperability KW - Legacy systems KW - Mobile agent KW - Mobile agents KW - Public key cryptography KW - Public key infrastructure KW - Role-Based Access Control (RBAC) KW - Role-based Access Control KW - Security of data KW - Societies and institutions KW - Systems interoperability SP - 349 EP - 354 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889049143&doi=10.1109%2FCBMS.2013.6627814&partnerID=40&md5=99e15b4d07260d7f38f443e6092904ce N1 - Cited By :7 Export Date: 10 September 2018 References: Vieira-Marques, P.M., Cruz-Correia, R.J., Robles, S., Cucurull, J., Navarro, G., Marti, R., Secure integration of distributed medical data using mobile agents (2006) Ieee Intelligent Systems, 21, pp. 47-54. , Nov-Dec; Katsikas, S.K., Health care management and information systems security: Awareness, training or education? (2000) Int J Med Inform, 60, pp. 129-135. , Nov; Cruz-Correia, R., Vieira-Marques, P., Costa, P., Ferreira, A., Oliveira-Palhares, E., Araujo, F., Costa-Pereira, A., Integration of hospital data using agent technologies - A case study (2005) Ai Communications, 18, pp. 191-200; Martins, R.A., Correia, M.E., Augusto, A.B., A Literature Review of Security Mechanisms Employed by Mobile Agents.; Chen, T.L., Chung, Y.F., Lin, F.Y.S., A study on agent-based secure scheme for electronic medical record system (2012) Journal of Medical Systems, 36, pp. 1345-1357. , Jun; Nikooghadam, M., Zakerolhosseini, A., Secure communication of medical information using mobile agents (2012) Journal of Medical Systems, 36, pp. 3839-3850. , Dec; Jansen, W., Karygiannis, T., (2000) NIST Special Publication 800-19 Mobile Agent Security; Hayrinen, K., Saranto, K., Nykanen, P., Definition, structure, content, use and impacts of electronic health records: A review of the research literature (2008) International Journal of Medical Informatics, 77, pp. 291-304. , May; Borselius, N., Mobile agent security (2002) Electronics Communication Engineering Journal, 14, pp. 211-218; (2012) HIMSS, , http://www.himss.org/ASP/index.asp, HIMSS; Analitics, H., (2012) Security of Patient Data, , USA April 2012; (2006) Health Informatics - Privilege Management and Access Control, , ISO/TS 22600-2:2006; Sandhu, R., Ferraiolo, D., Kuhn, R., The NIST model for role-based access control: Towards a unified standard (2000) The Proceedings of the Fifth ACM Workshop on Role-based Access Control, , presented at, Berlin, Germany; Ferreira, A., Cruz-Correia, R., Antunes, L., Chadwick, D., Access control: How can it improve patients' healthcare? (2007) Stud Health Technol Inform, 127, pp. 65-76; Ahn, G.-J., Lam, J., Managing privacy preferences for federated identity management (2005) Presented at the Workshop on Digital Identity Management, , Fairfax, VA, USA; Schneier, B., (1995) Applied Cryptography (2nd Ed.): Protocols, Algorithms, and Source Code in C, , New York, NY, USA: John Wiley & Sons, Inc; (2004) Security Audit and Access Accountability Message XML Data Definitions for Healthcare Applications, , The Internet Society, RFC 3881; (2009) Health Informatics - Electronic Health Record Communication, , ISO/TS 13606-4:2009; Ferreira, A., Chadwick, D., Zao, G., Farinha, P., Correia, R., Chilro, R., Antunes, L., How securely break into RBAC: The BTG-RBAC model (2009) Proceedings from 25th Annual Computer Security Applications Conference - ACSAC 2009; Sandhu, R.S., Samarati, P., Access-control - Principles and practice (1994) Ieee Communications Magazine, 32, pp. 40-48. , Sep RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In medical organizations, healthcare providers need to have fast access to patients' medical information in order to make accurate diagnoses as well as to provide appropriate treatments. Efficient healthcare is thus highly dependent on doctors being provided with access to patients' medical information at the right time and place. However it frequently happens that critical pieces of pertinent information end up not being used because they are located in information systems that do not inter-operate in a timely manner. Unfortunately the standard operational mode for many healthcare applications, and even healthcare institutions, is to be managed and operated as isolated islands that do not share information in an efficient manner. There are many reasons that contribute to this grim state of affairs, but what interests us the most is the lack of enforceable security policies for systems interoperability and data exchange and the existence of many heterogeneous legacy systems that are almost impossible to directly include into any reasonable secure interoperable workflow. In this paper we propose a RBAC mobile agent access control model supported by a specially managed public key infrastructure for mobile agent's strong authentication and access control. Our aim is to create the right means for doctors to be provided with timely accurate information, which would be otherwise inaccessible, by the means of strongly authenticated mobile agents capable of securely bridging otherwise isolated institutional eHealth domains and legacy applications. © 2013 IEEE. ER - TY - CONF T1 - Standard-based data and service interoperability in eHealth systems A1 - Sartipi, K A1 - Yarmand, M H Y1 - 2008/// KW - Administrative data processing KW - Application Servers KW - Artificial intelligence KW - Case studies KW - Clinical terminologies KW - Computer software maintenance KW - Decision Support Systems, Clinical KW - Decision support systems KW - Decision theory KW - Do-mains KW - Electric relays KW - Electronic medical equipment KW - HL7 KW - Health Care Costs KW - Health care information systems KW - Healthcare KW - Healthcare environments KW - Human computer interaction KW - Information Systems KW - Information representations KW - Information systems KW - Information theory KW - International standardizations KW - Interoperability KW - Interoperable KW - Legacy system KW - Legacy systems KW - Maintainability KW - Maintenance KW - Management information systems KW - Medical computing KW - Migration KW - National standards KW - Public healths KW - Real worlds KW - Semantic interoperability KW - Servers KW - Service interoperability KW - Service representations KW - Standardization KW - Standards KW - Terminology KW - Web services KW - World Wide Web SP - 187 EP - 196 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-57849083109&doi=10.1109%2FICSM.2008.4658067&partnerID=40&md5=beb344865d215d1029712d078a0e84e3 N1 - Cited By :9 Export Date: 10 September 2018 References: Canada Health Infoway, , www.infoway-inforoute.ca; www.compete-study.com, COMPETE official website; Gello official website, , www.gello.org; Health Level Seven ballot, , www.hl7.org/v3ballot/html/welcome/environment/index.htm; Health Level Seven official website, , www.hl7.org; www.regenstrief.org/medinformatics/loinc, LOINC official website; www.snomed.org, SNOMED official website; Berler, D.K.A., Pavlopoulos, S., Design of an interoperability framework in a regional healthcare system (2004) Engineering in Medicine and Biology Society, pp. 3093-3096; Grimson, J., Grimson, W., Hasselbring, W., The si challenge in health care (2000) Commun. ACM, pp. 48-55; HL7. Message development framework, December 1999. version 3.3; (2007) Bioinformatics and Bioengineering, pp. 1230-1234. , e. a. Hsieh. Middleware based inpatient healthcare information system; Infoway, C.H., EHRS Blueprint, an interoperable EHR framework (2006), April, v2; C. H. Infoway. iEHR Vocabulary Status, August 2006. IE50102-3004; C. H. Infoway. CeRx MIF View, July 2007. PN502-2003-V01R04.3; Infoway, C.H., (2007) CeRx Vocabulary Status, pp. PN502-P3004. , July; C. H. Infoway. CeRx XML Schemas, July 2007. PN502-2003-V01R04.3; C. H. Infoway. HL7 v3 pan-Canadian Messaging Standards - Implementation Guide 1 - Clinical Records, July 2007. v01R04.3; C. H. Infoway. HL7 v3 pan-Canadian Messaging Standards - Implementation Guide 1 - Pharmacy, July 2007. v01R04.2; C. H. Infoway. HL7 v3 pan-Canadian Messaging Standards - Implementation Guide 1 - Shared Interactions, July 2007. v01R04.3; C. H. Infoway. iEHR Message Definition Worksheet, April 2007. IE50102-0009; C. H. Infoway. iEHR Scope and Package Tracking Framework, April 2007. IE50102-PM99; Jin, D., Cordy, J.R., Integrating reverse engineering tools using a service-sharing methodology (2006) International Conference on Program Comprehension, pp. 94-99; Jin, D., Winter, A., Working session on interoperable reengineering services (2005) Program Comprehension,IWPC 2005, pp. 291-293; (2006) e-Health Networking, Applications and Services, pp. 152-156. , e. a. Li-Fan Ko. Hl7 middleware framework for healthcare information system; (2005) Oracle Healthcare Transaction Base - datasheet, , ORACLE, August; (2007), SNOMED clinical terms user guide, January; Souder, T., Mancoridis, S., A tool for securely integrating legacy systems into a distributed environment (1999) Reverse Engineering, pp. 47-55; e. a. T. H. Yang. A scalable multi-tier architecture for the national taiwan university hospital information system based on hl7 standard. In IEEE CBMS'06, pages 99-104, 2006; Weiping Wang, S.Z., Wang, M., Healthcare information system integration: A service oriented approach (2005) Services Systems and Services Management, pp. 1475-1480; Zou, Y., Kontogiannis, K., Towards a web-centric legacy system migration framework (2005) Software Maintenance RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - International standardization in information representation, organization, and dissemination are meant to eliminate the discrepancies in communication among participating organizations and institutions in a particular domain. The management of domain information will then allow different participants to integrate their legacy information or application servers to a nation-wide network and use widely approved services to communicate their proprietary data and services with a large group of clients. In this context, traditional healthcare information systems require fundamental re-engineering to new network-centric environments in order to reduce the huge costs of healthcare while maintaining the expected quality of public health. This integration using new HL7 v3 standards and leading-edge information technologies will be the initial steps for shifting towards an interoperable healthcare environment. This paper aims at addressing new challenges in standard-based interoperability provision among legacy healthcare information systems, while adhering to international and national standards for data and service representations. We introduce a framework to employ healthcare standards and clinical terminology systems to achieve semantic interoperability between distributed Electronic Medical Record (EMR) systems. A real world case study for integration of a Clinical Decision Support System (CDSS) with the EMR of a specialist will be presented. © 2008 IEEE. ER - TY - JOUR T1 - A Public Health Grid (PHGrid): Architecture and value proposition for 21st century public health A1 - Savel, T. A1 - Hall, K. A1 - Lee, B. A1 - McMullin, V. A1 - Miles, M. A1 - Stinn, J. A1 - White, P. A1 - Washington, D. A1 - Boyd, T. A1 - Lenert, L. Y1 - 2010/07// PB - Elsevier JF - International Journal of Medical Informatics VL - 79 IS - 7 SP - 523 EP - 529 DO - 10.1016/J.IJMEDINF.2010.04.002 UR - https://www.sciencedirect.com/science/article/pii/S1386505610000912?via%3Dihub L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Savel et al. - 2010 - A Public Health Grid (PHGrid) Architecture and value proposition for 21st century public health.pdf N2 - PURPOSE This manuscript describes the value of and proposal for a high-level architectural framework for a Public Health Grid (PHGrid), which the authors feel has the capability to afford the public health community a robust technology infrastructure for secure and timely data, information, and knowledge exchange, not only within the public health domain, but between public health and the overall health care system. METHODS The CDC facilitated multiple Proof-of-Concept (PoC) projects, leveraging an open-source-based software development methodology, to test four hypotheses with regard to this high-level framework. The outcomes of the four PoCs in combination with the use of the Federal Enterprise Architecture Framework (FEAF) and the newly emerging Federal Segment Architecture Methodology (FSAM) was used to develop and refine a high-level architectural framework for a Public Health Grid infrastructure. RESULTS The authors were successful in documenting a robust high-level architectural framework for a PHGrid. The documentation generated provided a level of granularity needed to validate the proposal, and included examples of both information standards and services to be implemented. Both the results of the PoCs as well as feedback from selected public health partners were used to develop the granular documentation. CONCLUSIONS A robust high-level cohesive architectural framework for a Public Health Grid (PHGrid) has been successfully articulated, with its feasibility demonstrated via multiple PoCs. In order to successfully implement this framework for a Public Health Grid, the authors recommend moving forward with a three-pronged approach focusing on interoperability and standards, streamlining the PHGrid infrastructure, and developing robust and high-impact public health services. ER - TY - CONF T1 - Connecting Personal Health Records Together with EHR Using Tangle A1 - Saweros, E A1 - Song, Y.-T. Y1 - 2019/// JF - Proceedings - 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2019 SP - 547 EP - 554 SN - 9781728116518 DO - 10.1109/SNPD.2019.8935646 N2 - ©2019 IEEE. Health Data Records Fragmentation across hospitals, labs, pharmacies, and general caregivers has been hurting medical services quality and patient outcome. The problem is getting worse as we have even more healthcare accesses from different sources such as mobile phones, wearable devices, etc. In an attempt to defragment health data, we are proposing the utilization of distributed transaction ledgers (DTL) technology by IOTA-Tangle which facilitates communication between patients and care providers. Through this technology the gap between health-care delivery and population health can be bridged so the quality of health services and patient outcomes may be improved. Our approach provides complete picture for each patient by sharing data between healthcare participants. ER - TY - CONF T1 - A dynamic web application within an n-tier architecture: A multi-source information system for end-stage renal disease A1 - Saäd, M B A1 - Simonet, A A1 - Guillon, D A1 - Jacquelinet, C A1 - Gaspoz, F A1 - Dufour, E A1 - Jais, J P A1 - Simonet, M A1 - Landais, P Y1 - 2003/// KW - Business logic KW - Data warehouse KW - Dynamic Web interface KW - Information Systems KW - Kidney Failure, Chronic KW - Multi-Source Infonnation System KW - end-stage renal disease KW - n-tier architecture VL - 95 SP - 95 EP - 100 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-14044264004&doi=10.3233%2F978-1-60750-939-4-95&partnerID=40&md5=2f291b3494a6e9bad26e98473da7f2f2 N1 - Cited By :13 Export Date: 10 September 2018 References: Landais, P., L'insuffisance rénale terminale en France : Offre de soms et prévention (2002) Presse Med., 31, pp. 176-85; Landais, P., Simonet, A., Guillon, D., Jacquelinet, C., Ben Said, M., Mugnier, C., Simonet, M., SIMS@rein : Un système d'information multi-sources pour l'insuffisance rénale terminale (2002) CR Biol, 325, pp. 515-528; Rindfleisch, T.C., Privacy, information technology, and health care (1997) Communications of the ACM August, 40, pp. 93-100; Kassem, N., (2000) Designing Enterprise Applications with the JavaTM 2 Platform, Enterprise Edition, p. 341. , Addison-Wesley New York; Marcus, A., (1992) Graphic Design for Electronic Documents and User Interfaces, p. 266. , ACM Press. New York; Nielsen, J., (2000) Designing Web Usability, p. 419. , New Riders Publ. Indianapolis; Dubois, P., MySQL (2000) Campuserve, p. 750. , Paris; Jones, K., An introduction to data warehousing: What are the implications for the network int (1998) J. Network Mgmt, 8, pp. 42-56; Kimball, R., (1996) The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses, p. 416. , John Wiley RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - A Multi-Source Information System (MSIS) has been designed for the Renal Epidemiology and Information Network (REIN) dedicated to End-Stage Renal Disease. Interoperability has been considered at 4 levels: semantics, network, formats and contents. An n-tier architecture has been chosen at the network level. It is made out ofa universal client, a dynamic Web server connected to a production database and to a data warehouse. The MSIS is patient-oriented, based on a regional organization. Its implementation in the context of a regional experimentation is presented with insights on the design and underlying technologies. The n-tier architecture is a robust model and flexible enough to aggregate multiple information sources and integrate modular developments. The data warehouse is dedicated to support health care decision-making. ER - TY - CONF T1 - DebugIT: Ontology-mediated layered data integration for real-time antibiotics resistance surveillance A1 - Schober, D A1 - Choquet, R A1 - Depraetere, K A1 - Enders, F A1 - Daumke, P A1 - Jaulent, M.-C. A1 - Teodoro, D A1 - Pasche, E A1 - Lovis, C A1 - Boekera, M Y1 - 2014/// KW - Anti-biotics resistance KW - Antibacterial drug resistance KW - Antibacterial drugs KW - Antibiotics KW - Antibiotics resistance KW - Biotics KW - Clinical information system KW - Data description KW - Data integration KW - Data linkage KW - Description logic KW - Domain ontologies KW - Drug therapy KW - Epidemiological monitoring KW - Hospitals KW - Infection monitoring KW - Interoperability KW - Medical computing KW - Medical information systems KW - Ontology KW - Ontology-based integrations KW - Public health surveil-lance KW - Query languages KW - Query processing KW - Search engines KW - Semantic Web KW - Semantic web KW - Social networking (online) VL - 1320 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920001166&partnerID=40&md5=67415a2b2e32e3120a6cc8de42c19a3c N1 - Export Date: 5 April 2018 N2 - Antibiotics resistance poses a significant problem in today's hospital care. Although large amounts of resistance data are gathered locally, they can-not be compared globally due to format and access diversity.We present an ontology-based integration approach serving an EU project in making antibiotics resistance data semantically and geographically interopera-ble. We particularly focus on EU-wide clinical data integration for real-time an-tibiotic resistance surveillance. The data semantics is formalized by multiple layers of terminology-bound description logic ontologies. Local database-to-RDF (D2R) converters, normalizers and data wrapper ontologies render hospi-tal data accessible to SPARQL queries, which populate a mediator layer. This semiformal data is then integrated and rendered comparable via formal OWL domain ontologies and rule-driven reasoning applications. The presented inte-gration layer enables clinical data miners to query over multiple hospitals which behave like one homogeneous 'virtual clinical information system'. We show how cross-site querying can be achieved across borders, languages and different data models. Aside the drawbacks, we elaborate on the unique advantages over comparable previous efforts, i.e. tackling real-time data access and scalability. ER - TY - JOUR T1 - The DebugIT core ontology: Semantic integration of antibiotics resistance patterns A1 - Schober, Daniel A1 - Boeker, Martin A1 - Bullenkamp, Jessica A1 - Huszka, Csaba A1 - Depraetere, Kristof A1 - Teodoro, Douglas A1 - Nadah, Nadia A1 - Choquet, Remy A1 - Daniel, Christel A1 - Schulz, Stefan Y1 - 2010/// KW - Anti-Bacterial Agents KW - Antibiotics KW - Drug Resistance, Microbial KW - Information storage and retrieval KW - Knowledge sharing KW - Ontology KW - Semantic heterogeneity KW - Semantics KW - Systems integrations JF - Studies in Health Technology and Informatics VL - 160 SP - 1060 EP - 1064 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Antibiotics resistance development poses a significant problem in today's hospital care. Massive amounts of clinical data are being collected and stored in proprietary and unconnected systems in heterogeneous format. The DebugIT EU project promises to make this data geographically and semantically interoperable for case-based knowledge analysis approaches aiming at the discovery of patterns that help to align antibiotics treatment schemes. The semantic glue for this endeavor is DCO, an application ontology that enables data miners to query distributed clinical information systems in a semantically rich and content driven manner. DCO will hence serve as the core component of the interoperability platform for the DebugIT project. Here we present DCO and an approach thet uses the semantic web query language SPARQL to bind and ontologically query hospital database content using DCO and information model mediators. We provide a query example that indicates that ontological querying over heterogeneous information models is feasible via SPARQL construct- and resource mapping queries. ER - TY - CONF T1 - Infrastructure for Innovative Research on Healthy Food Choice, Preparation and Consumption: A Position Paper on the RICHFIELDS project A1 - Seljak, B K A1 - Popp, K A1 - Finglas, P A1 - Timotijevic, L A1 - Vee, P V A1 - Zimmerman, K Y1 - 2019/// JF - Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019 SP - 5183 EP - 5185 SN - 9781728108582 DO - 10.1109/BigData47090.2019.9006393 N2 - ©2019 IEEE. This paper presents the recently finished EU-funded RICHFIELDS project aimed to design a new research infrastructure that would foster research in the areas of food and nutrition with a focus on consumers' behavior and lifestyle. In this project, an architecture of a new consumer data platform was designed and discussed from the researchers, business, management, ethical and legal points of view. Also new methodology for supporting big and open data standardization and interoperability was developed. ER - TY - CONF T1 - HAIKU: A semantic framework for surveillance of healthcare-associated infections A1 - Shaban-Nejad, A A1 - Riazanov, A A1 - Charland, K M A1 - Rose, G W A1 - Baker, C J O A1 - Tamblyn, R A1 - Forster, A J A1 - Buckeridge, D L Y1 - 2012/// KW - Biomedical Ontologies KW - Hospital acquired infection KW - Knowledge processing in pervasive healthcare envir KW - Recommender Systems KW - Semantic Web KW - Web Ontology Language (OWL) VL - 10 SP - 1073 EP - 1079 DO - 10.1016/j.procs.2012.06.151 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84896957757&doi=10.1016%2Fj.procs.2012.06.151&partnerID=40&md5=eee4aa45f308fd3140cb87ee53480953 N1 - Cited By :3 Export Date: 5 April 2018 N2 - Healthcare-Associated Infections (HAI) impose a substantial health and financial burden. Surveillance for HAI is essential to develop and evaluate prevention and control efforts. The traditional approaches to HAI surveillance are often limited in scope and efficiency by the need to manually obtain and integrate data from disparate paper charts and information systems. The considerable effort required for discovery and integration of relevant data from multiple sources limits the current effectiveness of HAI surveillance. Knowledge-based systems can address this problem of contextualizing data to support integration and reasoning. In order to facilitate knowledge-based decision making in this area, availability of a reference vocabulary is crucial. The existing terminologies in this domain still suffer from inconsistencies and confusion in different medical/clinical practices, and there is a need for their further improvement and clarification. To develop a common understanding of the infection control domain and to achieve data interoperability in the area of hospital-acquired infections, we present the HAI Ontology (HAIO) to improve knowledge processing in pervasive healthcare environments, as part of the HAIKU (Hospital Acquired Infections - Knowledge in Use) system. The HAIKU framework assists physicians and infection control practitioners by providing recommendations regarding case detection, risk stratification and identification of diagnostic factors. © 2012 Published by Elsevier Ltd. ER - TY - JOUR T1 - PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data A1 - Shaban-Nejad, Arash A1 - Lavigne, Maxime A1 - Okhmatovskaia, Anya A1 - Buckeridge, David L. Y1 - 2017/01// KW - Article KW - Biological Ontologies KW - Computer-Assisted KW - Data Mining KW - Decision Making KW - Electronic Health Records KW - Evidence-Based Medicine KW - Health Status Indicators KW - Humans KW - Image Interpretation KW - Internet KW - Public Health Informatics KW - Software KW - Software Design KW - Systems Integration KW - architecture KW - biological ontology KW - chronic disease KW - computer assisted diagnosis KW - data analysis KW - data mining KW - data processing KW - decision support system KW - electronic health record KW - evidence based medicine KW - evidence based practice KW - health care system KW - health data analytics KW - health informatics KW - health status indicator KW - health survey KW - human KW - knowledge KW - medical decision making KW - medical informatics KW - medical information system KW - population health record KW - population health surveillance KW - procedures KW - public health KW - semantic data modeling KW - semantics KW - software KW - software design KW - system analysis KW - trends PB - Wiley/Blackwell (10.1111) JF - Annals of the New York Academy of Sciences VL - 1387 IS - 1 SP - 44 EP - 53 DO - 10.1111/nyas.13271 UR - http://doi.wiley.com/10.1111/nyas.13271 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991677366&doi=10.1111%2Fnyas.13271&partnerID=40&md5=3007437bb50d8f0d97bdddad13b83464 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Shaban-Nejad et al. - 2017 - PopHR a knowledge-based platform to support integration, analysis, and visualization of population health d.pdf N1 - From Duplicate 2 (PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data - Shaban-Nejad, A; Lavigne, M; Okhmatovskaia, A; Buckeridge, D L) Cited By :3 Export Date: 5 April 2018 N2 - Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy fromheterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction ofmassive amounts of heterogeneous data frommultiple distributed sources (e.g., administrativedata, clinical records, and survey responses) to support themeasurementand monitoring of population health and health systemperformance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platformand discuss the architecture, design, keymodules, and its implementation and use ER - TY - CHAP T1 - Design and development of standards (HL7 V3) based enterprise architecture for public health programs integration at the county of Los Angeles A1 - Shakir, A.-M. A1 - Cardenas, D A1 - Datta, G A1 - Mittra, D A1 - Basu, A A1 - Verma, R Y1 - 2008/// KW - Application programs KW - Data integration KW - Design and Development KW - Electronic data exchange KW - Electronic data interchange KW - Enterprise Architecture KW - Health KW - Health projects KW - Health risks KW - Hydrogen-Ion Concentration KW - Information networks KW - Information services KW - Interoperability KW - Management tool KW - Network architecture KW - Public health KW - Service oriented architecture (SOA) KW - Standardization KW - Web-based applications KW - Web-based tools KW - Websites JF - Medical Informatics: Concepts, Methodologies, Tools, and Applications VL - 1 SP - 500 EP - 512 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018567513&doi=10.4018%2F978-1-60566-050-9.ch039&partnerID=40&md5=be81b215630860bb89ae0bfaf5c6804c N1 - Export Date: 10 September 2018 References: Arsanjani, A., (2004) Service-Oriented modeling and architecture: How to identify, specify, and realize services for your SOA, , IBM; (2002) Public health information technology, functions and specifications, , http://www.cdc.gov/cic/functionsspecs/IT_FunctionsSpecifications_final_21402.pdf, (for emergency preparedness and bioterrorism) (February 2002); (2005) Web sphere integration reference architecture: A service-based foundation for enterprise reference architecture; Klein, J., Integrating (2005) electronic health records Using HL7 clinical document architecture (2005) Business Integration Journal; (2003) SARS-EDS Software Requirement Specifications v1.0.2, , SARS-EDS Functional Document v1.0.2; (2003) PHIS Action Plan for Bio-terrorism Preparedness Initiative, , The application of NEDSS architecture to Public Health Information systems in Los Angeles County; (2005) ODS and ODSAPI design and architecture documents; (2004) Bio-terrorism Preparedness and Response Initiative, , The application of PHIN Standards & NEDSS Architecture towards integrating Pubic Health Information Systems in Los Angeles County -Program Plan; Mead, C., Data interchange standards in healthcare IT-Computable semantic interoperability: Now possible but still difficult, do we really need a better mousetrap? (2005) Journal of Healthcare Information Management, 20 (1), pp. 71-78; (2004) The surveillance and monitoring component of the public health information network, , http://www.cdc.gov/nedss; (2004) An overview, , http://www.cdc.gov/phin/index.html; Regio, M., Greenfield, J., Design and implement a software factory (2006) The Architecture Journal, p. 6; Schuschel, H., Weske, M., Infrastructure for Collaborative Enterprises (2004) In Proceedings of the 13th IEEE International Workshops on Enabling Technologies (WETICE'04), pp. 75-80; Spewak, S., Hill, S., (1992) Enterprise architecture planning publishers, , John Wiley and Sons; Sprott, D., The business case for service oriented architecture (2004) CBDI Journal, pp. 3-11; Tsai, W.T., Chen, Y., Fan, C., PESOI: Process Embedded Service-Oriented Architecture (2006) Journal of Software, 17 (6), pp. 1470-1484; Utschig, C., Rodriguez, J., Buelow, H., Practical interoperability approaches, WS-Security and WS-Addressing Explained (2006) SOA Webservices Journal; Verma, R., Shakir, A.M., Cardenas, D., Mittra D.Marwaha, A., Datta, G., Integrated disease surveillance application in a standards (HL7 V3) based public health information network (2005) The Journal on Information Technology in Healthcare, 3 (6) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public Health (PH) applications in County of Los Angeles (LAC), Department of PH have been developed to meet individual PH program's goals. This resulted in lack of county-wide PH data integration, efficiency, and usefulness. LAC encouraged the development of web-based applications utilizing standards-based PH Information Network interoperable service-oriented architecture (SOA). The goal was to stop the evolution of fragmented health data systems which place limitations on the PH mission of safeguarding and improving the health of the community as well as responding to large-scale threats to PH. PH Nursing case management is one example of LAC's initiative for promotion of web-based tools which will be utilized within this SOA. This PH architecture is capable of supporting electronic data exchange from PH partners using a HL7 integration hub. It promotes the development of management tools and applications to assist PH response and recovery activities while providing resources to support departmental integration. © 2009 by IGI Global. All rights reserved. ER - TY - JOUR T1 - Designing a communication protocol for acquired immunodeficiency syndrome information exchange A1 - Shanbehzadeh, M A1 - Abdi, J A1 - Ahmadi, M Y1 - 2019/// JF - Journal of Education and Health Promotion VL - 8 IS - 1 SP - 99 EP - 99 DO - 10.4103/jehp.jehp_2_19 N2 - ©2020 BioMed Central Ltd.. All rights reserved. INTRODUCTION: Interoperability will provide similar understanding on the meaning of communicated messages to intelligent systems and their users. This feature is essential for controlling and managing contagious diseases which threaten public health, such as acquired immunodeficiency syndrome (AIDS). The aim of this study was also designing communication protocols for normalizing the content and structure of intelligent messages in order to optimize the interoperability. MATERIALS AND METHODS: This study used a checklist to extract information content compatible with minimum data set (MDS) of AIDS. After coding information content through selected classification and nomenclature systems, the reliability and validity of codes were evaluated by external agreement method. The MindMaple software was used for mapping the information content to Systematized Nomenclature of Medicine-Clinical Terminology (SNOMED-CT) integrated codes. Finally, the Clinical Document Architecture (CDA) format was used for standard structuring of information content. RESULTS: The information content standard format, compatible selected classification, or nomenclature system and their codes were determined for all information contents. Their corresponding codes in SNOMED-CT were structured in the form of CDA body and title. CONCLUSION: The complex and multidimensional nature of AIDS requires the participation of multidisciplinary teams from different organizations, complex analyzes, multidimensional and complex information modeling, and maximum interoperability. In this study, the use of CDA structure along with SNOMED-CT codes is completely compatible with optimal interoperability needs for AIDS control and management. ER - TY - JOUR T1 - Evaluating public health uses of health information exchange A1 - Shapiro, Jason S. Y1 - 2007/12// KW - Antibiotics KW - Electronic health records KW - Evaluation studies KW - Health KW - Health information exchange KW - Health information exchange (HIE) KW - Information Dissemination KW - Information Systems KW - Information analysis KW - Interoperability KW - Medical Informatics KW - Program Evaluation KW - Public Health Informatics KW - Public health KW - United States KW - antibiotic resistance KW - antibiotic sensitivity KW - article KW - electronic data interchange KW - health survey KW - human KW - medical informatics KW - medical record KW - physician attitude KW - priority journal KW - public health service PB - Academic Press JF - Journal of Biomedical Informatics VL - 40 IS - 6 SUPPL. SP - S46 EP - S49 DO - 10.1016/j.jbi.2007.08.003 UR - https://www.sciencedirect.com/science/article/pii/S1532046407000810?via%3Dihub UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-36048961558&doi=10.1016%2Fj.jbi.2007.08.003&partnerID=40&md5=806dc3e170bea312aa296974a8898b3c L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Shapiro - 2007 - Evaluating public health uses of health information exchange.pdf N1 - From Duplicate 2 (Evaluating public health uses of health information exchange - Shapiro, J S) Cited By :18 Export Date: 5 April 2018 N2 - Health information exchange (HIE) initiatives are in various stages of development across the United States. They aim to bring previously unavailable clinical data from patients' disparate health records, which may be spread over multiple provider and payer networks, to the point of care where clinicians and their patients need it most. The implications of these initiatives on public health are numerous. This article provides general evaluation methods for measuring the impact of HIE on public health in six use cases: (1) mandated reporting of laboratory diagnoses, (2) mandated reporting of physician-based diagnoses, (3) public health investigation, (4) disease-based non-reportable laboratory data, (5) antibiotic-resistant organism surveillance, and (6) population-level quality monitoring. © 2007 Elsevier Inc. All rights reserved. ER - TY - BOOK T1 - A Study on Blockchain Applications in Healthcare A1 - Sharma, A A1 - Hung, Y.-H. A1 - Agarwal, P A1 - Kalra, M Y1 - 2019/// JF - Lecture Notes in Electrical Engineering VL - 542 SP - 623 EP - 628 SN - 9789811336478 DO - 10.1007/978-981-13-3648-5_75 N2 - ©2019, Springer Nature Singapore Pte Ltd. Blockchain or the distributed ledger technology has the power to transform various industries including healthcare. It reduce or abolish the friction and costs of current intermediaries present in network. Decentralized and programmable nature of blockchain applications can be used for the betterment of public and private healthcare system. It has the ability to transform health care, placing the patient at the center of the healthcare ecosystem and increasing the security, privacy, and interoperability of information related to health. It creates various opportunities to reduce complexity, enable trustless collaboration, and create secure and immutable information. Management of electronic health record, conserving patient identification, insurance claiming process, frauds in public programs like medicaid and medicare and prevention of counterfeit drugs are the areas where the use of this new technology is particularly beneficial. Many organizations and research groups are working on resolving issues like interoperability, privacy and security of data, frauds in medicaid program, counterfeit drugs, that plague health IT and have come up with various blockchain solutions to it. We present some of the blockchain solutions, ongoing projects and case studies in this paper. ER - TY - JOUR T1 - Improving the value of clinical research through the use of Common Data Elements A1 - Sheehan, J A1 - Hirschfeld, S A1 - Foster, E A1 - Ghitza, U A1 - Goetz, K A1 - Karpinski, J A1 - Lang, L A1 - Moser, R P A1 - Odenkirchen, J A1 - Reeves, D A1 - Rubinstein, Y A1 - Werner, E A1 - Huerta, M Y1 - 2016/// KW - Biomedical Research KW - Common Data Elements KW - Cross-Over Studies KW - Data Collection KW - Humans KW - Information Dissemination KW - National Institutes of Health (U.S.) KW - Review KW - United States KW - accuracy KW - clinical practice KW - clinical research KW - clinical trial (topic) KW - common data elements KW - confidentiality KW - cross-sectional study KW - data aggregation KW - data collection KW - data sharing KW - data standards KW - health program KW - human KW - information dissemination KW - information processing KW - information science KW - interoperability KW - medical information system KW - medical research KW - national health organization KW - priority journal KW - quality control KW - questionnaire KW - reliability KW - reproducibility KW - standard KW - training KW - trend study KW - validity JF - Clinical Trials VL - 13 IS - 6 SP - 671 EP - 676 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85001018492&doi=10.1177%2F1740774516653238&partnerID=40&md5=60e30a4fa7a7db5d8b94e9a8f05c3e0b L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Sheehan et al. - 2016 - Improving the value of clinical research through the use of Common Data Elements.pdf N1 - Cited By :10 Export Date: 10 September 2018 References: Silva, J., Wittes, R., Role of clinical trials informatics in the NCI's cancer informatics infrastructure (1999) Proc AMIA Symp, pp. 950-954; (2015) What Is A CDE?, , http://www.nlm.nih.gov/cde/glossary.html#cdedefinition, National Institutes of Health. (accessed 9 September 2015); (2015) Glossary, , http://www.nlm.nih.gov/cde/glossary.html, National Institutes of Health. (accessed 9 September 2015); Cox, J.H., Ferrari, G., Kalams, S.A., Results of an ELISPOT proficiency panel conducted in 11 laboratories participating in international human immunodeficiency virus type 1 vaccine trials (2005) AIDS Res Hum Retroviruses, 21, pp. 68-81; Janetzki, S., Panageas, K.S., Ben-Porat, L., Results and harmonization guidelines from two large-scale international Elispot proficiency panels conducted by the Cancer Vaccine Consortium (CVC/SVI) (2008) Cancer Immunol Immunother, 57, pp. 303-315; Check, D.K., Weinfurt, K.P., Dombeck, C.B., Use of central institutional review boards for multicenter clinical trials in the United States: A review of the literature (2013) Clin Trials, 10, pp. 560-567; Slutsman, J., Hirschfeld, S., A federated model of IRB review for multi-site studies: A report on the national children's study federated IRB Initiative (2014) IRB: Ethics Hum Res, 36, pp. 1-6; Mandl, K.D., Kohane, I.S., Federalist principles for healthcare data networks (2015) Nat Biotechnol, 33, pp. 360-363; Silva, J.S., Ball, M.J., Douglas, J.V., Translating cancer research into cancer care: Final report of the Long Range Planning Committee (2002) Cancer Informatics Essential Technologies for Clinical Trials, pp. 5-16. , Long Range Planning Committee. In: (eds). New York: Springer; Rubinstein, Y., McInnes, P., NIH/NCATS/GRDR® Common Data Elements: A leading force for standardized data collection (2015) Contemp Clin Trials, 20, pp. 78-80; Ghitza, U.E., Gore-Langton, R.E., Lindblad, R., NIDA clinical trials network Common Data Elements initiative: Advancing big-data addictive-disorders research (2015) Front Psychiatry, 6, p. 33; (2015) Guidance to Encourage the Use of CDEs, , http://www.nlm.nih.gov/cde/policyinformation.html, National Institutes of Health. (accessed 9 September 2015); (2015) NINDS Common Data Elements, , https://commondataelements.ninds.nih.gov, National Institutes of Health. (accessed 9 September 2015) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The use of Common Data Elements can facilitate cross-study comparisons, data aggregation, and meta-analyses; simplify training and operations; improve overall efficiency; promote interoperability between different systems; and improve the quality of data collection. A Common Data Element is a combination of a precisely defined question (variable) paired with a specified set of responses to the question that is common to multiple datasets or used across different studies. Common Data Elements, especially when they conform to accepted standards, are identified by research communities from variable sets currently in use or are newly developed to address a designated data need. There are no formal international specifications governing the construction or use of Common Data Elements. Consequently, Common Data Elements tend to be made available by research communities on an empiric basis. Some limitations of Common Data Elements are that there may still be differences across studies in the interpretation and implementation of the Common Data Elements, variable validity in different populations, and inhibition by some existing research practices and the use of legacy data systems. Current National Institutes of Health efforts to support Common Data Element use are linked to the strengthening of National Institutes of Health Data Sharing policies and the investments in data repositories. Initiatives include cross-domain and domain-specific resources, construction of a Common Data Element Portal, and establishment of trans-National Institutes of Health working groups to address technical and implementation topics. The National Institutes of Health is seeking to lower the barriers to Common Data Element use through greater awareness and encourage the culture change necessary for their uptake and use. As National Institutes of Health, other agencies, professional societies, patient registries, and advocacy groups continue efforts to develop and promote the responsible use of Common Data Elements, particularly if linked to accepted data standards and terminologies, continued engagement with and feedback from the research community will remain important. © The Author(s) 2016. ER - TY - JOUR T1 - Experience and challenge on interoperability of big data in health care A1 - Shengfeng, W A1 - Yi, N A1 - Liming, L Y1 - 2020/// JF - Chinese Journal of Endemiology VL - 41 IS - 2 SP - 303 EP - 309 DO - 10.3760/cma.j.issn.0254-6450.2020.02.005 N2 - ©2020 Chinese Medical Association. All rights reserved. Problems in interoperability is the biggest barrier limiting the use of big data in health care worldwide. Interoperability contains five dimensions: Business, security, ethics, semantics and technology. Based on the comparison of the three common interoperability models led by government, enterprise or research institution, and the current status of big data development in China, this paper proposes a new operation model which can be led by university, aided by enterprise and supported by government, and summarizes the three major challenges in the development of big data interoperability in China: Professional standard and specification, data security and ethics, incentive mechanism and assessment. Only when a feasible model is adopted, technical difficulties are overcome and data are truly shared, we can achieve maximized integration of multi-source data, expanding its application fields and establish a multi-business mode to comprehensively improve the population based health decision-making and management. ER - TY - JOUR T1 - Digital health and the state of interoperable electronic health records A1 - Shull, J G Y1 - 2019/// JF - Journal of Medical Internet Research VL - 21 IS - 11 DO - 10.2196/12712 N2 - ©Jessica Germaine Shull. Digital health systems and innovative care delivery within these systems have great potential to improve national health care and positively impact the health outcomes of patients. However, currently, very few countries have systems that can implement digital interventions at scale. This is partly because of the lack of interoperable electronic health records (EHRs). It is difficult to make decisions for an individual or population when the data on that person or population are dispersed over multiple incompatible systems. This viewpoint paper has highlighted some key obstacles of current EHRs and some promising successes, with the goal of promoting EHR evolution and advocating for frameworks that develop digital health systems that serve populations—a critical goal as we move further into this data-rich century with an ever-increasing number of patients who live longer and depend on health care services where resources may already be strained. This paper aimed to analyze the evolution, obstacles, and current landscape of EHRs and identify fundamental areas of hindrance for interoperability. It also aimed to highlight countries where advances have been made and extract best practices from these examples. The obstacles to EHR interoperability are not easily solved, but improving the current situation in countries where a national policy is not in place will require a focused inquiry into solutions from various sources in the public and private sector. Effort must be made on a national scale to seek solutions for optimally interoperable EHRs beyond status quo solutions. A list of considerations for best practices is suggested. ER - TY - JOUR T1 - A fog computing-based architecture for medical records management A1 - Silva, C.-C.A. A1 - Aquino, G S A1 - Melo, S R M A1 - Egdio, D J B Y1 - 2019/// JF - Wireless Communications and Mobile Computing VL - 2019 DO - 10.1155/2019/1968960 N2 - ©2019 Cícero A. Silva et al. The aging of the world's population and the growth in the number of people with chronic diseases have increased expenses with medical care. Thus, the use of technological solutions has been widely adopted in the medical field to improve the patients' health. In this context, approaches based on Cloud Computing have been used to store and process the information generated in these solutions. However, using Cloud can create delays that are intolerable for medical applications. Thus, the Fog Computing paradigm emerged as an alternative to overcome this problem, bringing computation and storage closer to the data sources. However, managing medical data stored in Fog is still a challenge. Moreover, characteristics of availability, performance, interoperability, and privacy need to be considered in approaches that aim to explore this problem. So, this article shows a software architecture based on Fog Computing and designed to facilitate the management of medical records. This architecture uses Blockchain concepts to provide the necessary privacy features and to allow Fog Nodes to carry out the authorization process in a distributed way. Finally, this paper describes a case study that evaluates the performance, privacy, and interoperability requirements of the proposed architecture in a home-centered healthcare scenario. ER - TY - CONF T1 - A big data architecture for the extraction and analysis of EHR data A1 - Silvestri, S A1 - Esposito, A A1 - Gargiulo, F A1 - Sicuranza, M A1 - Ciampi, M A1 - De Pietro, G Y1 - 2019/// JF - Proceedings - 2019 IEEE World Congress on Services, SERVICES 2019 SP - 283 EP - 288 SN - 9781728138510 DO - 10.1109/SERVICES.2019.00082 N2 - ©2019 IEEE. In the current Italian eHealth scenario, a national IT platform has been designed and developed with the purpose of ensuring the interoperability between the various Electronic Health Record (EHR) systems that have been adopted in the different regions of the country, according to the requirements provided by Italian Laws. In this way, the healthcare providers and the policy makers can acquire and process the data of a patient despite its initial format and source, allowing an improved quality of patient care and optimizing the management of the financial resources. To further exploit this huge resource of health and social data, it is very important to allow the extraction of the complex information buried under the Big Data source enabled by the EHRs, providing the physicians, the researchers and public health policy makers with innovative instruments. Meeting this need is not a trivial task, due to the difficulties of processing different document formats and processing Natural Language text, alongside to the problems related to the data size. In this paper we propose a Big Data architecture that is able to extract information from the documents acquired by the EHRs, integrate and process them, providing a set of valuable data for both physicians and patients, as well as decision makers. ER - TY - JOUR T1 - Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies A1 - Sinaci, A A A1 - Laleci Erturkmen, G B A1 - Gonul, S A1 - Yuksel, M A1 - Invernizzi, P A1 - Thakrar, B A1 - Pacaci, A A1 - Cinar, H A A1 - Cicekli, N K Y1 - 2015/// KW - Article KW - Electronic Health Records KW - Humans KW - Internet KW - Italy KW - Product Surveillance, Postmarketing KW - common data elements KW - electronic health record KW - electronic medical record KW - human KW - information model KW - information retrieval KW - information system KW - postmarketing surveillance JF - BioMed Research International VL - 2015 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946012618&doi=10.1155%2F2015%2F976272&partnerID=40&md5=d8bd08dd947768a832d1702483013e15 N1 - Cited By :1 Export Date: 10 September 2018 References: Hauben, M., Bate, A., Data mining in pharmacovigilance (2009) Pharmaceutical Data Mining: Approaches and Applications for Drug Discovery, 6; Norén, G.N., Orre, R., Bate, A., Edwards, I.R., Duplicate detection in adverse drug reaction surveillance (2007) Data Mining and Knowledge Discovery, 14 (3), pp. 305-328; Suling, M., Pigeot, I., Signal detection and monitoring based on longitudinal healthcare data (2012) Pharmaceutics, 4 (4), pp. 607-640; Nelson, J.C., Cook, A.J., Yu, O., Zhao, S., Jackson, L.A., Psaty, B.M., Methods for observational post-licensure medical product safety surveillance (2015) Statistical Methods in Medical Research, 24 (2), pp. 177-193; Strom, B.L., Kimmel, S.E., Hennessy, S., The future of pharmacoepidemiology (2013) Textbook of Pharmacoepidemiology, pp. 447-454; Platt, R., Wilson, M., Chan, K.A., Benner, J.S., Marchibroda, J., McClellan, M., The new sentinel network-improving the evidence of medical-product safety (2009) The New England Journal of Medicine, 361 (7), pp. 645-647; Hauben, M., Bate, A., Decision support methods for the detection of adverse events in post-marketing data (2009) Drug Discovery Today, 14 (7-8), pp. 343-357; Consortium, S., SALUS: Scalable, standard based interoperability framework for sustainable proactive post market safety studies. A brief overview of SALUS interoperability approach Whitepaper, 2012, , http://www.salusproject.eu/docs/SALUSwhitepaper-Final.pdf; Coorevits, P., Sundgren, M., Klein, G.O., Electronic health records: New opportunities for clinical research (2013) Journal of Internal Medicine, 274 (6), pp. 547-560; Behrman, R.E., Benner, J.S., Brown, J.S., McClellan, M., Woodcock, J., Platt, R., Developing the sentinel system-a national resource for evidence development (2011) The New England Journal of Medicine, 364 (6), pp. 498-499; Robb, M.A., Racoosin, J.A., Sherman, R.E., The US food and drug administration's sentinel initiative: Expanding the horizons of medical product safety (2012) Pharmacoepidemiology and Drug Safety, 21 (1), pp. 9-11; Foundation for National Institutes of Health, Observational Medical Outcomes Partnership (OMOP), , http://omop.org/; National Institute for Health Research, Clinical Practice Research Datalink (CPRD), , http://www.cprd.com/; (2013) University College London, the Health Improvement Network (THIN), , http://www.ucl.ac.uk/pcph/research-groupsthemes/thin-pub; (2014) Translational Research and Patient Safety in Europe (TRANSFoRm), , http://www.transformproject.eu/; (2014) Electronic Health Record Systems for Clinical Research (EHR4CR), , http://www.ehr4cr.eu/; DeStefano, F., The vaccine safety datalink project (2001) Pharmacoepidemiology and Drug Safety, 10 (5), pp. 403-406; Murphy, S.N., Weber, G., Mendis, M., Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) (2010) Journal of TheAmericanMedical Informatics Association, 17 (2), pp. 124-130; Sinaci, A.A., Laleci Erturkmen, G.B., A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains (2013) Journal of Biomedical Informatics, 46 (5), pp. 784-794; (2013) Integrating the Healthcare Enterprise (IHE), Data Element Exchange (DEX) Profile, Trial Implementation, , http://www.ihe.net/uploadedFiles/Documents/QRPH/IHEQRPHSupplDEX.pdf; (2014) World Wide Web Consortium (W3C), Resource Description Framework (RDF), , http://www.w3.org/RDF/, WorldWideWeb Consortium (W3C); (2014) Health Level 7 (HL7)/American Society for Testing and Materials (ASTM), , http://www.hl7.org/documentcenter/publictempDC68F8CB-1C23-BA17-0CB6B9727B87B502/pressreleases/20070212.pdf, Continuity of Care Document (CCD); (2008) The European Committee for Standardization (CEN) and International StandardizationOrganization (ISO), Health Informatics-Electronic Health Record Communication (EN 13606), the European Committee for Standardization (CEN), International Standardization Organization (ISO); (2014) Clinical Data Interchange Standards Consortium (CDISC), Study Data Tabulation Model (SDTM), , http://www.cdisc.org/sdtm; Yuksel, M., Gonul, S., Erturkmen, G.B.L., Demonstration of the SALUS semantic interoperability framework for case series characterization studies (2013) SWAT4LS; (2014), http://www.hitsp.org/ConstructSetDetails.aspx?&PrefixAlpha=4&PrefixNumeric=154, Healthcare Information Technology Standards Panel (HITSP), C154:HITSPData Dictionary; Sinaci, A.A., (2014) Data Interoperability Through Federated Semantic Metadata Registries, , [Ph. D. Thesis], Middle East Technical University, Ankara, Turkey; (2014) InternationalOrganization for Standardization (ISO) and International Electrotechnical Commission (IEC), ISO/IEC 11179: Information Technology-Metadata Registries (MDR) Parts 1-6, International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), , 2nd edition; SALUS Deliverable 4. 2. 2-SALUS Common Set of Data Elements for Post Market Safety Studies-R2, , http://www.salusproject.eu/docs/D4.2.2.pdf; (2014) SPARQL Query Language for RDF, , http://www.w3.org/TR/rdf-sparql-query/, World Wide Web Consortium (W3C); (2010) SAS 9. 2 Language Reference: Concepts, , SAS Institute Inc, SAS Institute Inc. , Cary, NC, USA, 2nd edition; (2014) XML Path Language (Xpath), , http://www.w3.org/TR/xpath/, World Wide Web Consortium (W3C); (2014) International Conference on Harmonisation (ICH), Medical Dictionary for Regulatory Activities (MedDRA), , http://www.meddra.org/; Klann, J.G., Buck, M.D., Brown, J., Query health: Standards-based, cross-platform population health surveillance (2014) Journal of the AmericanMedical Informatics Association, 21 (4), pp. 650-656; Yen, P.-Y., Wantland, D., Bakken, S., Development of a customizable health IT usability evaluation scale (2010) AMIA Annual Symposium Proceedings, 2010, pp. 917-921 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: duplicated? N2 - Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases. © 2015 A. Anil Sinaci et al. ER - TY - JOUR T1 - A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains A1 - Sinaci, A Anil A1 - Laleci Erturkmen, Gokce B Y1 - 2013/// KW - Registries KW - Semantics PB - Academic Press JF - Journal of Biomedical Informatics VL - 46 IS - 5 SP - 784 EP - 794 CY - Dip. di Etologia, Ecologia ed Evoluzione, University of Pisa, via A. Volta 6, Pisa, I-56126, Italy. vformi@discau.unipi.it DO - S0047-2484(98)90270-6 [pii] ENGLAND UR - https://www.sciencedirect.com/science/article/pii/S1532046413000750?via%3Dihub N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. ER - TY - JOUR T1 - Modularising ontology and designing inference patterns to personalise health condition assessment: The case of obesity A1 - Sojic, A A1 - Terkaj, W A1 - Contini, G A1 - Sacco, M Y1 - 2016/// KW - Adolescent KW - Healthy lifestyle KW - Nutritional habits KW - Obesity KW - Ontology modularisation KW - Person KW - Personalised inference KW - Physical activity KW - Physical constitution KW - Teenager JF - Journal of Biomedical Semantics VL - 7 IS - 1 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Sojic et al. - 2016 - Modularising ontology and designing inference patterns to personalise health condition assessment The case of obes.pdf N1 - Cited By :5 Export Date: 10 September 2018 References: (2014) European Food and Nutrition Action Plan 2015-2020, , WHO Regional Office for Europe; Addy, N.A., Shaban-Nejad, A., Buckeridge, D.L., Dubé, L., An innovative approach to addressing childhood obesity: A knowledge-based infrastructure for supporting multi-stakeholder partnership decision-making in Quebec, Canada (2015) International Journal of Environmental Research and Public Health, 12 (2), pp. 1314-1333; Guarneri, R., Andreoni, G., Active prevention by motivating and engaging teenagers in adopting healthier lifestyles (2014) Applications in Health, Safety, Ergonomics and Risk Management, pp. 351-360. , In: Digital Human Modeling, Switzerland: Springer International Publishing; Caon, M., Carrino, S., Lafortuna, C.L., Serrano, J.C., Coulson, N.S., Sacco, M., Khaled, O.A., Mugellinia, E., Tailoring motivational mechanisms to engage teenagers in healthy life-style: A concept (2014) AHFE Conference on Advances in Human Aspects of Healthcare; Lafortuna, C.L., Caon, M., Tabozzi, S.A., Carrino, S., Coulson, N.S., Serrano, J.C., Towards individualised persuasive technology for obesity prevention in teenagers (2014) In: Proceedings of the 7th International Conference on Health Informatics (HEALTHINF); Mazzola, M., Arslan, P., Cândea, G., Radu, C., Azzolini, M., Degano, C., Andreoni, G., Integrated Architecture for Next-Generation m-Health Services (Education, Monitoring and Prevention) in Teenagers (2014) Applications in Health, Safety, Ergonomics and Risk Management, pp. 403-414. , In: Digital Human Modeling, Switzerland: Springer International Publishing; http://www.w3.org/2001/sw/wiki/Main_Page, Semantic Web W3C Portal. Accessed 2015-05-10; Sojic, A., Kutz, O., Open biomedical pluralism: formalising knowledge about breast cancer phenotypes (2012) Journal of biomedical semantics, 3 (2), pp. 1-31; Kutz, O., Mossakowski, T., Hastings, J., Castro, A.G., Sojic, A., (2011) Hyperontology for the biomedical ontologist: A sketch and some examples, , In: ICBO; Kádár, B., Terkaj, W., Sacco, M., Semantic virtual factory supporting interoperable modelling and evaluation of production systems (2013) CIRP Annals-Manufacturing Technology, 62 (1), pp. 443-446; Uschold, M., Gruninger, M., Ontologies: Principles, methods and applications (1996) The knowledge engineering review, 11 (2), pp. 93-136; the ISO 17347 Standard Development Initiative http://ontoiop.org, Accessed 2015-05-12; Uschold, M., Gruninger, M., Ontologies and semantics for seamless connectivity (2004) ACM SIGMod Record., 33 (4), pp. 58-64; Spyns, P., Meersman, R., Jarrar, M., Data modelling versus ontology engineering (2002) ACM SIGMod Record., 31 (4), pp. 12-17; Noy, N.F., Klein, M., Ontology evolution: Not the same as schema evolution (2004) Knowledge and information systems, 6 (4), pp. 428-440; Moniruzzaman, A., Hossain, S.A., NoSQL Database: New Era of Databases for Big data Analytics-Classification, Characteristics and Comparison (2013), arXiv preprint arXiv:1307.0191; Shaban-Nejad, A., Buckeridge, D.L., Dubé, L., Cope: childhood obesity prevention [knowledge] enterprise (2011) In: Artificial Intelligence in Medicine, pp. 225-229. , Berlin Heidelberg: Springer-Verlag; Scala, P.L., Pasquale, D., Tresoldi, D., Lafortuna, C.L., Rizzo, G., Padula, M., Ontology-supported clinical profiling for the evaluation of obesity and related comorbidities (2012) Studies in health technology and informatics, 180, p. 1025; http://www.w3.org/TR/owl2-overview/, OWL 2 - Overview. Accessed 2015-04-20; Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M., SWRL: A semantic web rule language combining OWL and RuleML W3C Member submission, 21 (2004), p. 79. , http://www.w3.org/Submission/SWRL/; Guarino, N., Oberle, D., Staab, S., What is an Ontology? (2009) Handbook on Ontologies. International Handbooks on Information Systems, pp. 1-17. , In: Staab S, Studer R, editors. Berlin Heidelberg: Springer-Verlag; http://pegasof4f.eu/, Pegaso - Fit 4 Future. Accessed 2015-04-20; Caon, M., Carrino, S., Guarnieri, R., Andreoni, G., Lafortuna, C.L., Abou Khaled, O., Mugellini, E., A persuasive system for obesity prevention in teenagers: a concept (2014) In: Proceedings of the Second International Workshop on Behavior Change Support Systems (BCSS2014), , http://ceur-ws.org/Vol-1153/Paper_2.pdf, Padova, Italy. CEUR-WS; Carrino, S., Caon, M., Khaled, O.A., Andreoni, G., Mugellini, E., Pegaso: Towards a life companion (2014) Applications in Health, Safety, Ergonomics and Risk Management, pp. 325-331. , In: Digital Human Modeling, Switzerland: Springer International Publishing; Obesity: Preventing and Managing the Global Epidemic (2000) IIS microfiche library. World Health Organization, , http://books.google.it/books?id=AvnqOsqv9doC; Pannese, L., Morosini, D., Lameras, P., Arnab, S., Dunwell, I., Becker, T., Pegaso: A serious game to prevent obesity (2014) Applications in Health, Safety, Ergonomics and Risk Management, pp. 427-435. , In: Digital Human Modeling, Switzerland: Springer International Publishing; Gruber, T.R., Toward Principles for the Design of Ontologies Used for Knowledge Sharing (1995) International Journal of Human-Computer Studies, 43 (4-5), pp. 907-928; Gangemi, A., Presutti, V., Ontology design patterns (2009) In: Handbook on Ontologies, pp. 221-243. , Berlin Heidelberg: Springer-Verlag; Guarino, N., Welty, C.A., An overview of OntoClean (2009) In: Handbook on Ontologies, pp. 201-220. , Berlin Heidelberg: Springer-Verlag; Jansen, L., Classifications (2008) Applied Ontology: An Introduction, pp. 159-172. , In: Munn, K., Smith, B. (eds.). Walter de Gruyter; International Standard Classification of Education, , http://www.uis.unesco.org/Education/Pages/international-standard-classification-of-education.aspx, Accessed 2015-05-6; Rector, A.L., Modularisation of domain ontologies implemented in description logics and related formalisms including OWL (2003) In: Proceedings of the 2nd International Conference on Knowledge Capture, pp. 121-128. , A.C.M; Stuckenschmidt, H., Parent, C., Spaccapietra, S., (2009) Modular Ontologies: Concepts, Theories and Techniques for Knowledge Modularization, 5445. , Berlin Heidelberg: Springer-Verlag; Sure, Y., Staab, S., Studer, R., Ontology engineering methodology (2009) In: Handbook on Ontologies, pp. 135-152. , Berlin Heidelberg: Springer-Verlag; d'Aquin, M., Schlicht, A., Stuckenschmidt, H., Sabou, M., Criteria and evaluation for ontology modularization techniques (2009) In: Modular Ontologies, pp. 67-89. , Berlin Heidelberg: Springer-Verlag; Parent, C., Spaccapietra, S., An overview of modularity (2009) In: Modular Ontologies, pp. 5-23. , Berlin Heidelberg: Springer-Verlag; Konev, B., Lutz, C., Walther, D., Wolter, F., Formal properties of modularisation (2009) In: Modular Ontologies, pp. 25-66. , Berlin Heidelberg: Springer-Verlag; Bezerra, C., Freitas, F., Euzenat, J., Zimmermann, A., ModOnto: A tool for modularizing ontologies (2008) In: Proc. 3rd Workshop on Ontologies and Their Applications (Wonto); d'Aquin, M., Schlicht, A., Stuckenschmidt, H., Sabou, M., Ontology modularization for knowledge selection: Experiments and evaluations (2007) In: Database and Expert Systems Applications, pp. 874-883. , Berlin Heidelberg: Springer-Verlag; WHO child growth standards: methods and development: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age (2006), Geneva: WHO; Lewontin, R., The genotype/phenotype distinction (2011) The Stanford Encyclopedia of Philosophy, , http://plato.stanford.edu/archives/sum2011/entries/genotype-phenotype/, In: Zalta, E.N. (ed.), Summer 2011 edn; Hitzler, P., Parsia, B., Ontologies and rules (2009) In: Handbook on Ontologies, pp. 111-132. , Berlin Heidelberg: Springer-Verlag; Terkaj, W., Tolio, T., Urgo, M., A virtual factory approach for in situ simulation to support production and maintenance planning (2015) CIRP Annals-Manufacturing Technology, 64 (1), pp. 451-454; Horridge, M., Patel-Schneider, P.F., OWL 2 web ontology language: Manchester syntax, , http://www.w3.org/TR/2009/NOTE-owl2-manchester-syntax-20091027/, W3C candidate recommendation, World Wide Web Consortium (W3C) (October 2009); Sirin, E., Parsia, B., Grau, B.C., Kalyanpur, A., Katz, Y., Pellet: A practical owl-dl reasoner (2007) Web Semantics: science, services and agents on the World Wide Web, 5 (2), pp. 51-53; Musen, M.A., Protégé ontology editor (2013) In: Encyclopedia of Systems Biology, pp. 1763-1765. , (Eds) Dubitzky et. al. New York: Springer-Verlag; Terkaj, W., Šojić, A., Ontology-based representation of IFC EXPRESS rules: An enhancement of the ifcOWL ontology (2015) Automation in Construction, 57, pp. 188-201; Borgida, A., Description logics in data management (1995) Knowledge and Data Engineering, IEEE Transactions on, 7 (5), pp. 671-682; Nardi, D., Brachman, R.J., An introduction to description logics (2003) In: Description Logic Handbook, pp. 1-40; Alamri, A., Bertok, P., Fahad, A., Towards an architecture for managing semantic knowledge in semantic repositories (2014) International Journal of Parallel, Emergent and Distributed Systems (ahead-of-print), pp. 1-15; https://www.w3.org/2001/sw/wiki/Stardog, Accessed 2015-11-10; Motik, B., Grau, B.C., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C., Owl 2 web ontology language: Profiles (2009) W3C recommendation, 27, p. 61; Hartung, M., Groß, A., Kirsten, T., Rahm, E., Effective Mapping Composition for Biomedical Ontologies (2012) In: Proc. of Semantic Interoperability in Medical Informatics (SIMI-12), , Workshop at ESWC-12; Mammalian Phenotype Ontology, , http://bioportal.bioontology.org/ontologies/MP, Accessed 2015-06-6; HPO Human Phenotype Ontology, , http://www.human-phenotype-ontology.org/, Accessed 2015-06-6; UMLS Unified Medical Language System, , http://www.nlm.nih.gov/research/umls/, Accessed 2015-06-6; http://www.ihtsdo.org/snomed-ct/, Accessed 2015-06-5; ICD-10 International Classification of Diseases, , http://bioportal.bioontology.org/ontologies/ICD10, Accessed 2015-06-6; http://bioportal.bioontology.org/ontologies/NCIT, Accessed 2015-06-5; OBI Ontology for Biomedical Investigations, , http://bioportal.bioontology.org/ontologies/OBI, Accessed 2015-06-6; UO Units of Measurement Ontology, , http://bioportal.bioontology.org/ontologies/UO, Accessed 2015-06-6; HL7 Health Level Seven Reference Implementation Model, , http://bioportal.bioontology.org/ontologies/HL7, Accessed 2015-06-5; Herre, H., A Foundational Ontology for Conceptual Modelling (2010) Theory and Applications of Ontology, 2. , In: Poli R, Obrst L, editors. Berlin: Springer; GFO General Formal Ontology, , http://www.onto-med.de/ontologies/gfo/, Accessed 2015-06-6; Masolo, C., Borgo, S., Gangemi, A., Guarino, N., Oltramari, A., (2003) WonderWeb Deliverable D18: Ontology Library; BFO Basic Formal Ontology, , http://bioportal.bioontology.org/ontologies/BFO, Accessed 2015-06-6; https://loinc.org/, LOINC Logical Observation Identifiers Names and Codes. Accessed 2015-06-20UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84965036461&doi=10.1186%2fs13326-016-0049-1&partnerID=40&md5=703ee8f494c9762a4613deb0bdde61c7 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background: The public health initiatives for obesity prevention are increasingly exploiting the advantages of smart technologies that can register various kinds of data related to physical, physiological, and behavioural conditions. Since individual features and habits vary among people, the design of appropriate intervention strategies for motivating changes in behavioural patterns towards a healthy lifestyle requires the interpretation and integration of collected information, while considering individual profiles in a personalised manner. The ontology-based modelling is recognised as a promising approach in facing the interoperability and integration of heterogeneous information related to characterisation of personal profiles. Results: The presented ontology captures individual profiles across several obesity-related knowledge-domains structured into dedicated modules in order to support inference about health condition, physical features, behavioural habits associated with a person, and relevant changes over time. The modularisation strategy is designed to facilitate ontology development, maintenance, and reuse. The domain-specific modules formalised in the Web Ontology Language (OWL) integrate the domain-specific sets of rules formalised in the Semantic Web Rule Language (SWRL). The inference rules follow a modelling pattern designed to support personalised assessment of health condition as age- and gender-specific. The test cases exemplify a personalised assessment of the obesity-related health conditions for the population of teenagers. Conclusion: The paper addresses several issues concerning the modelling of normative concepts related to obesity and depicts how the public health concern impacts classification of teenagers according to their phenotypes. The modelling choices regarding the ontology-structure are explained in the context of the modelling goal to integrate multiple knowledge-domains and support reasoning about the individual changes over time. The presented modularisation pattern enhances reusability of the domain-specific modules across various health care domains. © 2016 Sojic et al. ER - TY - CONF T1 - Integration of data mining operations for structural health monitoring A1 - Sonnleitner, E A1 - Kosorus, H A1 - Anderlik, S A1 - Stumptner, R A1 - Freudenthaler, B A1 - Allmer, H A1 - Küng, J Y1 - 2011/// KW - Application domains KW - Artificial intelligence KW - Civil engineers KW - Data integration KW - Data mining KW - Decision support systems KW - Heterogeneous data sources KW - Intelligent structures KW - Maintenance KW - Measurement analysis KW - Mining operations KW - Reliable decision KW - Schemas KW - Semantics VL - 1 SP - 1325 EP - 1332 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866684310&partnerID=40&md5=3533cd1ada1083f181c9dd698ff2e948 N1 - Cited By :1 Export Date: 10 September 2018 References: Wenzel, H., Pichler, D., (2005) Ambient Vibration Monitoring, , John Wiley & Sons Ltd., Chichester; Wenzel, H., (2008) Health Monitoring of Bridges, , John Wiley & Sons Ltd., Chichester; Anderlik, S., Stumptner, R., Freudenthaler, B., Fritz, M., A proposal for ontology-based integration of heterogeneous decision support systems for structural health monitoring (2010) Proceedings of the 12th International Conference on Information Integration and Web-based Applications and Services, pp. 166-173. , Paris; Graczyk, M., Lasota, T., Trawinski, B., Comparative analysis of premises valuation models using KEEL, RapidMiner, and WEKA (2009) Proceedings of 1st International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems, pp. 800-812. , Berlin/Heidelberg; Holmes, G., Donkin, A., Witten, I.H., WEKA: A machine learning workbench (1994) Proceedings of the 1994 Second Australian and New Zealand Conference on Intelligent Information Systems, pp. 357-361. , Brisbane, Qld; (2010) Rapid-I: Rapidminer 5.0 Manual, , http://rapid-i.com/content/view/26/84/; Jones, O., Maillardet, R., Robinson, A., (2009) Introduction to Scientific Programming and Simulation Using, , R. Chapman & Hall/CRC; Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., Huebner, S., Ontology-based integration of information - A survey of existing approaches (2001) Proceedings of the IJCAI-01 Workshop on Ontologies and Information Sharing, pp. 108-117. , (Seattle, USA, August 4 - 5, 2001), IJCA'01 IEEE; Buccella, A., Cechich, A., Brisaboa, N.R., Ontology-based data integration methods: A framework for comparison (2005) Journal of Intelligent and Cooperative Information Systems, 2 (2), pp. 127-158. , Paper Proposal. University of Com-ahue.sources; Wache, H., Voegele, T., Visser, U., Stuckenschmidt, H., Schuster, G., Neumann, H., Huebner, S., Ontology-based integration of information - A survey of existing approaches (2001) Proceedings of the IJCAI-01 Workshop on Ontologies and Information Sharing, pp. 108-117. , IEEE; Mita, A., Inamura, T., Yoshikawa, S., Structural health monitoring for buildings with automatic data management system (2006) Proceedings of the 4th International Conference on Earthquake Engineering, , Taiwan; Ripley, B.D., (2001) The R and Omegahat Projects in Statistical Computing, , Department of Statistics, University of Oxford RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Data Integration is a well elaborated scientific area and one of the most important use cases of the Semantic Web. Techniques developed in this field aim at providing interoperability between heterogeneous data sources. Compared to typical Semantic Web use cases, data integration issues are manifold and also affect applications through their underlying schemas. Civil engineers specialized in risk and measurement analysis need a reliable Decision Support System (DSS) that integrates various required techniques. Hence, Structural Health Monitoring (SHM) applications tend to adopt typical integration concepts, but not by regarding data and their semantics independent from the application domain. Instead, such a DSS should be accessible in an integrated manner to support the usage of methods and techniques from different systems according to their intended operational purpose. This paper presents some practical examples of using Data Mining operations which enable a better understanding of the analysed data and which can be successfully integrated into a unified DSS for SHM. ER - TY - BOOK T1 - Step Towards Monitoring Intelligent Agents in Healthcare Information Systems A1 - Sousa, R A1 - Ferreira, D A1 - Abelha, A A1 - Machado, J Y1 - 2020/// JF - Advances in Intelligent Systems and Computing VL - 1161 AISC SP - 510 EP - 519 SN - 9783030456962 DO - 10.1007/978-3-030-45697-9_50 N2 - ©2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. A platform for establishing interoperability between heterogeneous information systems implemented in a hospital environment is more a requirement than an option. The Agency for the Integration, Diffusion and Archiving of Medical and Clinical Information (AIDA) is an interoperability platform designed specifically to address the problem of integrating information from multiple systems and addressing interoperability, confidentiality, integrity and data availability. This article focuses on the relevance and need for such vigilance, finding and designing effective new ways to establish them. This study culminated in the creation of AIDAMonit, a surveillance platform developed and tested by ALGORITMI Center researchers, which has shown promise and is extremely beneficial for the well-functioning of the health facilities currently using the AIDA platform. ER - TY - CONF T1 - Architecture of a learning surveillance system for malaria elimination in India A1 - Sreeganga, S D A1 - Mitra, S G A1 - Ramaprasad, A Y1 - 2020/// JF - HEALTHINF 2020 - 13th International Conference on Health Informatics, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020 SP - 377 EP - 382 SN - 9789897583988 N2 - ©2020 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. Surveillance is critical for malaria elimination. Malaria transmission takes place in a dynamic and complex environment. The key goal in developing a malaria surveillance system is to ensure that it is robust, systematic, and effective for improving data availability for decision-making. We present a unified framework for envisioning malaria surveillance informatics as an ontology-based feedback system. The framework presented is a solution for the current fragmented and linear surveillance processes for malaria case management. It encapsulates a comprehensive natural language enumeration of the requirements of the cyberenvironment, structured into 5 dimensions - timing, surveillance process, information surveyed, malaria management, and stakeholder, with each of them articulated as a taxonomy of its constituent elements. The elements are combined to form natural language statements of the cyberenvironment requirement. The information generation through the semiotic cycle provides real-time sense and response capability for timely and targeted interventions. The response mechanism creates both positively and negatively reinforcing feedback-based learning processes at multiple levels. Such a system enables data interoperability for capturing malaria incidence, discover epidemiological clusters, and predict propagation dynamics. On a larger scale, the integrative framework enables data harmonization, analytics, and visualization towards effective management and knowledge generation on disease surveillance. ER - TY - JOUR T1 - A case for using grid architecture for state public health informatics: The Utah perspective A1 - Staes, C J A1 - Xu, W A1 - Lefevre, S D A1 - Price, R C A1 - Narus, S P A1 - Gundlapalli, A A1 - Rolfs, R A1 - Nangle, B A1 - Samore, M A1 - Facelli, J C Y1 - 2009/// KW - Data Collection KW - Government Agencies KW - Humans KW - Informatics KW - Information Systems KW - Public Health Administration KW - Public Health Informatics KW - State Government KW - Systems Integration KW - United States KW - Utah KW - article KW - data analysis KW - government KW - health service KW - health status KW - human KW - information processing KW - information system KW - information technology KW - medical informatics KW - medical research KW - methodology KW - organization and management KW - public health KW - public health service KW - system analysis JF - BMC Medical Informatics and Decision Making VL - 9 IS - 1 N1 - Cited By :6 Export Date: 10 September 2018 References: Of Medicine, I., (1988) The Future of Public Health, the Report of the Committee for the Study of the Future of Public Health, , Washington, DC: National Academy Press; (2007) Understanding State Public Health, , Washington, DC: ASTHO; Patrick, W., O'Carroll, P.W., Yasnoff, W.A., Editors W. E, M., (2003) Public Health Informatics and Information Systems, p. 383. , New York: Springer; Improving early detection by unsing a standards-based approach to connecting public health and clinical medicine (2004) Morb Mort Weekly Rev, 53 (SUPPL), pp. 199-202. , CVLJ Broome Public Health Information Network; Information management for State Health Officials. Integrating child health information systems while protecting privacy (2005) A Review of Four State Approaches. Washington, DC, , http://www.astho.org/pubs/ChildHealthInformationSystems.pdf; National electronic disease surveillance system (2008) Atlanta, , http://www.cdc.gov/nedss/; (2008) Davies Public Health Award Recipient Manuscripts, , http://www.himss.org/ASP/davies-publichealth.asp, Chicago: Healthcare Information and Management Systems Society; Stevens, R., Trends in Cyberinfrastructire for Biomedical and Computational Biology (2006) CTWatch, 2, pp. 1-5; Saltz, J., Oster, S., Hastings, S., Langella, S., Kurc, T., Sanchez, W., CaGrid: Design and implementation of the core architecture of the cancer biomedical informatics grid (2006) Bioinformatics, 22, pp. 1910-6. , 10.1093/bioinformatics/btl272 16766552; Jithesh, P.V., Donachy, T., Harmer, T., Kelly, N., Perrott, R., Wasnik, S., GeneGrid: Architecture, IMplementation and Application (2006) J Grid Computing, 4, pp. 209-22. , 10.1007/s10723-006-9045-5; Drake, T.A., Braun, J., Marchevsky, A., Kohane, I.S., Fletcher, C., Chueh, H., (2007) A System for Sharing Routine Surgical Pathology Specimens Across Institutions: The Shared Pathology Informatics Network, 38 (8), p. 1212. , 17490722; Sinnott, R.O., Stell, A.J., Ajayi, O., Supporting grid-based clinical trials in Scotland (2008) Health Informatics Journal, 14 (2), pp. 79-93. , 10.1177/1081180X08089317 18477596; Friedrich, C.M., Dach, H., Gattermayer, T., Engelbrecht, G., Benkner, S., Editors, H.M., @neuLink: A Service-oriented Application for Biomedical Knowledge Discovery (2008) HealthGrid, , Chicago: IOS Press; Breton, V., Solomonides, A.E., McClatchey, R.H., A perspective on the Healthgrid initiative (2004) Second International Workshop on Biomedical Computations on the Grid, at the 4th IEEE/ACM International Symposium on Cluster Computing and the Grid; Chicago, , http://arxiv.org/abs/cs.DB/0402025; Erverich, S.G., Silverstein, J.C., Chervenak, A., Schuler, R., Nelson, M.D., Kesselman, C., Globus MEDICUS federation of DICOM medical imaging devices into healthcare Grids (2007) Stud Health Technol Inform, 126, pp. 269-78. , 17476069; Pierson, J.M., Gossa, J., Wehrle, P., Cardenas, Y., Cahon, S., El Samad, M., GGM: Efficient Navigation and Mining in Distributed Genomedical Data (2007) Nanobioscience, IEEE Transactions on Nanobioscience, 6 (2), p. 110. , 10.1109/TNB.2007.897477; Mirto, M., Cafaro, M., Fiore, S.L., Tartarini, D., Aloisio, G., A Grid-Enabled Protein Secondary Structure Predictor Nanobioscience, IEEE Transactions on 2007, 6 (2), p. 124. , 10.1109/TNB.2007.897475; Sun, Y., Wipat, A., Pocock, M., Lee, P.A., Flanagan, K., Worthington, J.T., Exploring microbial genome sequences to identify protein families on the grid (2007) IEEE Trans Inf Technol Biomed, 11, pp. 435-42. , 10.1109/TITB.2007.892913 17674626; Piggott, D.K.A., Teljeur, C., Exploring the combination of computational Grid processing techniques and public health information in relation to modeling the effects of hospital closure proposals (2004) IEEE International Symposium on Cluster Computing and the Grid (IEEE Cat No04EX836), pp. 336-7; Zhang, J.G.J., Zhu, J., Xu, B., Wu, X., A GI services grid for public health management and disease control. Source: IGARSS 2005 (2005) IEEE International Geoscience and Remote Sensing Symposium, p. 4; Zimmerman, D.M., Chandy, K.M., Snapshot processing in streaming environments (2006) 7th IEEE/ACM International Conference on Grid Computing (IEEE Cat No 06EX1363C), p. 2; Da Silva, F.A., Gagliardi, H.F., Gallo, E., Neto, V.C., Pisa, I.T., IntegraEPI: A Grid-based epidemic surveillance system (2007) Stud Health Technol Inform, 126, pp. 197-206. , 17476062; Co-Chairs, I., (2007) Ms. Mary Kratz JS, MD, MS, FACS, Parvati Dev, PhD, , Integrated Research Team Final Report HealthGrid: Grid Technologies for Biomedicine; Lenert, L., Perspectives on Harmonization: The New NCPHI (2007) The 2007 Public Health Information Network Conference, , Atlanta, Georgia: The PHIN Conference; (2007) NCSA Technology, Resources Enable Automatic Triggering of Severe Weather Forecasts, , http://www.ncsa.uiuc.edu/News/07/0531NCSAtechnology.html, Chicago: National Center for Supercomputing Applications; (2008) Natural Hazards, , http://earthobservatory.nasa.gov/NaturalHazards/; Facelli, J.C., Giribet, C.G., Contreras, R.H., The use of partially restricted molecular orbitals to investigate transmission mechanisms of spin-spin coupling constants. III. An INDO study of long-range fluorine-hydrogen couplings in fluorinated derivatives of toluene (1982) Organic Magnetic Resonance, 19 (3), pp. 138-43. , 10.1002/mrc.1270190306; (2008), http://ibis.health.utah.gov/home/Welcome.html, Utah's Indicator-Based Information System for Public Health Utah Department of HealthUR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-67651033882&doi=10.1186%2f1472-6947-9-32&partnerID=40&md5=af04ab4a6586ad81f1414a39cd289b84 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This paper presents the rationale for designing and implementing the next-generation of public health information systems using grid computing concepts and tools. Our attempt is to evaluate all grid types including data grids for sharing information and computational grids for accessing computational resources on demand. Public health is a broad domain that requires coordinated uses of disparate and heterogeneous information systems. System interoperability in public health is limited. The next-generation public health information systems must overcome barriers to integration and interoperability, leverage advances in information technology, address emerging requirements, and meet the needs of all stakeholders. Grid-based architecture provides one potential technical solution that deserves serious consideration. Within this context, we describe three discrete public health information system problems and the process by which the Utah Department of Health (UDOH) and the Department of Biomedical Informatics at the University of Utah in the United States has approached the exploration for eventual deployment of a Utah Public Health Informatics Grid. These three problems are: i) integration of internal and external data sources with analytic tools and computational resources; ii) provide external stakeholders with access to public health data and services; and, iii) access, integrate, and analyze internal data for the timely monitoring of population health status and health services. After one year of experience, we have successfully implemented federated queries across disparate administrative domains, and have identified challenges and potential solutions concerning the selection of candidate analytic grid services, data sharing concerns, security models, and strategies for reducing expertise required at a public health agency to implement a public health grid. © 2009 Staes et al. ER - TY - CONF T1 - New era for technology in healthcare powered by GDPR and blockchain A1 - Stan, O P A1 - Miclea, L Y1 - 2019/// JF - IFMBE Proceedings VL - 71 SP - 311 EP - 317 SN - 9789811362064 DO - 10.1007/978-981-13-6207-1_49 N2 - ©2019, Springer Nature Singapore Pte Ltd. The development of patients' electronic healthcare records has been hampered by bureaucracy and by heavy regulation within the medical field. Medical data recorded in a patient health records is a valuable source of information that can be used by doctors and researchers to improve the quality of healthcare and the quality of life. Medical data should be owned and controlled by the patient instead of being scattered in different healthcare systems that does not support transfer and semantic interoperability between different healthcare providers. Blockchain technology has demonstrated in the financial field that it is possible to create a safe, secure and auditable mechanism by using a decentralized network along with a public ledger. But with the adoption of the newly General Data Protection Regulation, all technological advances discovered by the Blockchain are now blocked. In this paper we present the main aspect of the GDPR and Blockchain technology in healthcare and a way in which this two can work together. ER - TY - CONF T1 - Federated data warehouse approach to support the national and international interoperability of healthcare information systems 1 A1 - Stolba, N A1 - Tjoa, A M A1 - Mueck, T A1 - Banek, M Y1 - 2007/// KW - Data structures KW - Data warehouses KW - Federated data warehouse KW - HL7 KW - Health care KW - Health care information system KW - Healthcare domains KW - Hospital data processing KW - Information Services KW - Information Systems KW - Information integration KW - Information networks KW - Information services KW - Institutional barriers KW - International cooperation KW - International interoperability KW - Interoperability KW - Interoperability of medical information systems KW - Medical information systems KW - Ontological integration KW - Organizational aspects KW - Patient data KW - Public sector KW - Research challenges KW - e-Health systems SP - 2161 EP - 2172 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84869418229&partnerID=40&md5=749b3a27d72441807bcfc604aa501ebe N1 - Cited By :3 Export Date: 10 September 2018 References: http://www.symcorp.com/, Last Access: 2006-11-23; Beneventano, D., Bergamaschi, S., Guerra, F., Vincini, M., Synthesizing an integrated ontology (2003) IEEE Internet Computing Magazine, pp. 42-51; Beneventano, D., Bergamaschi, S., Semantic search engines based on data integration systems (2006) Semantic Web: Theory, Tools and Applications, , (Ed. Jorge Cardoso) Idea Group Publishing; Bilykh, I., Bychkov, Y., Dahlem, D., Jahnke, J.H., McCallum, G., Obry, C., Onabajo, A., Kuziemsky, C., Can GRID services provide answers to the challenges of national health information sharing?, IBM Centre for Advanced Studies Conference (2003) Proceedings of the 2003 Conference of the Centre for Advanced Studies on Collaborative Research, , http://www.infoway-inforoute.ca/en/home/home.aspx, Toronto, Ontario, Canada, Pages: 39-53. Canada Health Infoway:, Last Access: 2006-10-29; http://ksz-bcss.fgov.be/En/CBSS.htm, CBSS, Crossroad Bank for Social Security, , Last Access: 2006-11-03; Commission of the European Communities. (2004) e-Health-making healthcare better for European citizens: An action plan for a European e-Health Area, {SEC(2004)539}, Brussels; Dorda, W., Duftschmied, D., Gerhold, L., Gall, W., Gambal, J., Introducing the electronic health record in Austria (2005) MIE 2005, 116, pp. 119-124; Duftschmied, G., Dorda, W., Gall, W., (2003) MAGDA-LENA Versus HIPAA: Two National Frameworks for Healthcare Data Exchange, Tagungsband der 3. Tagung der Österreichischen Wissenschaftlichen Gesellschaft Für Telemedizin, , Graz, Austria, 25-33; Gall, W., Duftschmied, G., Dorda, W., (2004) Temporal Components in Architectures of Electronic Health Records, 49, pp. 99-102. , Jahrestagung der Deutschen Geselschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds2004) Innsbruck; Halevy A, Y., Answering queries using views: A survey (2001) VLDB Journal, 10 (4), pp. 270-294; http://www.health.gov.au/healthconnect, HealthConnect:, Last Access: 2006-10-23; http://www.hipaa.org/, Last Access: 2006-11-03; http://www.hygeianet.gr/, Last Access: 2006-11-03; Heitmann, K.U., (2006) Kommunikation Mit HL7 Version 3-Aspekte der Interoperabilität im Gesundheitswesen, Datenbank Spektrum, , http://www.medcom1-4.dk/, 17/2006, dpunkt.verlag, 12-16. MedCom:, Last Access: 2006-10-30; http://www.connectingforhealth.nhs.uk/delivery/programmes/nhscrs, NPfIT:, Last Access: 2006-10-30; http://www.hhs.gov/healthit/, Office of the National Coordinator for Health Information Technology:, Last Access: 2006-10-23; http://www.carelink.se; Stolba, N., Banek, M., Tjoa, A.M., (2006) The Security Issue of Federated Data Warehouses in the Area of Evidence-Based Medicine, , First International Conference on Availability, Reliability and Security (ARES 2006) Vienna, Austria, IEEE Computer Society Press; Stolba, N., Nguyen, T.M., Tjoa, A.M., (2007) Sustainable Decision-Support System Facilitating Evidence-Based Medicine, , Submitted to 12th World Congress on Health (Medical) Informatics, Brisbane Convention Centre; Stolba, N., Tjoa, A.M., (2006) An Approach Towards the Fulfilment of Security Requirements for Decision Support Systems in the Field of Evidence-Based Healthcare, pp. 51-59. , Knowledge Rights-Legal, Societal and Related Technological Aspects (KnowRight2006) Vienna, Austria, Austrian Computer Society; (2000) Rahmenbedingungen Für Ein Logisches Österreichisches Gesundheitsdatennetz ("MAGDA-LENA"), , http://www.svb.at/mediaDB/63656.PDF, STRING-Kommission, Last Access: 2006-11-23; Ullman J, D., (1997) Information Integration Using Logical Views, pp. 19-40. , ICDT Conference RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The interoperability of medical information systems is gaining more attention as the need for the collaboration in healthcare domain increases. Consolidation of distributed patient data and building a sustainable e-health system is the major research challenge. In order to overcome institutional barriers and competences for changes across sectors, standardized data structures and corresponding underlying infrastructure are needed. A concisely defined information network for the exchange of sensitive patient's data is a significant step towards enabling national and international cooperation. In this paper, we discuss the challenges and the advantages of the healthcare information integration into a federated data warehouse (DWH). We present technical and organizational aspects for creation of Austrian healthcare information network, and describe a scenario-based federation of Austrian health-insurance DWHs in compliance with the national governing framework for electronic exchange of patient-related data. This example will illustrate the benefits of standardized, identifiable and secure consolidation of the local DWHs and promote innovation in the public sector. ER - TY - JOUR T1 - Building a transnational biosurveillance network using semantic Web technologies: Requirements, design, and preliminary evaluation A1 - Teodoro, D A1 - Pasche, E A1 - Gobeill, J A1 - Emonet, S A1 - Ruch, P A1 - Lovis, C Y1 - 2012/// KW - Antimicrobial drug resistance KW - Computer Simulation KW - Drug Resistance KW - Heterogeneous databases KW - International Cooperation KW - Internet KW - Microbial KW - Online information services KW - Population Surveillance KW - Software KW - Surveillance KW - User-Computer Interface KW - antibiotic resistance KW - article KW - computer interface KW - computer program KW - computer simulation KW - health survey KW - international cooperation JF - Journal of Medical Internet Research VL - 14 IS - 3 DO - 10.2196/jmir.2043 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864272496&doi=10.2196%2Fjmir.2043&partnerID=40&md5=ca7ce4fd516e83409f16839736afd5c5 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Teodoro et al. - 2012 - Building a transnational biosurveillance network using semantic Web technologies Requirements, design, and preli.txt N1 - Cited By :13 Export Date: 5 April 2018 N2 - Background: Antimicrobial resistance has reached globally alarming levels and is becoming a major public health threat. Lack of efficacious antimicrobial resistance surveillance systems was identified as one of the causes of increasing resistance, due to the lag time between new resistances and alerts to care providers. Several initiatives to track drug resistance evolution have been developed. However, no effective real-time and source-independent antimicrobial resistance monitoring system is available publicly. Objective: To design and implement an architecture that can provide real-time and source-independent antimicrobial resistance monitoring to support transnational resistance surveillance. In particular, we investigated the use of a Semantic Web-based model to foster integration and interoperability of interinstitutional and cross-border microbiology laboratory databases. Methods: Following the agile software development methodology, we derived the main requirements needed for effective antimicrobial resistance monitoring, from which we proposed a decentralized monitoring architecture based on the Semantic Web stack. The architecture uses an ontology-driven approach to promote the integration of a network of sentinel hospitals or laboratories. Local databases are wrapped into semantic data repositories that automatically expose local computing-formalized laboratory information in the Web. A central source mediator, based on local reasoning, coordinates the access to the semantic end points. On the user side, a user-friendly Web interface provides access and graphical visualization to the integrated views. Results: We designed and implemented the online Antimicrobial Resistance Trend Monitoring System (ARTEMIS) in a pilot network of seven European health care institutions sharing 70+ million triples of information about drug resistance and consumption. Evaluation of the computing performance of the mediator demonstrated that, on average, query response time was a few seconds (mean 4.3, SD 0.1×10 2 seconds). Clinical pertinence assessment showed that resistance trends automatically calculated by ARTEMIS had a strong positive correlation with the European Antimicrobial Resistance Surveillance Network (EARS-Net) (ρ =.86, P <.001) and the Sentinel Surveillance of Antibiotic Resistance in Switzerland (SEARCH) (ρ =.84, P <.001) systems. Furthermore, mean resistance rates extracted by ARTEMIS were not significantly different from those of either EARS-Net (Δ = ±0.130; 95% confidence interval -0 to 0.030; P <.001) or SEARCH (δ = ±0.042; 95% confidence interval -0.004 to 0.028; P =.004). Conclusions: We introduce a distributed monitoring architecture that can be used to build transnational antimicrobial resistance surveillance networks. Results indicated that the Semantic Web-based approach provided an efficient and reliable solution for development of eHealth architectures that enable online antimicrobial resistance monitoring from heterogeneous data sources. In future, we expect that more health care institutions can join the ARTEMIS network so that it can provide a large European and wider biosurveillance network that can be used to detect emerging bacterial resistance in a multinational context and support public health actions. © Douglas Teodoro, Emilie Pasche, Julien Gobeill, Stéphane Emonet, Patrick Ruch, Christian Lovis. ER - TY - JOUR T1 - Interoperability driven integration of biomedical data sources A1 - Teodoro, Douglas A1 - Choquet, Rémy A1 - Schober, Daniel A1 - Mels, Giovanni A1 - Pasche, Emilie A1 - Ruch, Patrick A1 - Lovis, Christian Y1 - 2011/// KW - Data Integration KW - Europe KW - Interoperability KW - Ontology KW - Semantic Integration KW - Semantics JF - Studies in Health Technology and Informatics VL - 169 SP - 185 EP - 189 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In this paper, we introduce a data integration methodology that promotes technical, syntactic and semantic interoperability for operational healthcare data sources. ETL processes provide access to different operational databases at the technical level. Furthermore, data instances have they syntax aligned according to biomedical terminologies using natural language processing. Finally, semantic web technologies are used to ensure common meaning and to provide ubiquitous access to the data. The system's performance and solvability assessments were carried out using clinical questions against seven healthcare institutions distributed across Europe. The architecture managed to provide interoperability within the limited heterogeneous grid of hospitals. Preliminary scalability result tests are provided. ER - TY - JOUR T1 - C ommittee o pinion A1 - Testing, Ovarian Reserve Y1 - 2015/// VL - 125 IS - 618 SP - 268 EP - 273 ER - TY - CONF T1 - Cross-domain attribute conversion for authentication and authorization A1 - Thaler, S A1 - Den Hartog, J A1 - Ayed, D A1 - Sommer, D A1 - Hitchens, M Y1 - 2015/// KW - Access control KW - Animal disease KW - Animals KW - Attribute-based KW - Authentication KW - Authentication and authorization KW - Authorization KW - Collaboration KW - Conversion process KW - Cross-domain KW - Disease Outbreaks KW - Interoperability KW - Ontology-based KW - Societies and institutions KW - Vocabulary SP - 652 EP - 659 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961575526&doi=10.1109%2FARES.2015.41&partnerID=40&md5=cb8da805a3c6a91971b64017794f7a79 N1 - Export Date: 10 September 2018 References: Agostino Ardagna, C., Di Vimercati, S., Neven, G., Paraboschi, S., Preiss, F.-S., Samarati, P., Verdicchio, M., Enabling privacy-preserving credential-based access control with XACML and SAML (2010) Computer and Information Technology (CIT), 2010 IEEE 10th International Conference on, pp. 1090-1095. , IEEE; Ayed, D., Bichsel, P., Camenisch, J., Den Hartog, J., Integration of data-minimising authentication into authorisation systems (2014) Trust and Trustworthy Computing, pp. 179-187. , Springer; Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S., Dbpedia-a crystallization point for the web of data (2009) Web Semantics: Science, Services and Agents on the World Wide Web, 7 (3), pp. 154-165; Böhm, K., Etalle, S., Den Hartog, J., Hütter, C., Trabelsi, S., Trivellato, D., Zannone, N., A flexible architecture for privacy-aware trust management (2010) Journal of Theoretical and Applied Electronic Commerce Research, 5 (2), pp. 77-96; (2000) Rethinking Public Key Infrastructures and Digital Certificates: Building in Privacy, , MIT Press Stefan A Brands; Brickley, D., Guha, R.V., McBride, B., (2014) RDF Schema 1. 1. W3C Recommendation; Camenisch, J., Lysyanskaya, A., An efficient system for non-transferable anonymous credentials with optional anonymity revocation (2001) Advances in CryptologyEUROCRYPT, pp. 93-118. , Springer; Ciuciu, I., Claerhout, B., Schilders, L., Meersman, R., Ontology-based matching of security attributes for personal data access in e-health (2011) On the Move to Meaningful Internet Systems: OTM, pp. 605-616. , Springer; Costante, E., Den Hartog, J., Petkovíc, M., Understanding perceived trust to reduce regret (2015) Computational Intelligence, 31 (2), pp. 327-347; Ehrig, M., (2006) Ontology Alignment: Bridging the Semantic Gap, 4. , Springer Science & Business Media; Euzenat, J., Shvaiko, P., (2007) Ontology Matching, 18. , Springer; Fellbaum, C., (1998) WordNet, , Wiley Online Library; Granitzer, M., Sabol, V., Weng Onn, K., Lukose, D., Tochtermann, K., Ontology alignmenta survey with focus on visually supported semi-automatic techniques (2010) Future Internet, 2 (3), pp. 238-258; Harris, S., Seaborne, A., (2013) SPARQL 1. 1 Query Language. W3C Recommendation, 21; Hu, W., Qu, Y., Falcon-AO: A practical ontology matching system (2008) Web Semantics: Science, Services and Agents on the World Wide Web, 6 (3), pp. 237-239; Lambrix, P., Tan, H., SamboA system for aligning and merging biomedical ontologies (2006) Web Semantics: Science, Services and Agents on the World Wide Web, 4 (3), pp. 196-206; Mascardi, V., Cord, V., Rosso, P., A comparison of upper ontologies (2007) WOA, pp. 55-64; Miles, A., Bechhofer, S., SKOS simple knowledge organization system reference (2009) W3C Recommendation, 18, p. W3C; Poveda-Villalón, M., Carmen Suárez-Figueroa, M., Gómez-Pérez, A., Validating ontologies with oops (2012) Knowledge Engineering and Knowledge Management, pp. 267-281. , Springer; Priebe, T., Dobmeier, W., Kamprath, N., Supporting attribute-based access control with ontologies (2006) Availability, Reliability and Security, 2006. ARES 2006. The First International Conference on, p. 8. , IEEE; Sabouri, A., Krontiris, I., Rannenberg, K., (2012) Attribute-based Credentials for Trust (ABC4Trust), , Springer; Trivellato, D., Zannone, N., Glaundrup, M., Skowronek, J., Etalle, S., A semantic security framework for systems of systems (2013) International Journal of Cooperative Information Systems, 22 (1); Veeningen, M., Brusò, M., Den Hartog, J., Zannone, N., POSTER: TRIPLEX: Verifying data minimisation in communication systems (2013) Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, pp. 1415-1418. , ACM; Veeningen, M., De Weger, B., Zannone, N., Data minimisation in communication protocols: A formal analysis framework and application to identity management (2014) International Journal of Information Security, 13 (6), pp. 529-569; (2012) OWL 2 Web Ontology Language, , W3C OWL Working Group; (2013) EXtensible Access Control Markup Language (XACML) Version 3. 0, , XACML Technical Committee RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In bio-security emergencies, such as an outbreak of an exotic animal disease, it is essential that the organizations involved in combating this outbreak collaborate effectively and efficiently. To achieve such a collaboration potentially confidential infrastructure and resources need to be shared amongst members of the participating organizations. In AU2EU we demonstrate the combination of existing data minimizing authentication, attribute-based authorization technologies to dynamically enable collaborations between these organization. However, a key problem that occurs during the establishment of such collaboration is different terminologies for similar authorization attributes. To overcome these differences and to minimize the overhead for new organizations to join an existing consortium we propose an ontology-based solution for converting attributes from one domain vocabulary to another. Additionally, we propose a methodology to construct a shared domain vocabulary. Using a shared domain vocabulary in the conversion process decreases the amount of alignments required for collaborating. We integrate and demonstrate the feasibility of this approach in a real-life scenario within the scope of AU2EU. This paper presents preliminary work, which is currently being deployed and will be evaluated in the upcoming months. © 2015 IEEE. ER - TY - ICOMM T1 - No Title A1 - The openEHR Foundation UR - http://www.openehr.org ER - TY - CONF T1 - Goals and challenges for the realization of a european wide ehealth infrastructure A1 - Thiel, A A1 - Eichelberg, M A1 - Wein, B A1 - Namli, T A1 - Dogac, A Y1 - 2007/// KW - Clinical data KW - Clinical practices KW - Coding system KW - EHR systems KW - Ehealth KW - Electronic health record KW - Europe KW - Health informations KW - Interoperability KW - Models KW - Public health KW - Reference models KW - Semantic interoperability KW - Semantics KW - Telemedicine KW - Terminology System KW - e-Health systems SP - 53 EP - 64 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84873463560&partnerID=40&md5=2ad5d80ad01c646822411f093e639180 N1 - Export Date: 10 September 2018 References: Building an enterprise master person index (2004) (AHIMA Practice Brief) Journal of AHIMA, 75 (1), pp. 56A-56D. , AHI04] American Health Information Management Association (AHIMA) MPI Task Force. (January; Bales, M.E., Kukafka, R., Burkhardt, A., Friedman, C., Qualitative assessment of the international classification of functioning, disability, and health with respect to the desiderata for controlled medical vocabularies (2006) Int J Med Inform, 75 (5), pp. 384-395. , BKB+06, May; Medical informatics - Electronic healthcare record communication European Prestandard ENV 13606, , CEN00, European Committee for Standardization, Brussels, Belgium; Health Informatics - Electronic Health Record Communication - Part 1: Reference Model, , CEN04] prEN 13606-1, Draft for CEN Enquiry, CEN/TC 251 Health Informatics, European Committee for Standardization, Brussels, Belgium; (2004) Current and Future Standardization Issues in the E-Health Domain: Achieving Interoperability (Draft 4.1)., , CEN04] CEN/ISSS eHealth Standardization Focus Group, Geneva, Switzerland: European Committee for Standardization/Information Society Standardization System; Cimino, J.J., Hripcsak, G., Johnson, S.B., Clayton, P.D., Designing an introspective, multipurpose, controlled medical vocabulary (1989) Proceedings of the Thirteenth Annual Symposium on Computer Applications in Medical Care, pp. 513-518. , CHJ+89, Kingsland LC (Ed). New York: IEEE Computer Society Press, S; Ceusters, W., Smith, B., Strategies for referent tracking in electronic health records (2006) J Biomed Inform, 39 (3), pp. 362-378. , CS06, Jun; Eichelberg, M., Aden, T., Riesmeier, J., Dogac, A., Laleci, G., A survey and analysis of electronic healthcare record standards (2005) ACM Computing Surveys, 37 (4). , EAR+05; Marshall, G., (2004) RFC 3881 - Security Audit and Access Accountability Message XML Data Definitions for Healthcare Applications, , http://www.faqs.org/rfcs/rfc3881.html, Mar04, last access 1.06.2007; Rector, A.L., Clinical terminology: Why is it so hard? (1999) Method Inform Med, 38, pp. 239-252. , Rec+99; Rector, A., Terminologies, ontologies, & SNOMED, What are they for? What would quality assurance mean? (2006) First European Conference on SNOMED CT, , http://www.hiww.org/smcs2006, Rec06, Paper presented at the, last access 1.06.2007; (2006) RIDE Deliverable D2.3.1: Requirements Analysis for the RIDE Roadmap, , http://www.srdc.metu.edu.tr/webpage/projects/ride/deliverables/RIDE-D2.3. 1-2006-09-28_final.pdf, Ride06, 09 last access 14.06.2007; (2007) RIDE Deliverable D3.2.1: Vision for a Europe-wide Semantically Interoperable EHealth Infrastructure, , http://www.srdc.metu.edu.tr/webpage/projects/ride/deliverables/ RIDE-D_3_2_1Vision-v1.5final.doc, Ride07, 02, last access 14.06.2007; (2007) RIDE Deliverable D3.1.2: Goals and Challenges II, , http://www.srdc.metu.edu.tr/webpage/projects/ride/deliverables/RIDED.3.1. 2_final_V2.pdf, Ride07a, 02, last access 14.06.2007; Smith, B., From concepts to clinical reality: An essay on the benchmarking of biomedical terminologies (2006) J Biomed Inform, 39 (3), pp. 288-298. , Smi+06, Jun; Schadow, G., Mead, C.N., Walker, M., The HL7 reference information model under scrutiny (2006) Studies in Health Technology and Informatics, Amsterdam, 124, pp. 151-156. , SMW06, The Netherlands: IOS Press; Sackmann, S., Strüker, J., Accorsi, R., Privacy and security in highly dynamic systems (2006) Communications of the ACM, 49 (9), pp. 32-38. , SSA06, (SPECIAL ISSUE: Privacy and security in highly dynamic systems); Tang, P.C., Ash, J.S., Bates, D.W., Overhage, J.M., Sands, D.Z., Personal health records: Definitions, benefits, and strategies for overcoming barriers to adoption (2006) Journal of the American Medical Informatics Association, 13, pp. 121-126. , TAB+06; Wagner, Public health surveillance: The role of clinical information systems (2004) Healthcare Information Management Systems, Cases, Strategies, and Solution, pp. 513-531. , Wag+04, Ball MJ, Weaver CA, Kiel JM (eds.), Chapter 39. Health Informatics Series, 3rd Ed. Springer-Verlag, 2004; World Health Organization Family of International Classifications: Definition, Scope and Purpose, , http://www.who.int/classifications/icd/docs/en/WHOFICFamily.pdf, WHO04, from, last access 1.12.2006 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - A number of Electronic Health Record (EHR) standards and frameworks have been developed to assist with the interoperability and integration of distributed EHR information. Ideally, all EHR systems would adopt common and systematized hierarchies of component names, use multi-lingual clinical coding systems with perfect cross-mappings and use identical reference models for measurements. However, this has not been realized yet. Not only do a number of international health information standards exist, such as CEN EN 13606, HL7 and GEHR, but each country, state, division, hospital and vendor usually has their own "standard clinical data model". Since it is not realistic to expect to have a single universally accepted clinical data model that will be adhered to all over Europe and that the clinical practice, terminology systems and EHR systems are all a long way from such a complete harmonisation. This paper presents some results of the RIDE project; a project that will address the interoperability of eHealth systems with special emphasis on semantic interoperability. The paper describes relevant goals for the development of the eHealth sector in Europe that have been identified in the project as common requirements for many eHealth applications and names the technical and organisational challenges accompanying these goals. ER - TY - JOUR T1 - Hospital adoption of interoperability functions A1 - Thompson, M P A1 - Graetz, I Y1 - 2019/// JF - Healthcare VL - 7 IS - 3 DO - 10.1016/j.hjdsi.2018.12.001 N2 - ©2019 Elsevier Inc. Background: The seamless transmission of patient health information across health care settings, commonly referred to as interoperability, is a focal point of federal electronic health record (EHR) incentive programs. The objective of this study was to examine the extent to which interoperability functions outlined in Promoting Interoperability Stage 3 (PI3) requirements have been adopted by US hospitals, and barriers to interoperability. Methods: We conducted a cross-sectional analysis of 2781 non-federal, acute-care hospitals responding to the 2015 American Hospital Association Information Technology (IT) Supplement survey. We described the percentage of hospitals that adopted PI3 functionalities, identified hospital characteristics associated with adoption, and compared barriers to interoperability between hospitals that have and have not adopted PI3 functionalities. Results: Only 16.7% of hospitals had adopted all six core functionalities required to meet PI3 objectives. Over 70% of hospitals had implemented at least four of six functionalities, while 1.8% implemented none. Major teaching (adjusted odds ratio [aOR]=1.66), system affiliated (aOR=1.63), and regional health information exchange participating hospitals (aOR=1.86) were more likely to adopt PI3 functionalities, while for-profit hospitals (OR=0.11) were less likely. Hospitals that adopted PI3 functionalities more frequently reported experiencing barriers to interoperability, including the receiving provider's ability and interest to send/receive data. Conclusions: While only a small proportion of hospitals had implemented all six PI3 functionalities at the time the requirements were finalized, the vast majority had already implemented most of the required functionalities. Still, several barriers stand in the way of achieving seamless interoperability, many of which lie outside hospitals' control. ER - TY - JOUR T1 - RD-connect: An integrated platform connecting databases, registries, biobanks and clinical bioinformatics for rare disease research A1 - Thompson, R A1 - Johnston, L A1 - Taruscio, D A1 - Monaco, L A1 - Béroud, C A1 - Gut, I G A1 - Hansson, M G A1 - T Hoen, P.-B.A. A1 - Patrinos, G P A1 - Dawkins, H A1 - Ensini, M A1 - Zatloukal, K A1 - Koubi, D A1 - Heslop, E A1 - Paschall, J E A1 - Posada, M A1 - Robinson, P N A1 - Bushby, K A1 - Lochmüller, H Y1 - 2014/// KW - Biocompatible Materials KW - Biological Specimen Banks KW - Computational Biology KW - Databases, Factual KW - Electronic health records KW - Genomics KW - Health Information Exchange KW - Humans KW - Rare Diseases KW - Registries KW - biobank KW - biology KW - clinical trials KW - databases KW - factual database KW - genetics KW - human KW - medical informatics KW - medical information system KW - rare disease KW - register JF - Journal of General Internal Medicine VL - 29 SP - S780 EP - S787 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905859770&doi=10.1007%2Fs11606-014-2908-8&partnerID=40&md5=3163653eff44f129bab327eef3be9b4e N1 - Cited By :73 Export Date: 10 September 2018 References: Gut, I.G., New sequencing technologies (2013) Clin Transl Oncol, 15 (11), pp. 879-881; Aymé, S., Rodwell, C., (2013) 2013 Report on the State of the Art of Rare Disease Activities in Europe, , July; Bushby, K., Lochmüller, H., Lynn, S., Straub, V., Interventions for muscular dystrophy: Molecular medicines entering the clinic (2009) Lancet, 28, pp. 1849-1856. , 374; Tremblay, J.P., Xiao, X., Aartsma-Rus, A., Translating the genomics revolution: The need for an international gene therapy consortium for monogenic diseases (2013) Mol Ther, 21 (2), pp. 266-268; International network of cancer genome projects (2010) Nature, 15, pp. 993-998. , The International Cancer Genome Consortium. 464; International Rare Disease Research Consortium (IRDiRC) Policies and Guidelines [Pdf], , http://www.irdirc.org/wp-content/up-loads/2013/06/ IRDiRC_Policies_Longversion_24May2013.pdf, Available at: Accessed April 1, 2014; (2013) Rare Diseases - How Europe Is Meeting the Challenges, , Commission E. Luxembourg: Publications Office of the European Union; 'T Hoen, P.A., Friedländer, M.R., Almlöf, J., Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories (2013) Nat Biotechnol, 31 (11), pp. 1015-1022; Church, D.M., Lappalainen, I., Sneddon, T.P., Public data archives for genomic structural variation (2010) Nat Genet, 42 (10), pp. 813-814; Groth, P., Gibson, A., Velterop, J., The anatomy of a nanopublication (2010) Information Services and Use, 30, pp. 51-56; Patrinos, G.P., Cooper, D.N., Van Mulligen, E., Gkantouna, V., Tzimas, G., Tatum, Z., Schultes, E., Mons, B., Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain (2012) Hum Mutat, 33 (11), pp. 1503-1512; Giardine, B., Borg, J., Higgs, D.R., Systematic documentation and analysis of human genetic variation in hemoglobinopathies using the microattribution approach (2011) Nat Genet, 43 (4), pp. 295-301; Firth, H.V., Richards, S.M., Bevan, A.P., DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources (2009) Am J Hum Genet, 84 (4), pp. 524-533; Yuille, M., Van Ommen, G.J., Bréchot, C., Biobanking for Europe (2008) Brief Bioinform, 9 (1), pp. 14-24; Crosswell, L.C., Thornton, J.M., ELIXIR: A distributed infrastructure for European biological data (2012) Trends Biotechnol, 30 (5), pp. 241-242; Editorial. Open to interpretation (2013) Nat Biotechnol, 31 (8), p. 661; Fokkema, I.F., Taschner, P.E., Schaafsma, G.C., Celli, J., Laros, J.F., Den Dunnen, J.T., LOVD v. 2.0: The next generation in gene variant databases (2011) Hum Mutat, 32 (5), pp. 557-563; Tuffery-Giraud, S., Béroud, C., Leturcq, F., Genotype-phenotype analysis in 2,405 patients with a dystrophinopathy using the UMD-DMD database: A model of nationwide knowledgebase (2009) Hum Mutat, 30 (6), pp. 934-945; Frédéric, M.Y., Lalande, M., Boileau, C., UMD-predictor, a new prediction tool for nucleotide substitution pathogenicity - Application to four genes: FBN1, FBN2, TGFBR1, and TGFBR2 (2009) Hum Mutat, 30 (6), pp. 952-959; Robinson, P., Köhler, S., Oellrich, A., Improved exome prioritization of disease genes through cross species phenotype comparison (2013) Genome Res, , Oct 25. [E-pub ahead of print]; Brudno, M., Gîrdea, M., Buske, O., PhenomeCentral: An Integrated Portal for Sharing and Searching Patient Phenotype Data for Rare Genet ic Disorders Figshare, , http://dx.doi.org/10.6084/m9.figshare.939458; Hunter, A.A., Macgregor, A.B., Szabo, T.O., Wellington, C.A., Bellgard, M.I., Yabi: An online research environment for grid, high performance and cloud computing (2012) Source Code Biol Med, 7 (1), p. 1; Lopes, P., Oliveira, J.L., COEUS: "semantic web in a box" for biomedical applications (2012) J Biomed Semantics, 3 (1), p. 11; Lopes, P., Oliveira, J.L., An innovative portal for rare genetic diseases research: The semantic Disease card (2013) J Biomed Inform, 21. , epub ahead of print; Hall, D., Huerta, M.F., McAuliffe, M.J., Farber, G.K., Sharing heterogeneous data: The national database for autism research (2012) Neuroinformatics, 10 (4), pp. 331-339; Orth, M., Handley, O.J., Schwenke, C., Dunnett, S.B., Craufurd, D., Ho, A.K., Wild, E., Landwehrmeyer, G.B., Observing Huntington' s Disease: The European Huntington's Disease Network's REGISTRY (2010) PLOS Currents Huntington Disease, , the European Huntington's Disease Network Tio. Sep 28. Edition 1; Lochmüller, H., Aymé, S., Pampinella, F., The Role of Biobanking in Rare Diseases: European Consensus Expert Group Report (2009) Biopreservation and Biobanking, 7 (3), pp. 155-156; Roos, M., Marshall, M.S., Gibson, A.P., Structuring and extracting knowledge for the support of hypothesis generation in molecular biology (2009) BMC Bioinformatics, 1 (10 SUPPL. 10), pp. S9; Köhler, S., Doelken, S.C., Mungall, C.J., The Human Phenotype Ontology project: Linking molecular biology and disease through phenotype data (2013) Nucl. Acids Res., , doi:10.1093/nar/gkt1026; Girdea, M., Dumitriu, S., Fiume, M., PhenoTips: Patient phenotyping software for clinical and research use (2013) Hum Mutat, 34 (8), pp. 1057-1065; Rath, A., Olry, A., Dhombres, F., Brandt, M.M., Urbero, B., Ayme, S., Representation of rare diseases in health information systems: The Orphanet approach to serve a wide range of end users (2012) Hum Mutat, 33 (5), pp. 803-808; Bushby, K., Lynn, S., Straub, V., Collaborating to bring new therapies to the patient - The TREAT-NMD model (2009) Acta Myol, 28 (1), pp. 12-15; McCormick, J., Mehta, G., Olesen, H.V., Viviani, L., Macek Jr., M., Mehta, A., Comparative demographics of the European cystic fibrosis population: A cross-sectional database analysis (2010) Lancet, 375 (9719), pp. 1007-1013. , European Registry Working Group; Tabrizi, S.J., Scahill, R.I., Owen, G., Predictors of phenotypic progression and disease onset in premanifest and early-stage Huntington's disease in the TRACK-HD study: Analysis of 36-month observational data (2013) Lancet Neurol, 12 (7), pp. 637-649; Global Rare Diseases Patient Registry and Data Repository. CDE Overview, , https://grdr.ncats.nih.gov/index.php?option=com_content&view= article&id=3&Itemid=5, Available at: Accessed 15 April 2014; Lochmüller, H., Schneiderat, P., Biobanking in rare disorders (2010) Adv Exp Med Biol, 686, pp. 105-113; Filocamo, M., Baldo, C., Goldwurm, S., Telethon Network of Genetic Biobanks: A key service for diagnosis and research on rare diseases (2013) Orphanet J Rare Dis, 8 (1), p. 129; Hansson, M.G., Van Ommen, G.J., Chadwick, R., Dillner, J., Patients would benefit from simplified ethical review and consent procedure (2013) Lancet Oncol, 14 (6), pp. 451-453; Bellgard, M., Beroud, C., Parkinson, K., Dispelling myths about rare disease registry system development (2013) Source Code Biol Med, 8 (1), p. 21; Wichmann, H.E., Kuhn, K.A., Waldenberger, M., Comprehensive catalog of European biobanks (2011) Nat Biotechnol, 29 (9), pp. 795-797; (2013) Orphanet Report Series: Disease Registries in Europe, , http://www.orpha.net/orphacom/cahiers/docs/GB/Registries.pdf, January Available at. Accessed 15 April 2014 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Research into rare diseases is typically fragmented by data type and disease. Individual efforts often have poor interoperability and do not systematically connect data across clinical phenotype, genomic data, biomaterial availability, and research/trial data sets. Such data must be linked at both an individual-patient and whole-cohort level to enable researchers to gain a complete view of their disease and patient population of interest. Data access and authorization procedures are required to allow researchers in multiple institutions to securely compare results and gain new insights. Funded by the European Union's Seventh Framework Programme under the International Rare Diseases Research Consortium (IRDiRC), RD-Connect is a global infrastructure project initiated in November 2012 that links genomic data with registries, biobanks, and clinical bioinformatics tools to produce a central research resource for rare diseases. © 2014 Society of General Internal Medicine. ER - TY - JOUR T1 - Design and development of a linked open data-based health information representation and visualization system: potentials and preliminary evaluation. A1 - Tilahun, Binyam A1 - Kauppinen, Tomi A1 - Keßler, Carsten A1 - Fritz, Fleur Y1 - 2014/// KW - HIV KW - Information Systems KW - Linked Open Data KW - Semantic Web KW - WHO KW - health information systems KW - ontology KW - public health KW - public health informatics KW - visualization PB - JMIR Publications Inc. JF - JMIR medical informatics VL - 2 IS - 2 SP - e31 EP - e31 CY - Toronto, Ontario N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)-a new Semantic Web set of best practice of standards to publish and link heterogeneous data-can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. OBJECTIVE The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. METHODS We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk-a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. RESULTS We developed an LOD-based health information representation, querying, and visualization system by using Linked Data tools. We imported more than 20,000 HIV-related data elements on mortality, prevalence, incidence, and related variables, which are freely available from the WHO global health observatory database. Additionally, we automatically linked 5312 data elements from DBpedia, Bio2RDF, and LinkedCT using the Silk framework. The system users can retrieve and visualize health information according to their interests. For users who are not familiar with SPARQL queries, we integrated a Linked Data search engine interface to search and browse the data. We used the system to represent and store the data, facilitating flexible queries and different kinds of visualizations. The preliminary user evaluation score by public health data managers and users was 82 on the SUS usability measurement scale. The need to write queries in the interface was the main reported difficulty of LOD-based systems to the end user. CONCLUSIONS The system introduced in this article shows that current LOD technologies are a promising alternative to represent heterogeneous health data in a flexible and reusable manner so that they can serve intelligent queries, and ultimately support decision-making. However, the development of advanced text-based search engines is necessary to increase its usability especially for nontechnical users. Further research with large datasets is recommended in the future to unfold the potential of Linked Data and Semantic Web for future health information systems development. ER - TY - JOUR T1 - An Interoperable System for Automated Diagnosis of Cardiac Abnormalities from Electrocardiogram Data A1 - Tinnakornsrisuphap, T A1 - Billo, R E Y1 - 2015/// KW - Automated diagnosis KW - Automated electrocardiogram (ECG) diagnosis KW - Automation KW - Biomedical equipment KW - Cardiovascular Abnormalities KW - Communication standards KW - Computer platforms KW - Diagnosis KW - Diagnosis, Computer-Assisted KW - Electrocardiography KW - Health Level 7 (HL7) KW - Heart KW - Humans KW - Internet browsers KW - Interoperability KW - Interoperable systems KW - Medical Devices KW - Medical device communication KW - Ontology KW - Proprietary software KW - Signal Processing, Computer-Assisted KW - Social networking (online) KW - Web browsers KW - World Wide Web KW - classification KW - computer assisted diagnosis KW - electrocardiography KW - human KW - procedures KW - signal processing JF - IEEE Journal of Biomedical and Health Informatics VL - 19 IS - 2 SP - 493 EP - 500 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84924731410&doi=10.1109%2FJBHI.2014.2321515&partnerID=40&md5=925562cf65c247e7b4538a1a9fd5dcfd N1 - Cited By :2 Export Date: 10 September 2018 References: Hughes, N., Tarassenko, L., Roberts, S., Markovmodels for Automated ECG Interval analysis (2004) Advances in Neural Information Processing Systems 16 (NIPS 2003), , S. Thrun, L. Saul, and B. Schoelkopf, Eds. Cambridge, MA: MIT Press; Hiroki, H., Arakawa, K., Muramatsu, J., Sugimoto, J.T., Sawayama, T., Inoue, K., Kawai, N., Mizutani, T., New electrocardiographic criteria for diagnosing right ventricular hypertrophy inmitral stenosis-comparison with the Bonner's and Mortara's criteria (1988) J. Japanese Circulation, 52 (10), pp. 1114-1120; Heden, B., Hans, O., Rittner, R., Edenbrandt, L., Acute myocardial infarction detected in the 12-lead ECG by artificial neural networks (1997) Circulation, 96 (6), pp. 1798-1802; Porela, P., Hanninen, K., Vuorenmaa, T., Arstila, M., Pulkki, K., Bredbacka, A., Antila, K.J., Voipio- Pulkki, L.-M., Computer-assisted electrocardiograhy in structured diagnosis of acute myocardial infarction (1999) J. Scand. Cardiovasc., 33 (2), pp. 89-96; (2005) Health Informatics. Standard Communication Protocol. Computer-Assisted Electrocardiography, , IST/35 Standard BS EN 1064; (2014) Health Level Seven (HL7), , http://www.hl7.org, Online Available; (2003) Draft Standard for Health Informatics-Point-of-Care Medical Device Communication-Nomenclature, pp. 62-81. , IEEE P1073-1.1.1/d08; Jenkins, D., Gerred, S., (1996) ECG Library, , http://www.ecglibrary.com/ecghome.html, Online Available; Yanowitz, F.G., (2005) ECG Learning Center, , http://ecg.utah.edu, Online Available; Wang, H., Azuaje, F., Clifford, G., Jung, B., Black, N., Methods and Tools for Generating and Managing ecgML-based information (2004) Computers in Cardiology, 31. , Chicago, IL, USA: IEEE; HL7 aECG Implementation Guide, , http://en.wikipedia.org/wiki/HL7_aECG, Online Available; (2005) E.C.G. Interpretation Made Incredibly Easy, 3rd Ed., , Philadelphia, PA: Lippincott Williams & Wilkins; Dubin, D., (2000) Rapid Interpretation of EKG's, 6th Ed., , Tampa, FL, USA: Cover Publishing Company; Marriott, H.J.L., (1988) Practical Electrocardiography, , Philadelphia, PA, USA: Williams & Wilkins; Walmsley, P., (2013) Definitive X.M.L.Schema, 2nd Ed., , Englewood Cliffs, NJ, USA: Prentice-Hall; Goldberger, A.L., Amaral, L.A.N., Glass, L., Hausdorff, J.M., Ivanov, P.C., Mark, R.G., Mietus, J.E., Stanley, H.E., Physiobank, Physiotoolkit, and Physionet: Components of a new research resource for complex physiologic signals Circulation, 101 (23), pp. e215-e220. , http://circ.ahajournals.org/cgi/content/full/101/23/e215, Online Available; (2014) E.C.G. Databases, , http://physionet.org/physiobank/database/#ecg, Online Available; Hayter, A.J., (1996) Probability and Statistics for Engineers and Scientists, , Boston, MA: PWS-Kent; Kaufman, S., Poupyrev, I., Miller, E., Billinghurst, M., Oppenheimer, P., Weghorst, S., New Interface Metaphors for Complex Information Space Visualization: An ECG Monitor Object prototype (1997) Medicine Meets Virtual Reality: Global Healthcare Grid, pp. 131-140. , San Diego, CA: IOS Press; Ayesta, U., Serrano, L., Romero, I., Complexity measure revisited: A new algorithm for classifying cardiac arrhythmias Proc. 23rd Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2001, 2, pp. 1589-1591; Burstein, H., (1971) Attribute Sampling: Tables and Explanations; Tables for Determining Confidence Limits and Sample Size Based on Close Approximations of the Binomial Distribution, , Burr Ridge, IL: McGraw-Hill RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Electrocardiogram (ECG) data are stored and analyzed in different formats, devices, and computer platforms. As a result, ECG data from different monitoring devices cannot be displayed unless the user has access to the proprietary software of each particular device. This research describes an ontology and encoding for representation of ECG data that allows open exchange and display of ECG data in a web browser. The ontology is based on the Health Level Seven (HL7) medical device communication standard. It integrates ECG waveform data, HL7 standard ECG data descriptions, and cardiac diagnosis rules, providing a capability to both represent ECG waveforms as well as perform automated diagnosis of 37 different cardiac abnormalities. The ECG ontology is encoded in XML, thus allowing ECG data from any digital ECG device that maps to it to be displayed in a general-purpose Internet browser. An experiment was conducted to test the interoperability of the system (ability to openly share ECG data without error in a web browser) and also to assess the accuracy of the diagnosis model. Results showed 100% interoperability using 276 ECG data files and 93% accuracy in diagnosis of abnormal cardiac conditions. © 2013 IEEE. ER - TY - JOUR T1 - A data driven multi-layer framework of pervasive information computing system for ehealthcare A1 - Tiwari, V A1 - Tiwari, B Y1 - 2019/// JF - International Journal of E-Health and Medical Communications VL - 10 IS - 4 SP - 66 EP - 85 DO - 10.4018/IJEHMC.2019100106 N2 - ©2019, IGI Global. In the last decade, significant advancements in telecommunications and informatics have seen which incredibly boost mobile communications, wireless networks, and pervasive computing. It enables healthcare applications to increase human livelihood. Furthermore, it seems feasible to continuous observation of patients and elderly individuals for their wellbeing. Such pervasive arrangements enable medical experts to analyse current patient status, minimise reaction time, increase livelihood, scalability, and availability. There is found plenty of remote patient monitoring model in literature, and most of them are designed with limited scope. Most of them are lacking to give an overall unified, complete model which talk about all state-of-the-art functionalities. In this regard, remote patient monitoring systems (RPMS's) play important roles through wearable devices to monitor the patient's physiological condition. RPMS also enables the capture of related videos, images, and frames. RPMS do not mean to enable only capturing various sorts of patient-related information, but it also must facilitate analytics, transformation, security, alerts, accessibility, etc. In this view, RPMS must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates these issues. The system has been classified into five fundamental layers: The data acquisition layer, the data pre-processing layer, the network and data transfer layer, the data management layer and the data accessing layer. It enables patient care at real-time using the network infrastructure efficiently. A detailed discussion on various security issues have been carried out. Moreover, standard deviation-based data reduction and a machine-learning-based data access policy is also proposed. ER - TY - JOUR T1 - Towards a cross-domain interoperable framework for natural hazards and disaster risk reduction information A1 - Tomas, R A1 - Harrison, M A1 - Barredo, J I A1 - Thomas, F A1 - Llorente Isidro, M A1 - Pfeiffer, M A1 - Čerba, O Y1 - 2015/// KW - Disasters KW - Humanism KW - Humanities KW - Humans JF - Natural Hazards VL - 78 IS - 3 SP - 1545 EP - 1563 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938984500&doi=10.1007%2Fs11069-015-1786-7&partnerID=40&md5=6a504704267712f685dfa3e042f91d17 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Tomas et al. - 2015 - Towards a cross-domain interoperable framework for natural hazards and disaster risk reduction information.pdf N1 - Export Date: 19 March 2018 Export Date: 10 September 2018 References: Aven, T., Renn, O., Risk management and governance: concepts, guidelines and applications, vol 16. Risk, governance and society. Springer, Berlin (2010) doi:10.1007/978-3-642-13926-0_1; Birkland, T.A., (2006) Lessons of disaster: policy change after catastrophic events, , American Governance and Public Policy Series, Georgetown University Press, Washington, DC; Directive 2007/2/EC, of 14th March, establishing an infrastructure for spatial information in the European Community (INSPIRE) (2007) Off J Eur Union, 24 (5), p. 2007; Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks (2007) Off J Eur Union, 6 (11), p. 2007; Commission Staff Working Paper on Risk Assessment and Mapping Guidelines for Disaster Management, Commission of the European Communities (2010) Brussels, 21, p. 12; Commission Regulation (EU) No. 1253/2013 of 21 October 2013 amending Regulation (EU) No. 1089/2010 implementing Directive 2007/2/EC as regards interoperability of spatial data sets and services (2013) Official Journal of the European Union, 10 (12), p. 2013; Cetl, V., Tuchyna, M., Nunes De Lima, M.V., Tóth, K., Lutz, M., Smits, P., INSPIRE Annex II and III themes testing and consultation summary. Joint Research Centre (2012) JRC Scientific and Policy Reports, p. 42; Craglia, M., Campagna, M., Advanced regional SDI in Europe: comparative cost-benefit evaluation and impact assessment perspectives (2010) Int J Spat Data Infrastruct Res, 5, pp. 145-167; http://forest.jrc.ec.europa.eu/effis, EFFIS (2014) European Forest Fire Information system (EFFIS). Accessed 31 Jan 2014; Data specification on Natural Risk Zones—technical guidelines. European Commission, Joint Research Centre (2013) D2.8.III.12_v3, p. 135; Drafting team “data specifications” methodology for the development of data specifications (2008) INSPIRE drafting team “data specifications”, p. 123; http://inspire.ec.europa.eu/documents/Data_Specifications/Stakeholder_Consultation_2011_Resolution_Table.xlsx, INSPIRE (2011) Stakeholder consultation 2011 resolution table. Accessed 30 June 2014; Consultation results - INSPIRE data specifications Annex II and III Comments and resolution (2013) INSPIRE, , http://inspire.jrc.ec.europa.eu/documents/Data_Specifications/Stakeholder_Consultation_2011_Resolution_Table.xlsx; D2.5: Generic conceptual model, version 3.4 (2013) INSPIRE drafting team “data specifications”, p. 152; http://inspire.ec.europa.eu/codelist/ExposedElementCategoryValue/, INSPIRE (2014a) Exposed element category. Accessed 31 Jan 2014; http://inspire.ec.europa.eu/codelist/, INSPIRE (2014b) INSPIRE code list register. Accessed 31 Jan 2014; http://inspire-geoportal.ec.europa.eu/, INSPIRE (2014c) INSPIRE GeoPortal. Accessed 30 June 2014; http://inspire.ec.europa.eu/index.cfm/pageid/5160, INSPIRE (2014d) INSPIRE maintenance and implementation. Accessed 31 Jan 2014; http://inspire.ec.europa.eu/index.cfm/pageid/181, INSPIRE (2014e) INSPIRE stakeholders. Accessed 31 Jan 2014; http://inspire.ec.europa.eu/index.cfm/pageid/601, INSPIRE (2014f) User requirements survey. Accessed 31 Jan 2014; http://inspire.ec.europa.eu/index.cfm/pageid/481, INSPIRE (2014 g) Who’s who in INSPIRE. Accessed 31 Jan 2014; Drafting Team Data Specifications, I.N.S.P.I.R.E., Drafting team “data specifications” methodology for the development of data specifications (2008) INSPIRE, p. 123; ISO 19107 geographic information—spatial schema (2003) ISO, p. 166; ISO 19123 geographic information—Schema for coverage geometry and functions (2005) ISO, p. 65; ISO 19131 geographic information—data product specifications (2007) ISO, p. 40; ISO 31010 Risk management—risk assessment techniques (2009) ISO, p. 176; Merrill, D.F., Alexander, M.E., Glossary of forest fire management terms. Canadian Committee on Forest Fire Management, National Research Council of Canada, ON Pub. NRCC No. 26516 (1987) Ottawa, p. 91; Olcina, J., Ayala, F.J., Riesgos Naturales. Conceptos fundamentales y clasificación (2002) Ariel, p. 1512; Reichardt, M., Open standards-based geoprocessing Web services support the study and management of hazard and risk geomatics (2010) Nat Hazards Risk, 1, pp. 171-184; Toth, K., Portele, C., Illert, A., Lutz, M., de Lima, M.N., A conceptual model for developing interoperability specifications in spatial data infrastructures. European Commission - Joint Research Centre, EUR 25280 EN, Publications Office of the European Union (2012) Luxemburg, p. 62; UNISDR terminology on disaster risk reduction. United Nations International Strategy for Disaster Reduction (UNISDR) (2009) Geneva, p. 30; Nations, U., Hyogo framework for action 2005–2015: building the resilience of nations and communities to disasters. UN - International Strategy for Disaster Reduction, A/CONF. 206/6, United Nations, Hyogo (2005) Japan, p. 22; Van Wagner, C.E., Development and structure of the Canadian Forest Fire Weather Index System. Canadian Forestry Service, Forestry Technical Report, 35, Headquarters (1987) Ottawa, p. 37 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-EXCLUSION-REASONS: possibly useful methods? N2 - According to the United Nations’ International Strategy for Disaster Reduction, “natural hazards are processes or phenomena that may cause loss of life, injury or other health impacts, property damage, loss of livelihoods and services, social and economic disruption, or environmental damage”. They are at the interface between human and natural systems. From this perspective, natural hazards are a multidimensional domain including environmental issues, the private and public sector and citizens and governance ranging from local to supranational. The vast amount of information and data necessary for comprehensive hazard and risk assessment present many challenges regarding the lack of accessibility, comparability, quality, organisation and dissemination of natural hazards spatial data. In order to mitigate these limitations, an interoperability framework has been developed and published in the INSPIRE Data Specification on Natural Risk Zones—technical guidelines (DS) document. This framework provides means for facilitating access, integration, harmonisation and dissemination of natural hazard data from different domains and sources. The objective of this paper is twofold. Firstly, the paper highlights the key aspects of the interoperability to the various natural hazard communities and illustrates the applicability of the interoperability framework developed in the DS. And secondly, the paper “translates” into common language the main features and potentiality of the interoperability framework of the DS for a wider audience of scientists and practitioners in the natural hazard domain. In this paper, the four pillars of the interoperability framework will be presented. First, the adoption of a common terminology for the natural hazard domain will be addressed. A common data model to facilitate cross-domain data integration will then follow. Thirdly, the common methodology developed to express qualitative or quantitative assessments of natural hazards is presented. Fourthly, the extensible classification schema for natural hazards developed from a literature review and key reference documents from the contributing community of practice is discussed. Furthermore, the applicability of the interoperability framework for the various stakeholder groups is illustrated. This paper closes discussing main advantages, limitations and next steps regarding the sustainability and evolution of the interoperability framework. © 2015, The Author(s). ER - TY - JOUR T1 - IDOMAL: An ontology for malaria A1 - Topalis, P A1 - Mitraka, E A1 - Bujila, I A1 - Deligianni, E A1 - Dialynas, E A1 - Siden-Kiamos, I A1 - Troye-Blomberg, M A1 - Louis, C Y1 - 2010/// KW - Animals KW - Computational Biology KW - Databases, Factual KW - Disease Vectors KW - Humanism KW - Humanities KW - Humans KW - Information Storage and Retrieval KW - Insecticide Resistance KW - Malaria KW - Software KW - Vocabulary, Controlled KW - animal KW - article KW - biology KW - computer program KW - disease carrier KW - disease transmission KW - epidemiological data KW - factual database KW - human KW - information retrieval KW - information technology KW - insecticide resistance KW - linguistics KW - malaria KW - malaria control KW - methodology JF - Malaria Journal VL - 9 IS - 1 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955290526&doi=10.1186%2F1475-2875-9-230&partnerID=40&md5=1a13e9f38e9b3d49fd936322434a32fe N1 - Cited By :16 Export Date: 10 September 2018 References: Roberts, L., Enserink, M., Malaria. Did they really say . eradication? (2007) Science, 318, pp. 1544-1545. , 10.1126/science.318.5856.1544. 18063766; Mendis, K., Rietveld, A., Warsame, M., Bosman, A., Greenwood, B., Wernsdorfer, W.H., From malaria control to eradication: The WHO perspective (2009) Trop Med Int Health, 14, pp. 802-809. , 10.1111/j.1365-3156.2009.02287.x. 19497083; Greenwood, B., Can malaria be eliminated? (2009) Trans R Soc Trop Med Hyg, 103 (SUPPL. 1), pp. 192-5. , 10.1016/j.trstmh.2008.10.027. 19062058; Topalis, P., Lawson, D., Collins, F.H., Louis, C., How can ontologies help vector biology? (2008) Trends Parasitol, 24, pp. 249-252. , 10.1016/j.pt.2008.03.002. 18440275; Topalis, P., Dialynas, E., Mitraka, E., Deliyanni, E., Siden-Kiamos, I., Louis, C., A set of ontologies to drive tools for the control of vector-borne diseases (2010) J Biomed Inform, , 20363364; The Gene Ontology project in 2008 (2008) Nucleic Acids Res, 36, pp. 4440-D444. , Gene Ontology Consortium, 10.1093/nar/gkm883. 17984083; Lawson, D., Arensburger, P., Atkinson, P., Besansky, N.J., Bruggner, R.V., Butler, R., Campbell, K.S., Collins, F.H., VectorBase: A data resource for invertebrate vector genomics (2009) Nucl Acids Res, 37, pp. 4583-587. , 10.1093/nar/gkn857. 19028744; Dialynas, E., Topalis, P., Vontas, J., Louis, C., MIRO and IRbase: IT Tools for the Epidemiological Monitoring of Insecticide Resistance in Mosquito Disease Vectors (2009) PLoS Negl Trop Dis, 3, p. 5465. , 10.1371/journal.pntd.0000465. 19547750; Day-Richter Ma, J., Harris, M., OBO-Edit - An ontology editor for biologists (2007) Bioinformatics, 23, pp. 2198-2200. , Haendel Gene Ontology OBO-Edit Working Group S Lewis 10.1093/ bioinformatics/btm112. 17545183; Browse Gene Ontology Files on SourceForge.net, , http://sourceforge.net/projects/geneontology/files/OBO- Edit%202%20%5Bcurrent%20release%5D/oboedit2.0/; Simon, J., Dos Santos, M., Fielding, J., Smith, B., Formal ontology for natural language processing and the integration of biomedical databases (2006) Int J Med Inform, 75, pp. 224-231. , 10.1016/j.ijmedinf.2005.07.015. 16153885; Grenon, P., Smith, B., Goldberg, L., Biodynamic ontology: Applying BFO in the biomedical domain (2004) Stud Health Technol Inform, 102, pp. 20-38. , 15853262; Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L.J., Lewis, S., The OBO Foundry: Coordinated evolution of ontologies to support biomedical data integration (2007) Nat Biotechnol, 25, pp. 1251-1255. , 10.1038/nbt1346. 17989687; IDOMAL, , http://anobase.vectorbase.org/idomal/IDOMAL.obo; NCBO BioPortal: Malaria Ontology, , http://bioportal.bioontology.org/visualize/40463; Infectious Disease Ontology, , http://www.infectiousdiseaseontology.org/Home.html; Haendel, M.A., Neuhaus, F., Osumi-Sutherland, O., Mabee, P.M., Mejino Jr., J.L.V., Mungall, C.J., Smith, B., CARO - The Common Anatomy Reference Ontology (2007) Anatomy Ontologies for Bioinformatics, pp. 327-349. , London: Springer Burger A, Davidson D, Baldock R; Topalis, P., Tzavlaki, C., Vestaki, K., Dialynas, E., Sonenshine, D.E., Butler, R., Bruggner, R.V., Louis, C., Anatomical ontologies of mosquitoes and ticks, and their web browsers in VectorBase (2008) Insect Mol Biol, 17, pp. 87-89. , 18237287; Smith, B., Grenon, P., The cornucopia of formal-ontological relations (2004) Dialectica, 58, pp. 279-296. , 10.1111/j.1746-8361.2004.tb00305.x; The Environment Ontology (EnvO)-Linking Environmental Data, , http://www.environmentontology.org/; Robson, K.J., Hall, J.R., Jennings, M.W., Harris, T.J., Marsh, K., Newbold, C.I., Tate, V.E., Weatherall, D.J., A highly conserved amino-acid sequence in thrombospondin, properdin and in proteins from sporozoites and blood stages of a human malaria parasite (1988) Nature, 335, pp. 79-82. , 10.1038/335079a0. 3045563; Spaccapelo, R., Naitza, S., Robson, K.J., Crisanti, A., Thrombospondin-related adhesive protein (TRAP) of Plasmodium berghei and parasite motility [1] (1997) Lancet, 350 (9074), p. 335. , DOI 10.1016/S0140-6736(97)24031-6; Sultan, A.A., Thathy, V., Frevert, U., Robson, K.J., Crisanti, A., Nussenzweig, V., Nussenzweig, R.S., Ménard, R., TRAP is necessary for gliding motility and infectivity of plasmodium sporozoites (1997) Cell, 90, pp. 511-522. , 10.1016/S0092-8674(00)80511-5. 9267031; Akhouri, R.R., Sharma, A., Malhotra, P., Sharma, A., Role of Plasmodium falciparum thrombospondin-related anonymous protein in host-cell interactions (2008) Malar J, 7, p. 63. , 10.1186/1475-2875-7-63. 18426606; Morahan, B.J., Wang, L., Coppel, R.L., No TRAP, no invasion (2009) Trends Parasitol, 25, pp. 77-84. , 10.1016/j.pt.2008.11.004. 19101208; Aurrecoechea, C., Brestelli, J., Brunk, B.P., Dommer, J., Fischer, S., Gajria, B., Gao, X., Wang, H., PlasmoDB: A functional genomic database for malaria parasites (2009) Nucleic Acids Res, 37, pp. 4539-543. , 10.1093/nar/gkn814. 18957442; Dolo, A., Modiano, D., Doumbo, O., Bosman, A., Sidibé, T., Keita, M.M., Naitza, S., Crisanti, A., Thrombospondin related adhesive protein (TRAP), a potential malaria vaccine candidate (1999) Parassitologia, 41, pp. 425-428. , 10697897; Epstein, J.E., Giersing, B., Mullen, G., Moorthy, V., Richie, T.L., Malaria vaccines: Are we getting closer? (2007) Curr Opin Mol Ther, 9, pp. 12-24. , 17330398; Artavanis-Tsakonas, K., Tongren, J.E., Riley, E.M., The war between the malaria parasite and the immune system: Immunity, immunoregulation and immunopathology (2003) Clin Exp Immunol, 133, pp. 145-152. , 10.1046/j.1365-2249.2003.02174.x. 12869017; Hviid, L., Naturally acquired immunity to Plasmodium falciparum malaria in Africa (2005) Acta Trop, 95, pp. 270-275. , 10.1016/j.actatropica.2005.06.012. 16018958; Dimopoulos, G., Insect immunity and its implication in mosquito-malaria interactions (2003) Cell Microbiol, 5, pp. 3-14. , 10.1046/j.1462-5822.2003.00252.x. 12542466; Alphey, L., Natural and engineered mosquito immunity (2009) J Biol, 8, p. 40. , 10.1186/jbiol143. 19439051; The Gene Ontology in 2010: Extensions and refinements (2010) Nucleic Acids Res, 38, pp. 4331-335. , Gene Ontology Consortium, 10.1093/nar/gkp1018. 19920128 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Background. Ontologies are rapidly becoming a necessity for the design of efficient information technology tools, especially databases, because they permit the organization of stored data using logical rules and defined terms that are understood by both humans and machines. This has as consequence both an enhanced usage and interoperability of databases and related resources. It is hoped that IDOMAL, the ontology of malaria will prove a valuable instrument when implemented in both malaria research and control measures. Methods. The OBOEdit2 software was used for the construction of the ontology. IDOMAL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium. Results. The first version of the malaria ontology covers both clinical and epidemiological aspects of the disease, as well as disease and vector biology. IDOMAL is meant to later become the nucleation site for a much larger ontology of vector borne diseases, which will itself be an extension of a large ontology of infectious diseases (IDO). The latter is currently being developed in the frame of a large international collaborative effort. Conclusions. IDOMAL, already freely available in its first version, will form part of a suite of ontologies that will be used to drive IT tools and databases specifically constructed to help control malaria and, later, other vector-borne diseases. This suite already consists of the ontology described here as well as the one on insecticide resistance that has been available for some time. Additional components are being developed and introduced into IDOMAL. © 2010 Topalis et al; licensee BioMed Central Ltd. ER - TY - JOUR T1 - Patient data discovery platforms as enablers of biomedical and translational research: A systematic review A1 - Trifan, A A1 - Oliveira, J L Y1 - 2019/// JF - Journal of Biomedical Informatics VL - 93 DO - 10.1016/j.jbi.2019.103154 N2 - ©2019 Background: The global shift from paper health records to electronic ones has led to an impressive growth of biomedical digital data along the past two decades. Exploring and extracting knowledge from these data has the potential to enhance translational research and lead to positive outcomes for the population's health and healthcare. Obective: The aim of this study was to conduct a systematic review to identify software platforms that enable discovery, secondary use and interoperability of biomedical data. Additionally, we aim evaluating the identified solutions in terms of clinical interest and main healthcare-related outcomes. Methods: A systematic search of the scientific literature published and indexed in Pubmed between January 2014 and September 2018 was performed. Inclusion criteria were as follows: relevance for the topic of biomedical data discovery, English language, and free full text. To increase the recall, we developed a semi-automatic and incremental methodology to retrieve articles that cite one or more of the previous set. Results: A total number of 500 candidate papers were retrieved through this methodology. Of these, 85 were eligible for abstract assessment. Finally, 37 studies qualified for a full-text review, and 20 provided enough information for the study objectives. Conclusions: This study revealed that biomedical discovery platforms are both a current necessity and a significantly innovative agent in the area of healthcare. The outcomes that were identified, in terms of scientific publications, clinical studies and research collaborations stand as evidence. ER - TY - JOUR T1 - Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: Why and how? A1 - Trifirò, G A1 - Coloma, P M A1 - Rijnbeek, P R A1 - Romio, S A1 - Mosseveld, B A1 - Weibel, D A1 - Bonhoeffer, J A1 - Schuemie, M A1 - van der Lei, J A1 - Sturkenboom, M Y1 - 2014/// KW - Adverse Drug Reaction Reporting Systems KW - Claims database KW - Databases, Factual KW - Drug Monitoring KW - Drug monitoring KW - Electronic Health Records KW - Electronic health records KW - Guillain Barre syndrome KW - Humans KW - Needs Assessment KW - Pharmaceutical Preparations KW - Population Surveillance KW - Postmarketing KW - Product Surveillance, Postmarketing KW - Product surveillance KW - Vaccine KW - Vaccines KW - acute heart infarction KW - cardiovascular effect KW - claims database KW - clinical practice KW - data base KW - disease course KW - disease predisposition KW - drug exposure KW - drug industry KW - drug monitoring KW - drug safety KW - drug surveillance program KW - drug utilization KW - electronic health records KW - food and drug administration KW - health care delivery KW - health care management KW - health care organization KW - health care personnel KW - health care utilization KW - human KW - ibuprofen KW - influenza vaccine KW - information processing KW - medical society KW - narcolepsy KW - national health organization KW - nonsteroid antiinflammatory agent KW - pharmacoepidemiology KW - postmarketing KW - postmarketing surveillance KW - priority journal KW - product surveillance KW - public health service KW - quality control KW - reimbursement KW - review KW - risk factor KW - rofecoxib KW - seasonal influenza KW - vaccine JF - Journal of Internal Medicine VL - 275 IS - 6 SP - 551 EP - 561 DO - 10.1111/joim.12159 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901981432&doi=10.1111%2Fjoim.12159&partnerID=40&md5=e2db366babc45d783a7f686ea53bb19f N1 - Cited By :39 Export Date: 5 April 2018 N2 - A growing number of international initiatives (e.g. EU-ADR, Sentinel, OMOP, PROTECT and VAESCO) are based on the combined use of multiple healthcare databases for the conduct of active surveillance studies in the area of drug and vaccine safety. The motivation behind combining multiple healthcare databases is the earlier detection and validation, and hence earlier management, of potential safety issues. Overall, the combination of multiple healthcare databases increases statistical sample size and heterogeneity of exposure for postmarketing drug and vaccine safety surveillance, despite posing several technical challenges. Healthcare databases generally differ by underlying healthcare systems, type of information collected, drug/vaccine and medical event coding systems and language. Therefore, harmonization of medical data extraction through homogeneous coding algorithms across highly different databases is necessary. Although no standard procedure is currently available to achieve this, several approaches have been developed in recent projects. Another main challenge involves choosing the work models for data management and analyses whilst respecting country-specific regulations in terms of data privacy and anonymization. Dedicated software (e.g. Jerboa) has been produced to deal with privacy issues by sharing only anonymized and aggregated data using a common data model. Finally, storage and safe access to the data from different databases requires the development of a proper remote research environment. The aim of this review is to provide a summary of the potential, disadvantages, methodological issues and possible solutions concerning the conduct of postmarketing multidatabase drug and vaccine safety studies, as demonstrated by several international initiatives. © 2014 The Association for the Publication of the Journal of Internal Medicine. ER - TY - CONF T1 - Exposing public health surveillance data using existing standards A1 - Turbelin, C A1 - Boëlle, P.-Y. Y1 - 2013/// KW - Artificial Intelligence KW - Data Mining KW - Data Standards KW - Electronic Health Records KW - Guidelines as Topic KW - Internationality KW - Medical Record Linkage KW - Natural Language Processing KW - Public Health KW - Public Health Surveillance KW - Vocabulary, Controlled KW - artificial intelligence KW - controlled vocabulary KW - data mining KW - electronic medical record KW - health survey KW - international cooperation KW - medical record KW - natural language processing KW - practice guideline KW - procedures KW - standards KW - statistics and numerical data VL - 192 IS - 1 SP - 802 EP - 806 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84894312498&doi=10.3233%2F978-1-61499-289-9-802&partnerID=40&md5=d0192cdcce02dcfb21820cd02b3551c9 N1 - Export Date: 10 September 2018 References: Thacker, S.B., Qualters, J.R., Lee, L.M., Public health surveillance in the united states: Evolution and challenges (2012) MMWR Surveill Summ, 61 (SUPPL.), pp. 3-9. , Jul 27; Tsui, F.C., Espino, J.U., Dato, V.M., Gesteland, P.H., Hutman, J., Wagner, M.M., Technical description of rods: A real-time public health surveillance system (2003) J Am Med Inform Assoc, 10 (5), pp. 399-408. , Sep-Oct; Polgreen, P.M., Chen, Y., Pennock, D.M., Nelson, F.D., Using internet searches for influenza surveillance (2008) Clin Infect Dis, 47 (11), pp. 1443-1448. , Dec 1; St Louis, C., Zorlu, G., Can twitter predict disease outbreaks? (2012) BMJ, 344, pp. e2353; Brownstein, J.S., Freifeld, C.C., Madoff, L.C., Digital disease detection-harnessing the web for public health surveillance (2009) N Engl J Med, 360 (21), pp. 2153-2155. , May 21, 7; Hanson, B., Sugden, A., Alberts, B., Making data maximally available (2011) Science, 331 (6018), p. 649. , Feb 11; Walport, M., Brest, P., Sharing research data to improve public health (2011) Lancet, 377 (9765), pp. 537-539. , Feb 12; Barrett, T., Troup, D.B., Wilhite, S.E., Ledoux, P., Evangelista, C., Kim, I.F., Tomashevsky, M., Soboleva, A., Ncbi geo: Archive for functional genomics data sets-10 years on (2011) Nucleic Acids Res, 39 (DATABASE ISSUE), pp. D1005-D1010. , Jan; Taylor, C.F., Field, D., Sansone, S.A., Aerts, J., Apweiler, R., Ashburner, M., Ball, C.A., Wiemann, S., Promoting coherent minimum reporting guidelines for biological and biomedical investigations: The mibbi project (2008) Nat Biotechnol, 26 (8), pp. 889-896. , Aug; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., Shabo Shvo, A., Hl7 clinical document architecture, release 2 (2006) J Am Med Inform Assoc, 13 (1), pp. 30-39. , Jan-Feb; Orlova, A.O., Dunnagan, M., Finitzo, T., Higgins, M., Watkins, T., Tien, A., Beales, S., Electronic health record-public health (ehr-ph) system prototype for interoperability in 21st century healthcare systems (2005) AMIA Annu Symp Proc, pp. 575-579; Clinical Data Interchange Standards Consortium, , http://www.cdisc.org, cited 2012 09/08/2012; Gallagher, J., Potter, N., Sgouros, T., Hankin, S., Flierl, G., (2007) The Data Access Protocol-DAP 2.0. NASA, , http://www.opendap.org/pdf/ESE-RFC-004v1.2.pdf; Network Common Data Form (NetCDF), , http://www.unidata.ucar.edu/software/netcdf/, 11/09/2011; (2012) Open Data Protocol. Microsoft, , http://www.odata.org/; (2012) DSPL: Dataset Publishing Language, , https://developers.google.com/public-data/, 29 nov 2012; http://www.sdmx-hd.org/; Flahault, A., Blanchon, T., Dorleans, Y., Toubiana, L., Vibert, J.F., Valleron, A.J., Virtual surveillance of communicable diseases: A 20-year experience in france (2006) Stat Methods Med Res, 15 (5), pp. 413-421. , Oct; Turbelin, C., Boelle, P.Y., Improving general practice based epidemiologic surveillance using desktop clients: The french sentinel network experience (2010) Stud Health Technol Inform, 160 (PART 1), pp. 442-446; Reichman, O.J., Jones, M.B., Schildhauer, M.P., Challenges and opportunities of open data in ecology (2011) Science, 331 (6018), pp. 703-705. , Feb 11; Challenges and opportunities (2011) Introduction. Science, 331 (6018), pp. 692-693. , Dealing with data. Feb 11; Overpeck, J.T., Meehl, G.A., Bony, S., Easterling, D.R., Climate data challenges in the 21st century (2011) Science, 331 (6018), pp. 700-702. , Feb 11; Lang, T., Advancing global health research through digital technology and sharing data (2011) Science, 331 (6018), pp. 714-717. , Feb 11; Sankoh, O., Ijsselmuiden, C., Sharing research data to improve public health: A perspective from the global south (2011) Lancet, 378 (9789), pp. 401-402. , Jul 30; Pisani, E., Abouzahr, C., Sharing health data: Good intentions are not enough (2010) Bull World Health Organ, 88 (6), pp. 462-466. , Jun; Whitaker, P., WHO Indicator and Metadata Registry (IMR), SDMX-HD Aggregate Data Exchange 2009, , http://sdmx.org/wpcontent/uploads/2009/10/sdmx_who_imr.pdf RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - With the growing use of information technologies, an increased volume of data is produced in Public Health Surveillance, enabling utilization of new data sources and analysis methods. Public health and research will benefit from the use of data standards promoting harmonization and data description through metadata. No data standard has yet been universally accepted for exchanging public health data. In this work, we implemented two existing standards eligible to expose public health data: Statistical Data and Metadata Exchange-Health Domain (SDMX-HD) proposed by the World Health Organization and Open Data Protocol (OData) proposed by Microsoft Corp. SDMX-HD promotes harmonization through controlled vocabulary and predefined data structure suitable for public health but requires important investment, while OData, a generic purpose standard, proposes a simple way to expose data with minimal documentation and end-user integration tools. The two solutions were implemented and are publicly available at http://sdmx.sentiweb.fr and http://odata.sentiweb.fr. These solutions show that data sharing and interoperability are already possible in Public Health Surveillance. © 2013 IMIA and IOS Press. ER - TY - JOUR T1 - Open data in public health surveillance systems: A case study using the French Sentinelles network A1 - Turbelin, Clément A1 - Boëlle, Pierre-Yves Y1 - 2013/10// PB - Elsevier JF - International Journal of Medical Informatics VL - 82 IS - 10 SP - 1012 EP - 1021 DO - 10.1016/J.IJMEDINF.2013.06.009 UR - https://www.sciencedirect.com/science/article/pii/S1386505613001378?via%3Dihub L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Turbelin, Boëlle - 2013 - Open data in public health surveillance systems A case study using the French Sentinelles network.pdf N2 - INTRODUCTION Public Health Surveillance (PHS) produces an increasing number of health indicators. Exposing these data is at the core of interoperability; however no standard has yet been adopted for such information on the internet. METHOD Here, we compared two approaches to expose data from the French Sentinelles network, an information system focusing on communicable diseases surveillance in the general population. We implemented SDMX-HD (Statistical Data and Metadata Exchange-Health Domain), a standard supported by government agencies to exchange statistical data and OpenData (OData), a general purpose protocol proposed by Microsoft Corp. The same data were described using SDMX-HD (available at http://sdmx.sentiweb.fr) and using OData (http://odata.sentiweb.fr). DISCUSSION These two use cases proved the feasibility of opening public health data on the internet, and highlighted difficulties: SDMX, a full-featured solution, encouraged harmonization and reusability, sustainability, but required complex developments and tools; OData was much simpler to implement but required a “from scratch” description and did not encourage reusability. From an end-user perspective, integration in every-day tools is not achieved yet. These two approaches are a first step to interoperability in PHS. ER - TY - JOUR T1 - An ontologically founded architecture for information systems in clinical and epidemiological research A1 - Uciteli, A A1 - Groß, S A1 - Kireyev, S A1 - Herre, H Y1 - 2011/// KW - Information Systems JF - Journal of Biomedical Semantics VL - 2 IS - 4 N1 - Cited By :5 Export Date: 10 September 2018 References: Pocock, S.J., Clinical Trials: A Practical Approach (1983), 1. , Wiley; Friedman, L.M., Furberg, C.D., DeMets, D.L., Fundamentals of Clinical Trials (2010), 4. , Springer; Fletcher, R.H., Fletcher, S.W., Clinical research in general medical journals: a 30-year perspective (1979) N. Engl. J. Med, 301, pp. 180-183; http://www.cdisc.org/standards; http://www.cdisc.org/stuff/contentmgr/files/0/be650811feb46f381f0af41ca40ade2e/misc//cdisc_2009_glossary.pdf; http://www.iso.org/iso/home.html; Information technology - Metadataregistries (MDR) - Part 1: Framework (2004), http://standards.iso.org/ittf/PubliclyAvailableStandards/c035343_ISO_IEC_11179-1_2004(E).zip; Information technology - Metadata registries (MDR) - Part 3: Registry metamodel and basic attributes (2010), http://jtc1sc32.org/doc/N1951-2000/32N1983Ta-Text-for-ballot-FCD_11179-3.pdf; Herre, H., Heller, B., Semantic foundations of medical information systems based on top-level ontologies (2006) Knowledge-Based Systems, 19, pp. 107-115; Herre, H., Heller, B., Ontology of Time and Situoids in Medical Conceptual Modeling (2005) 10th Conference on Artificial Intelligence in Medicine (AIME 05), 3581, pp. 266-275. , Aberdeen, Scotland. Lecture Notes in Computer Science. Edited by: Miksch S, Hunter J, Keravnou E. Berlin: Springer; Heller, B., Herre, H., Lippoldt, K., Domain-Specific Concepts and Ontological Reduction within a Data Dictionary Framework (2004) Data Integration in the Life Sciences (DILS 2004), Leipzig. Lecture Notes in Bioinformatics., pp. 47-62. , Edited by: Rahm E. 2004, Heidelberg: Springer; Heller, B., Herre, H., Lippoldt, K., Loeffler, M., Standardized Terminology for Clinical Trial Protocols Based on Ontological Top-Level Categories (2004) Computer-based Support for Clinical Guidelines and Protocols. Proceedings of the Symposium on Computerized Guidelines and Protocols. Studies in Health Technology and Informatics., 101, pp. 46-60. , Edited by: Kaiser K, Miksch S, Tu S. IOS Press; Heller, B., Herre, H., Lippoldt, K., The Theory of Top-Level Ontological Mappings and its Application to Clinical Trial Protocols (2004) Engineering Knowledge in the Age of the Semantic Web: Proceedings of the 14th International Conference (EKAW 2004), 3257, pp. 1-14. , Whittlebury Hall, UK, Oct 2004. Lecture Notes in Computer Science. Edited by: Motta E, Shadbolt N, Stutt A, Gibbins N. 2004, Berlin: Springer; Herre, H., General Formal Ontology (GFO): A Foundational Ontology for Conceptual Modelling (2010) Theory and Applications of Ontology., p. 2. , Edited by: Poli R, Obrst L. Berlin: Springer; Herre, H., Heller, B., Burek, P., Hoehndorf, R., Loebe, F., Michalek, H., General Formal Ontology (GFO): A Foundational Ontology Integrating Objects and Processes. Part I: Basic Principles (2006), (Version 1.0). Research Group Ontologies in Medicine (Onto-Med), University of Leipzig; Gracia, J., Individuality: an essay on the foundations of metaphysics (1988), Albany: State university of New York press; Gracia, J., Metaphysics and its task: the search for the categorial foundation of knowledge (1999), Albany N.Y.: State University of New York Press; Suárez, F., Über die Individualität und das Individuationsprinzip (1976), Hamburg: Meiner; Brentano, F., Philosophische Untersuchungen zu Raum, Zeit und Kontinuum (1976), Hamburg: Meiner; Barwise, J., Perry, J., Situations and attitudes (1983), Cambridge Mass.: MIT Press; Wittgenstein, L., Tractatus logico-philosophicus (1922), London: Routledge; Loebe, F., Abstract vs. social roles - Towards a general theoretical account of roles (2007) Applied Ontology, 2, pp. 127-158; Hoehndorf, R., Oellrich, A., Rebholz-Schuhmann, D., Interoperability between phenotype and anatomy ontologies (2010) Bioinformatics, 26, pp. 3112-3118; http://www.loa-cnr.it/DOLCE.html; http://www.ifomis.org/bfo; Hoehndorf, R., Loebe, F., Poli, R., Herre, H., Kelso, J., GFO-Bio: A biological core ontology (2008) Applied Ontology, 3, pp. 219-227; Neumuth, D., Loebe, F., Herre, H., Neumuth, T., Modeling surgical processes: A four-level translational approach (2011) Artif Intell Med.; Chang, C.C., Keisler, H.J., Model theory (1990), 3. , Amsterdam: North-Holland; Shoenfield, J.R., Mathematical Logic (2000), 2. , Peters, Wellesley; http://www.uml.org/; http://www.w3.org/TR/owl2-overview/; Information technology -- Common Logic (CL): a framework for a family of logic-based languages http://www.iso.org/iso/catalogue_detail.htm?csnumber=39175; Fraenkel, A.A., Bar-Hillel, Y., Levy, A., Foundations of Set Theory (1973), p. 2. , Amsterdam: North-Holland Publishing Co; http://www.zks.uni-leipzig.de/; http://obofoundry.org/wiki/index.php/PATO:Main_Page; Robinson, P.N., Köhler, S., Bauer, S., Seelow, D., Horn, D., Mundlos, S., The Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease (2008) Am. J. Hum. Genet, 83, pp. 610-615; http://www.uni-leipzig-life.de/; http://www.hl7.org/v3ballot/html/welcome/environment/index.html; http://www.openehr.org/home.html; http://www.cdisc.org/odm; Freimer, N., Sabatti, C., The Human Phenome Project (2003) Nature Genetics, 34, pp. 15-21; Mahner, M., Kary, M., What Exactly Are Genomes, Genotypes and Phenotypes? And What About Phenomes? (1997) Journal of Theoretical Biology, 186, pp. 55-63; Guizzardi, G., Herre, H., Wagner, G., Towards Ontological Foundations for UML Conceptual Models (2002) 1st International Conference on Ontologies, Databases and Applications of Semantics (ODBASE 2002), 2519, pp. 1100-1117. , Irvine, California, USA. Lectures Notes in Computer Science. Edited by: Meersman R, Tari Z. 2002, Springer; http://www.bmbf.de/UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921718152&doi=10.1186%2f2041-1480-2-S4-S1&partnerID=40&md5=93bad36d8d6a5cdcbcb8543167e30f96 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This paper presents an ontologically founded basic architecture for information systems, which are intended to capture, represent, and maintain metadata for various domains of clinical and epidemiological research. Clinical trials exhibit an important basis for clinical research, and the accurate specification of metadata and their documentation and application in clinical and epidemiological study projects represents a significant expense in the project preparation and has a relevant impact on the value and quality of these studies. An ontological foundation of an information system provides a semantic framework for the precise specification of those entities which are presented in this system. This semantic framework should be grounded, according to our approach, on a suitable top-level ontology. Such an ontological foundation leads to a deeper understanding of the entities of the domain under consideration, and provides a common unifying semantic basis, which supports the integration of data and the interoperability between different information systems. The intended information systems will be applied to the field of clinical and epidemiological research and will provide, depending on the application context, a variety of functionalities. In the present paper, we focus on a basic architecture which might be common to all such information systems. The research, set forth in this paper, is included in a broader framework of clinical research and continues the work of the IMISE on these topics. © 2011 Uciteli et al; licensee BioMed Central Ltd. ER - TY - JOUR T1 - Public Health Practice within a Health Information Exchange: Information Needs and Barriers to Disease Surveillance A1 - University of Illinois at Chicago. School of Public Health., Blaine A1 - Revere, Debra A1 - Hills, Rebecca A A1 - Baseman, Janet G A1 - Lober, William B Y1 - 2012/// KW - Public Health Practice JF - Online Journal of Public Health Informatics VL - 4 IS - 3 UR - http://uncommonculture.org/ojs/index.php/ojphi/article/view/4277/4779 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Introduction: Public health professionals engage in frequent exchange of health information while pursuing the objectives of protecting and improving population health. Yet, there has been little study of the information work of public health workers with regard to information exchange. Our objective was to gain a better understanding of information work at a local health jurisdiction before and during the early stages of participation in a regional Health Information Exchange.\r\n\r\nMethods: We investigated the information work of public health workers engaged in disease surveillance activities at a medium-sized local health jurisdiction by conducting semi-structured interviews and thematically analyzing interview transcripts.\r\n\r\nResults: Analysis of the information work of public health workers revealed barriers in the following areas: information system usability; data timeliness, accuracy and completeness; and social interaction with clients. We illustrate these barriers by focusing on the work of epidemiologists.\r\n\r\nConclusion: Characterizing information work and barriers to information exchange for public health workers should be part of early system design efforts. A comprehensive understanding of the information practice of public health workers will inform the design of systems that better support public health work. ER - TY - CONF T1 - A Pub/Sub based architecture to support public healthcare data exchange A1 - Wadhwa, R A1 - Mehra, A A1 - Singh, P A1 - Singh, M Y1 - 2015/// KW - Architecture KW - Electronic data interchange KW - Field workers KW - Health care KW - Health information exchanges KW - Network architecture KW - Policy makers KW - Privacy and security KW - Pub/sub KW - Public health KW - Public healthcares KW - Publish/subscribe KW - Web services UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84930448276&doi=10.1109%2FCOMSNETS.2015.7098706&partnerID=40&md5=8e9f18e061f7ec51e34466c0f67c8ee6 N1 - Cited By :6 Export Date: 10 September 2018 References: AMQP Features, , http://www.amqp.org/productifeatures, Accessed September-2014; ASHA Status of Selection and Training, , http://nrhm.gov.in/communitisation/ashalasha-data.html, Accessed September-2014; Columbia International EHealth Laboratory, , http://www.mvgnet.org/ciell?q=contenticolumbia-international-ehealth-laboratory-ciel, Accessed September-2014; Introduction to HL7 Standards, , http://www.hl7.orglimplementistandards/, Accessed September-2014; SDMX-HD (Health Domain), , http://www.sdmx-hd.org/, Accessed September-2014; What is Interoperability?, , http://www.himss.orgllibrary/interoperability-standards/what-is, Accessed September-2014; Bacon, J., Eyers, D.M., Singh, J., Pietzuch, P.R., Access control in publish/subscribe systems (2008) Proceedings of the Second International Conference on Distributed Event-based Systems, pp. 23-34. , ACM; David, J.B., Interoperability: The key to the future health care system (2005) Health Affairs-millwood VA Then Bethesda Ma, 24, p. W5; Th Eugster, P., Felber, P.A., Guerraoui, R., Kermarrec, A., The many faces of publish/subscribe (2003) ACM Computing Surveys (CSUR), 35 (2), pp. 114-131; Ferraiolo, D.F., Richard Kuhn, D., (2009) Role-based Access Controls, , arXiv preprint arXiv: 0903.2171; (2004) The Value of Healthcare Information Exchange and Interoperability. Healthcare Information and Management Systems Society, , C! TL (Center for Information Technology Leadership, Partners Healthcare System) Healthcare Information, and Management Systems Society; Geraci, A., Katki, F., McMonegal, L., Meyer, B., Lane, J., Wilson, P., Radatz, J., Springsteel, F., (1991) IEEE Standard Computer Dictionary: Compilation of IEEE Standard Computer Glossaries, , IEEE Press; Hunkeler, U., Linh Truong, H., Stanford-Clark, A., Mqttsa publish/subscribe protocol for wireless sensor networks (2008) Communication Systems Software and Middleware and Workshops 2008. COMSWARE 2008. 3rd International Conference on, pp. 791-798. , IEEE; Ko, L., Lin, J., Chen, C., Chang, J., Lai, F., Hsu, K., Yang, T., Chen, J., H17 middleware framework for healthcare information system (2006) E-Health Networking, Applications and Services 2006. HEALTHCOM 2006. 8th International Conference on, pp. 152-156. , IEEE; Massimo Ferrara, F., The standard healthcare information systems architectureand the dhe middleware (1998) International Journal of Medical Informatics, 52 (1), pp. 39-51; Ochian, A., Suciu, G., Fratu, O., Voicu, C., Suciu, V., An overview of cloud middleware services for interconnection of heaIthcare platforms (2014) Communications (COMM) 2014 10th International Conference on, pp. 1-4. , IEEE; Sandhu, R.S., Coyne, E.J., Feinstein, H.L., Youman, C.E., Role-based access control models (1996) Computer, 29 (2), pp. 38-47; Singh, J., Vargas, L., Bacon, J., Moody, K., Policybased information sharing in publish/subscribe middleware (2008) Policies for Distributed Systems and Networks 2008. POLICY 2008. IEEE Workshop on, pp. 137-144. , IEEE; Souto, E., Guimaraes, G., Vasconcelos, G., Vieira, M., Rosa, N., Ferraz, C., Kelner, J., Mires: A publish/ subscribe middleware for sensor networks (2006) Personal and Ubiquitous Computing, 10 (1), pp. 37-44; Spahni, S., Scherrer, J., Sauquet, D., Sottile, P., Towards specialised middleware for healthcare information systems (1999) International Journal of Medical Informatics, 53 (2), pp. 193-201; Hasmat Ullah, M., Park, S., No, J., Hun Kim, G., A collaboration mechanism between wireless sensor network and a cloud through a pub/sub-based middleware service (2013) INTERNET 2013, the Fifth International Conference on Evolving Internet, pp. 38-42 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Data exchange plays an important role in public healthcare. Having timely access to right data can allow detection of the spread of a disease, assess effectiveness of government schemes, etc. In order to improve policies and provide awareness, various government healthcare schemes are run which generate a huge amount of data. This data is collected by number of field workers and is then transferred to central repositories for further analysis. While the data eventually reaches researchers and scientist for analysis, the delay (usually in months) hampers timely actions that can be taken. In this paper, we propose a Publish/Subscribe based Architecture moderated through a web service that can enable an early exchange of healthcare data among different interested parties e.g. doctors, researchers, and policy makers. Our architecture handles the privacy and security requirements, and also provides interoperability support for data exchange. We have also highlighted how the architecture deals with the key challenges involved in public health information exchange. © 2015 IEEE. ER - TY - JOUR T1 - How Can We Not Waste Legacy Genomic Research Data? A1 - Wallace, S E A1 - Kirby, E A1 - Knoppers, B M Y1 - 2020/// JF - Frontiers in Genetics VL - 11 DO - 10.3389/fgene.2020.00446 N2 - ©Copyright ©2020 Wallace, Kirby and Knoppers. Enabling genomic and biomedical data to be shared for secondary research purposes is not always straightforward for existing “legacy” data sets. Researchers may not know whether their data meet ethical and regulatory requirements for sharing. As a result, these data, collected using public funds and the good will and efforts of the donors and investigators, may not be used beyond their original purpose. Single-use plastics are now being banned in many countries; single-use research should be avoided if possible. This paper describes a filter developed through the driver projects of the Global Alliance for Genomics and Health that can be used by researchers to help them determine the extent of sharing possible for their legacy data and actions to be taken to enable further sharing. ER - TY - JOUR T1 - The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions A1 - Vandervalk, Ben A1 - McCarthy, E Luke A1 - Cruz-Toledo, José A1 - Klein, Artjom A1 - Baker, Christopher J O A1 - Dumontier, Michel A1 - Wilkinson, Mark D Y1 - 2013/// KW - Drug Interactions KW - Quality of Life KW - SADI KW - SHARE KW - Web-based interaction KW - Web-based services KW - drug interactions KW - semantic Web KW - telemedicine JF - JMIR Research Protocols VL - 2 IS - 1 SP - e14 EP - e14 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - BACKGROUND The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. OBJECTIVE The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. METHODS We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. RESULTS A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. CONCLUSIONS The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this prototype was limited to a single knowledge domain (drug/drug interactions), the proposed architecture is generalizable, and could act as the foundation for much richer personalized-health-Web clients, while importantly providing a novel and personalizable mechanism for clinical experts to inject their expertise into the browsing experience of their patients in the form of customized semantic queries and ontologies. ER - TY - JOUR T1 - Creating personalised clinical pathways by semantic interoperability with electronic health records A1 - Wang, H.-Q. A1 - Li, J.-S. A1 - Zhang, Y.-F. A1 - Suzuki, M A1 - Araki, K Y1 - 2013/// KW - Appendicitis KW - Artificial Intelligence KW - Cerebral Palsy KW - Clinical pathway KW - Clinical pathways KW - Critical Pathways KW - Data Mining KW - Electronic Health Records KW - Electronic health record KW - Electronic health record (EHRs) KW - Health care KW - Humans KW - Individualized Medicine KW - Interoperability KW - Knowledge Bases KW - Knowledge base KW - Knowledge based systems KW - Programming Languages KW - Quality Improvement KW - Query languages KW - Records management KW - Research and development KW - Resource description framework KW - Semantic Web rule language (SWRL) KW - Semantic interoperability KW - Semantics KW - Systems Integration KW - Terminology as Topic KW - Therapy, Computer-Assisted KW - User-Computer Interface KW - acute appendicitis KW - appendectomy KW - article KW - clinical decision making KW - clinical pathway KW - electronic medical record KW - health care need KW - health care quality KW - human KW - knowledge base KW - knowledge management KW - markup language KW - medical history KW - medical information system KW - patient care KW - patient information KW - patient monitoring KW - personalized medicine KW - priority journal JF - Artificial Intelligence in Medicine VL - 58 IS - 2 SP - 81 EP - 89 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878109502&doi=10.1016%2Fj.artmed.2013.02.005&partnerID=40&md5=3224883054ad43c262e8792db5f50568 N1 - Cited By :22 Export Date: 10 September 2018 References: Chu, S., Computerised clinical pathway as process quality improvement tool (2001) Medinfo 2001: proceedings of the 10th world congress on medical informatics, pp. 1135-1139. , IOS Press, London, V.L. Patel, R. Rogers, R. Haux (Eds.); De Bleser, L., Depreitere, R., Waele, K.D., Vanhaecht, K., Vlayen, J., Sermeus, W., Defining pathways (2006) Journal of Nursing Management, 14 (7), pp. 553-563; Rotter, T., Kinsman, L., James, E., Machotta, A., Willis, J., Snow, P., The effects of clinical pathways on professional practice, patient outcomes, length of stay, and hospital costs: cochrane systematic review and meta-analysis (2012) Evaluation & the Health Professions, 35 (1), pp. 3-27; Alexandrou, D., Xenikoudakis, F., Mentzas, G., SEMPATH: Semantic adaptive and personalized clinical pathways (2009) eTELEMED 2009: proceedings of international conference on eHealth, telemedicine, and social medicine, pp. 36-41. , IEEE Computer Society Conference Publishing Services, Piscataway, E.C. Conley, C. Doarn, A. Hajjam-EI-Hassani (Eds.); Vanhaecht, K., Bollmann, M., Bower, K., Gallagher, C., Gardini, A., Guezo, J., Prevalence and use of clinical pathways in 23 countries: an international survey by the European Pathway Association (2006) Journal of Care Pathways, 10 (1), pp. 28-34; Li, W., Liu, K., Li, S., Yang, H., Normative modeling for personalized clinical pathway using organizational semiotics methods (2008) ISCSCT 2008: proceedings of the 1st international symposium on computer science and computational technology, pp. 3-7. , IEEE Computer Society, Piscataway, F. Yu, W. Chen, Z. Chen, J. Yuan (Eds.); Blaser, R., Schnabel, M., Biber, C., Bäumlein, M., Heger, O., Beyer, M., Improving pathway compliance and clinician performance by using information technology (2007) International Journal of Medical Informatics, 76 (2-3), pp. 151-156; Chu, S., Cesnik, B., Improving clinical pathway design: lessons learned from a computerised prototype (1998) International Journal of Medical Informatics, 51 (1), pp. 1-11; Fagot, C., Pierre, D., Py, S., Federate best practice around the patient clinical path (2007) ICDIM 2007: proceedings of the 2nd international conference on digital information management, pp. 583-590. , IEEE Conference Publications, Piscataway; Abidi, S., A conceptual framework for ontology based automating and merging of clinical pathways of comorbidities (2009) Knowledge management for health care procedures, pp. 55-66. , Springer, Berlin, D. Riaño (Ed.); Lenz, R., Blaser, R., Beyer, M., Heger, O., Biber, C., Bäumlein, M., IT support for clinical pathways-lessons learned (2007) International Journal of Medical Informatics, 76 (SUPPL. 3), pp. S397-S402; Gooch, P., Roudsari, A., Computerization of workflows, guidelines, and care pathways: a review of implementation challenges for process-oriented health information systems (2011) Journal of the American Medical Informatics Association, 18 (6), pp. 738-748; Blumenthal, D., Tavenner, M., The " meaningful use" regulation for electronic health records (2010) New England Journal of Medicine, 363 (6), pp. 501-504; Lurio, J., Morrison, F.P., Pichardo, M., Berg, R., Buck, M.D., Wu, W., Using electronic health record alerts to provide public health situational awareness to clinicians (2010) Journal of the American Medical Informatics Association, 17 (2), pp. 217-219; Zillner, S., Hauer, T., Rogulin, D., Tsymbal, A., Huber, M., Solomanides, T., Semantic visualization of patient information (2008) CBMS 2008: proceedings of the 21st IEEE international symposium on computer-based medical systems, pp. 296-301. , IEEE Computer Society, Piscataway, S. Puuronen, M. Pechenizkiy, A. Tsymbal, D.-J. Lee (Eds.); Tao, C., Pathak, J., Welch, S.R., Bouamrane, M.-M., Huff, S.M., Chute, C.G., Toward semantic web based knowledge representation and extraction from electronic health records (2011) MIXHS'11: proceedings of the 1st international workshop on managing interoperability and complexity in health systems, pp. 75-78. , ACM, New York, M.-M. Bouamrane, T. Cui (Eds.); Argüello Casteleiro, M., Des, J., Prieto, M.J.F., Perez, R., Paniagua, H., Executing medical guidelines on the web: towards next generation healthcare (2009) Knowledge-Based Systems, 22 (7), pp. 545-551; Fox, J., Alabassi, A., Patkar, V., Rose, T., Black, E., An ontological approach to modelling tasks and goals (2006) Computers in Biology and Medicine, 36 (7-8), pp. 837-856; Dang, J., Hedayati, A., Hampel, K., Toklu, C., An ontological knowledge framework for adaptive medical workflow (2008) Journal of Biomedical Informatics, 41 (5), pp. 829-836; Ye, Y., Jiang, Z., Diao, X., Yang, D., Du, G., An ontology-based hierarchical semantic modeling approach to clinical pathway workflows (2009) Computers in Biology and Medicine, 39 (8), pp. 722-732; Hu, Z., Li, J., Zhou, T., Yu, H., Suzuki, M., Araki, K., Ontology-based clinical pathways with semantic rules (2012) Journal of Medical Systems, 36 (4), pp. 2203-2212; http://www.ch-cp.org.cn/, [accessed 13.12.12]; Warner, B.W., Kulick, R.M., Stoops, M.M., Mehta, S., Stephan, M., Kotagal, U.R., An evidenced-based clinical pathway for acute appendicitis decreases hospital duration and cost (1998) Journal of Pediatric Surgery, 33 (9), pp. 1371-1375; Takegami, K., Kawaguchi, Y., Nakayama, H., Kubota, Y., Nagawa, H., Impact of a clinical pathway and standardization of treatment for acute appendicitis (2003) Surgery Today, 33 (5), pp. 336-341; Chevalley, T., Chevalley, T., Hoffmeyer, P., Bonjour, J.P., Rizzoli, R., An osteoporosis clinical pathway for the medical management of patients with low-trauma fracture (2002) Osteoporosis International, 13 (6), pp. 450-455; Stanton-Hicks, M.D., Burton, A.W., Bruehl, S.P., Carr, D.B., Harden, R.N., Hassenbusch, S.J., An updated interdisciplinary clinical pathway for CRPS: report of an expert panel (2002) Pain Practice, 2 (1), pp. 1-16; Chapman, W.W., Christensen, L.M., Wagner, M.M., Haug, P.J., Ivanov, O., Dowling, J.N., Classifying free-text triage chief complaints into syndromic categories with natural language processing (2005) Artificial Intelligence in Medicine, 33 (1), pp. 31-40; Casteleiro, M.A., Diz, J.J.D., Clinical practice guidelines: a case study of combining OWL-s, OWL, and SWRL (2008) Knowledge-Based Systems 2007;, 21, pp. 247-255; http://www.w3.org/TR/2004/REC-owl-features-20040210/%23s1.3, [accessed 13.12.12]; http://www.daml.org/rules/proposal/abstract.html, [accessed 13.12.12]; Hurley, K.F., Abidi, S.S.R., Ontology engineering to model clinical pathways: towards the computerization and execution of clinical pathways (2007) CBMS 2007: proceedings of the 20th IEEE international symposium on computer-based medical systems, pp. 536-541. , IEEE Computer Society, Piscataway, P. Kokol, V. Podgorelec, D. Micetic-Turk, M. Zorman, M. Verlic (Eds.); Sucurovic, S., An approach to access control in electronic health record (2010) Journal of Medical Systems, 34 (4), pp. 659-666; Patel, C., Gomadam, K., Khan, S., Garg, V., Trial, X., Using semantic technologies to match patients to relevant clinical trials based on their Personal Health Records (2010) Web Semantics: Science, Services and Agents on the World Wide Web, 8 (4), pp. 342-347; Serbanati, L.D., Ricci, F.L., Mercurio, G., Vasilateanu, A., Steps towards a digital health ecosystem (2011) Journal of Biomedical Informatics, 44 (4), pp. 621-636; Memisoglu, K., Karip, B., Mestan, M., Onur, E., The value of preoperative diagnostic tests in acute appendicitis, retrospective analysis of 196 patients (2010) World Journal of Emergency Surgery, 5 (1), p. 5; http://swrl.stanford.edu/ontologies/built-ins/3.3/temporal.owl%23, [accessed 13.12.12]; Tao, C., Wei, W.Q., Solbrig, H.R., Savova, G., Chute, C.G., CNTRO: a semantic web ontology for temporal relation inferencing in clinical narratives (2010) AMIA Annual Symposium Proceedings Archive, 2010, pp. 787-791; Yu, H., Li, J., Zhang, X., Tian, Y., Suzuki, M., Araki, K., Performance assessment of EMR systems based on post-relational database (2012) Journal of Medical Systems, 36 (4), pp. 2421-2430; Li, J., Zhang, X., Chu, J., Suzuki, M., Araki, K., Design and development of EMR supporting medical process management (2012) Journal of Medical Systems, 36 (3), pp. 1193-1203; Wakamiya, S., Yamauchi, K., What are the standard functions of electronic clinical pathways? (2009) International Journal of Medical Informatics, 78 (8), pp. 543-550 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objective: There is a growing realisation that clinical pathways (CPs) are vital for improving the treatment quality of healthcare organisations. However, treatment personalisation is one of the main challenges when implementing CPs, and the inadequate dynamic adaptability restricts the practicality of CPs. The purpose of this study is to improve the practicality of CPs using semantic interoperability between knowledge-based CPs and semantic electronic health records (EHRs). Methods: Simple protocol and resource description framework query language is used to gather patient information from semantic EHRs. The gathered patient information is entered into the CP ontology represented by web ontology language. Then, after reasoning over rules described by semantic web rule language in the Jena semantic framework, we adjust the standardised CPs to meet different patients' practical needs. Results: A CP for acute appendicitis is used as an example to illustrate how to achieve CP customisation based on the semantic interoperability between knowledge-based CPs and semantic EHRs. A personalised care plan is generated by comprehensively analysing the patient's personal allergy history and past medical history, which are stored in semantic EHRs. Additionally, by monitoring the patient's clinical information, an exception is recorded and handled during CP execution. According to execution results of the actual example, the solutions we present are shown to be technically feasible. Conclusion: This study contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system. © 2013 Elsevier B.V. ER - TY - JOUR T1 - Construction of a rational drug use monitoring ecosystem based on regional medical big data A1 - Wang, H A1 - Yang, Z W A1 - Mao, X F A1 - Zhang, D D A1 - Liu, Z Y Y1 - 2018/// JF - Pharmaceutical Care and Research VL - 18 IS - 6 DO - 10.5428/pcar20180606 N2 - ©2018 Publishing House of Pharmaceutical Care and Research. All rights reserved. Objectives To develop a professional tool both for mining and analysis of regional integrated big data and administration of rational drug use in hospital, and to construct the rational drug use monitoring ecosystem in the background of integration and application of medical big data. Methods: The collaboration platform for basic medical information standardization based on the cloud was established. The database with the memory and the data model for flexible and quick data mining and analysis were built. The user-defined, visualized and all-wave administration of drug use was carried out. Results: The regional national standardized medical database was also established. The standardized basic information for medical big data mining and analysis was realized, meanwhile, the online administration of the supply list of hospital essential drugs was achieved, and it was easy for users at different regulatory levels to operate at a rapid rate. Conclusion: The PLA data management center of clinical application of antibacterials offered all-around supports to regional data administration centers and hospitals for the administration of drug use,achieved the goals of "unified standards,unified platform,resource sharing and interoperability" in information construction of healthcare industry,thus achieving the construction of the drug-use administration ecosystem. ER - TY - JOUR T1 - Experience and challenge on interoperability of big data in health care A1 - Wang, S F A1 - Ning, Y A1 - Li, L M Y1 - 2020/// JF - Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi VL - 41 IS - 3 SP - 303 EP - 309 DO - 10.3760/cma.j.issn.0254-6450.2020.03.005 N2 - 互联互通是目前全球各国健康医疗大数据使用面临的最大壁垒。互联互通涉及业务、安全、伦理、语义和技术5个维度，本文在比较政府主导、企业主导和研究机构主导3种常见互联互通模式的基础上，结合中国健康医疗大数据的发展现状，提出高校牵头、企业助力和政府支持的工作模式。同时，归纳出目前我国健康医疗大数据互联互通面临的3大挑战：行业标准与规范、数据安全与伦理、激励机制与考核。唯有采用切实可行的模式，攻克相关关键技术，真正将数据打通共享，才能最大限度的整合多来源数据，挖掘多应用场景，培育多业态模式，全面提升人口健康科学决策和服务管理水平。. | Problems in interoperability is the biggest barrier limiting the use of big data in health care worldwide. Interoperability contains five dimensions: business, security, ethics, semantics and technology. Based on the comparison of the three common interoperability models led by government, enterprise or research institution, and the current status of big data development in China, this paper proposes a new operation model which can be led by university, aided by enterprise and supported by government, and summarizes the three major challenges in the development of big data interoperability in China: professional standard and specification, data security and ethics, incentive mechanism and assessment. Only when a feasible model is adopted, technical difficulties are overcome and data are truly shared, we can achieve maximized integration of multi-source data, expanding its application fields and establish a multi-business mode to comprehensively improve the population based health decision-making and management. ER - TY - CONF T1 - Interoperability enhancement in health care at remote locations using thread protocol in UAVs A1 - Vangimalla, S R A1 - El-Sharkawy, M Y1 - 2018/// JF - Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society SP - 2821 EP - 2826 SN - 9781509066841 DO - 10.1109/IECON.2018.8592759 N2 - ©2018 IEEE. In developing countries, population with low socioeconomic status are at risk of epidemics and their health care has always been a matter of concern. Though steps have been taken, they do not show significant output due to lack of data and liability of doctors to visit such rural areas. This paper aims at improving the current health care by enhancing interoperability in rural areas. This can be achieved by implementing a secured network like Thread in Unmanned Aerial Vehicles (UAV). They can be deployed to any remote location from the base station autonomously by planning a mission to collect sensitive patient information. This collected data can be analyzed and such implementation over a period helps in predictive analysis. Thus improving the future health of people. ER - TY - JOUR T1 - Where is the EHR in oncology? A1 - Warner, J A1 - Hochberg, E Y1 - 2012/// JF - JNCCN Journal of the National Comprehensive Cancer Network VL - 10 IS - 5 SP - 584 EP - 588 UR - http://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&D=emed14&AN=364942646 http://digitaal.uba.uva.nl:9003/uva-linker?sid=OVID:embase&id=pmid:22570289&id=doi:&issn=1540-1405&isbn=&volume=10&issue=5&spage=584&pages=584-588&date=2012&title N1 - Cited By :6 Export Date: 10 September 2018 References: Roth, C.P., Lim, Y.W., Pevnick, J.M., The challenge of measuring quality of care from the electronic health record (2009) Am J Med Qual, 24, pp. 385-394; Rosenbloom, S.T., Denny, J.C., Xu, H., Data from clinical notes: A perspective on the tension between structure and flexible documentation (2011) J Am Med Inform Assoc, 18, pp. 181-186; Demner-Fushman, D., Chapman, W.W., McDonald, C.J., What can natural language processing do for clinical decision support? (2009) J Biomed Inform, 42, pp. 760-772; Harpaz, R., Haerian, K., Chase, H.S., Friedman, C., Mining electronic health records for adverse drug effects using regression based methods (2010) Proceedings of the 1st ACM International Health Informatics Symposium (IHI '10), pp. 100-107. , Veinot T, ed. New York, NY: ACM; Murff, H.J., FitzHenry, F., Matheny, M.E., Automated identification of postoperative complications within an electronic medical record using natural language processing (2011) JAMA, 306, pp. 848-855; Warner, J.L., Anick, P., Hong, P., Xue, N., Natural language processing and the oncologic history: Is there a match? (2011) J Oncol Pract, 4, pp. e15-e19; Weber, G.M., Murphy, S.N., McMurry, A.J., The Shared Health Research Information Network (SHRINE): A prototype federated query tool for clinical data repositories (2009) J Am Med Inform Assoc, 16, pp. 624-630; Shulman, L.N., Miller, R.S., Ambinder, E.P., Principles of safe practice using an oncology EHR system for chemotherapy ordering, preparation, and administration, Part 1 of 2 (2008) J Oncol Pract, 4, pp. 203-206; Ensuring continuity of care through electronic health records: Recommendations from the ASCO Electronic Health Record Roundtable (2007) J Oncol Pract, 3, pp. 137-142; Blumenthal, D., Tavenner, M., The "meaningful use" regulation for electronic health records (2010) N Engl J Med, 363, pp. 501-504; Baron, R.J., It's time to meaningfully use electronic health records: Our patients are demanding it (2011) Ann Intern Med, 154, pp. 697-698; Abernethy, A.P., Etheredge, L.M., Ganz, P.A., Rapid-learning system for cancer care (2010) J Clin Oncol, 28, pp. 4268-4274 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: EHR,Health not surveillance N2 - Electronic health records (EHRs) have the potential to increase the quality and decrease the cost of cancer care. These twin goals can only be met by a fully functional oncology EHR, which includes at a minimum: searchable data repositories, clinical decision support (CDS), the ability to electronically order chemotherapeutic medications, and the ability to interface with patients via a patient portal. Such fully functional EHRs not only offer patients the best potential for high-quality care, they enable retrospective analysis to answer a wide variety of comparative effectiveness and quality improvement questions. The significant barriers of cost, time pressures, aversion to CDS, and interoperability will need to be overcome if EHRs are to be meaningfully used by the majority of oncologists. © JNCCN-Journal of the National Comprehensive Cancer Network. ER - TY - CONF T1 - Information Reference Architecture for the Portuguese Health Sector A1 - Vasconcelos, A.F.F.C.E. A1 - Brás, T J G Y1 - 2015/// KW - Architecture KW - Bottom up approach KW - Cost reduction KW - Health KW - Information Architecture KW - Information architectures KW - Information management KW - Information retrieval KW - Information science KW - Informational Entities KW - Interoperability KW - Models integration KW - Public administration KW - Reference Architecture KW - Reference architecture KW - Schema Integration KW - Schema integration KW - Societies and institutions VL - 2 SP - 72 EP - 79 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960130402&doi=10.1109%2FCBI.2015.53&partnerID=40&md5=52c1c4de16723a5ed4270c7c9bb3421f N1 - Cited By :1 Export Date: 10 September 2018 References: Watson, R.W., (2000) An Enterprise Information Architecture: A Case Study for Decentralized Organizations, , IEEE Computer Society; Batini, C., Ceri, S., Navathe, E., Shamkant, B., (1992) Conceptual Database Design: An Entity-Relationship Approach, , The Benjamim/Cummings Publishing Company, Inc; Resolução Do Conselho de Ministros No 12/2012 de 7 de Fevereiro, , Presidência do Conselho de Ministros: Diário da República, 1. série - No. 27. Portugal; Henver, A.R., Design science in information systems research (2004) MIS Quarterly, 28 (1), pp. 75-105; Peffers, K., A design science research methodology for information systems research (2007) Journal of Management Information Systems, 24 (3), pp. 45-77; (2015) Arquitetura Informacional, , https://m6.AMA.pt/docs/ArquiteturaInformacional.pdf, [Online] [Accessed: 15/02/]; Decreto-Lei N. 43/2010 de 23 de Fevereiro, , Presidência do Conselho de Ministros: Diário da República, 1 série - No. 39. Portugal; Decreto-Lei No 124/2011 de 29 de Dezembro, , Ministério da Saúde: Diário da República, 1 série - No. 249. Portugal; (2013) Newsletter Tecnologias de Informação e Comunicação, , http://www.apdh.pt/sites/apdh.pt/files/Newsletter_Julho2013.pdf, [Online] Julho de [Accessed: 24/09/2014]; Decreto-Lei No. 19/2010 de 22 de Março, , Ministério da Saúde: Diário da República, 1 sério - No. 56. Portugal; Decreto-Lei No. 108/2011 de 22 de Março, , Ministério da Saúde: Diário da República, 1 série - No. 221. Portugal; (2011) Interoperabilidade Na Administração Pública. Procedimentos Para A Adesão À IAP - Plataforma de Interoperabilidade da Administração Pública, , Versão 3.0; Giaglis, G.M., A taxonomy of business process modelling and information systems modelling techniques (2001) International Journal of Flexible Manufacturing Systems, 13 (2), pp. 209-228; (2000) IEEE Recommended Practice for Architectural Description for Software-Intensive Systems, 1471. , IEEE standard; Lankhorst, M., (2005) Enterprise Architecture at Work, , Springer; (2010) Reference Architecture Description; Godinez, M., (2010) The Art of Enterprise Information Architecture: A Systems-Bases Approach for Unlocking Business Insight, , IBM Press; Lapkin, A., (2008) Gartner Clarifies the Definition of the Term 'Enterprise Architecture', , Gartner; Spewak, S.H.E., Hill, S.C., (1993) Enterprise Architecture Planning: Developing A Blueprint for Data, Applications and Technology, , QED Technical Publishing Group; Vasconcelos, A., (2007) Arquitecturas Dos Sistemas de Informação: Representação e Avaliação, , Instituto Superior Técnico, Universidade Técnica de Lisboa; Cisneros, L., Hunt, D.E., McCollam, D., Information architecture bring the university's information inventory under control (1997) The Information Profession and the Information Professional; Vasconcelos, A., (2001) Arquitecturas de Sistemas de Informação No Contexto Do Negócio, , Instituto Superior Técnico, Universidade Técnica de Lisboa; Bernstein, P.A., (1996) Middleware: A Model for Distributed System Services, , ACM; (2010) European Interoperability Framework (EIF) for European Public Services; Rahm, E.E., Bernstein, P., A survey of approaches to automatic schema matching (2001) The VLDB Journal, 10; Batini, C., Lenzerini, M.E., Navathe, S.B., A comparative analysis of methodologies for database schema integration (1986) ACM Computing Surveys, 18; Su, X., A Text Categorization Perspective for Ontology Mapping, , Dept. of Computer and Information Science Norwegian University of Science and Technology; Bisson, G., (1995) Why and How to Define A Similarity Measure for Object Based Representation Systems, , IMAG-LIFIA, INRIA Rhône-Alpes, Project SHERPA; Ehrig, M., Sure, Y., (2004) Ontology Mapping - An Integrated Approach, , LNCS; Rizopoulos, N., McBrien, P., (2009) Schema Merging Based on Semantic Mappings, , Springer-Verlag; Hakimpour, F., Geppert, A., (2001) Resolving Semantic Heterogeneity in Schema Integration: An Ontology Based Aproach, , ACM RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The creation of an information architecture is one of the identified ways that contribute to increase competitiveness, enabling cost reduction and increasing productivity in organizations. When it comes to broaden comprehensive sectors gathering several organizations (for example in the health sector), the creation of a reference architecture acquires a higher importance to guide and constrain the implementation of information architectures of the involved organizations, ensuring interoperability and alignment among them. When creating a reference architecture, following a bottom-up approach, it is essential to identify the informational entities amongst the different data models in order to be possible to integrate these informational entities in the reference architecture that is being developed. This paper describes a process which allows the verification of correspondence between informational entities amongst different data models. As far as the Portuguese case is concerned, there is just one reference architecture for the Public Administration. In this paper we describe its foundations in order to make a specialization in that architecture that can be used, further on, as a reference for the Portuguese health sector in order to increase interoperability. Nevertheless, the presented solution may also be applied to any data models integration following the bottom-up approach. © 2015 IEEE. ER - TY - JOUR T1 - Progress in data interoperability to support computational toxicology and chemical safety evaluation A1 - Watford, S A1 - Edwards, S A1 - Angrish, M A1 - Judson, R S A1 - Paul Friedman, K Y1 - 2019/// JF - Toxicology and Applied Pharmacology VL - 380 DO - 10.1016/j.taap.2019.114707 N2 - ©2019 Elsevier Inc. New approach methodologies (NAMs) in chemical safety evaluation are being explored to address the current public health implications of human environmental exposures to chemicals with limited or no data for assessment. For over a decade since a push toward “Toxicity Testing in the 21st Century,” the field has focused on massive data generation efforts to inform computational approaches for preliminary hazard identification, adverse outcome pathways that link molecular initiating events and key events to apical outcomes, and high-throughput approaches to risk-based ratios of bioactivity and exposure to inform relative priority and safety assessment. Projects like the interagency Tox21 program and the US EPA ToxCast program have generated dose-response information on thousands of chemicals, identified and aggregated information from legacy systems, and created tools for access and analysis. The resulting information has been used to develop computational models as viable options for regulatory applications. This progress has introduced challenges in data management that are new, but not unique, to toxicology. Some of the key questions require critical thinking and solutions to promote semantic interoperability, including: (1) identification of bioactivity information from NAMs that might be related to a biological process; (2) identification of legacy hazard information that might be related to a key event or apical outcomes of interest; and, (3) integration of these NAM and traditional data for computational modeling and prediction of complex apical outcomes such as carcinogenesis. This work reviews a number of toxicology-related efforts specifically related to bioactivity and toxicological data interoperability based on the goals established by Findable, Accessible, Interoperable, and Reusable (FAIR) Data Principles. These efforts are essential to enable better integration of NAM and traditional toxicology information to support data-driven toxicology applications. ER - TY - CONF T1 - Secure networking is the key to german public e-health solution: Migration towards an integrated e-health infrastructure A1 - Weiss, B Y1 - 2011/// KW - Costs KW - Data privacy KW - Data privacy protections KW - E-health infrastructures KW - E-health solutions KW - Economic solutions KW - Electronic healthcare KW - Health KW - Health care KW - Interoperability KW - Interoperable network KW - Life Expectancy KW - Life expectancies KW - Privacy KW - Secure networking SP - 143 EP - 150 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84883695784&doi=10.1007%2F978-3-8348-9788-6-14&partnerID=40&md5=089b2f2329f7c58de83cc220d1cd2593 N1 - Export Date: 10 September 2018 References: (2009) Gematik - Gesellschaft Fur Telematikanwendungen der Gesundheitskarte MbH: Release 4.0.0 -R2A, , www.gematik.de, Specifications, gematik; (2010) Bestandsaufnahme Abgeschlossen, , gematik.de/cms/de/header_navigation/presse/pressemitteilungen/ pressemitteilungen_l.jsp#, gematik - Gesellschaft fur Telematikanwendungen der Gesundheitskarte mbH: 20.04.2010 Press release, gematik; (2009) KBV - Kassenarztliche Bundesvereinigung: Das KV-SafeNet, , www.kbv.de/12164.html, Information, KBV; Sozialgesetzbuch (SGB) Fiinftes Buch (V) - Gesetzliche Krankenversicherung: § 291a, , www.gesetze-im-internet.de/sgb_5/-291a.html, Legislation, juris; Sozialgesetzbuch (SGB) Fiinftes Buch (V) - Gesetzliche Krankenversicherung: § 291b, , www.gesetze-im-internet.de/sgb_5/-291b.html, Legislation, juris; Sozialgesetzbuch (SGB) Fiinftes Buch (V) - Gesetzliche Krankenversicherung: § 73b, , www.gesetze-im-internet.de/sgb_5/-73b.html, Legislation, juris; (2005) The Taiwan Health Care SmartCard Project, , Smart Card Alliance Leaflet, Smart Card Alliance Secure Personal Identification Task Force, Smart Card Alliance; (2010) Webportal, Sozialversicherungs-Chipkarten Betriebs- und Errichtungsgesellschaft M.B.H. - SVC, , www.chipkarte.at/, SVC: Willkommen bei der e-card; (2010) Encyclopaedia, , de.wikipedia.org/wiki/E-card_%28Chipkarte%29, Wikipedia: e-card (Chipkarte); (2010) Healthcare in Taiwan, , en.wikipedia.org/wiki/Healthcare_in_Taiwan, Encyclopaedia, Wikipedia; (2010) Deutscher Bundestag - Drucksache 17/2170: Anderung des Fiinften Buches Sozialgesetzbuch, , dip21.bundestag.de/dip21/btd/17/021/1702170.pdf, Legislation, 50. Sitzung des Deutschen Bundestages am 18. Juni RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - All around the world headlines warn about the exploding costs of healthcare as advanced medicines and technology are boosting life expectancy. Something needs to be done to contain these costs. An efficient and economic solution demands an electronic healthcare card system based on an integrated communication network which has been designed in Germany to help reduce costs. This system has been designed to meet the requirements of the healthcare modernization legislation passed by German Parliament in 2003. Its deployment is among other reasons challenged by networks and applications already in use by e-health professionals. These parallel infrastructures have been setup over the past years and already enable e.g. physicians to exchange information online and optimise their processes by accessing a centralised infrastructure. But these systems do not provide the level of interoperability required. Thus limiting use to regional groups only. This leads in consequence to different sectoral but not interoperable networks. This paper will discuss the success factors for a secure, flexible and interoperable e-health infrastructure solution capable of integrating existing applications and services. It will outline that only an integrated e-health infrastructure can enforce data privacy protection at multiple levels as legally required. © Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH 2011. ER - TY - JOUR T1 - Semantically Interoperable XML Data. A1 - Vergara-Niedermayr, Cristobal A1 - Wang, Fusheng A1 - Pan, Tony A1 - Kurc, Tahsin A1 - Saltz, Joel Y1 - 2013/// KW - Biomedical Data Management KW - Data Integration KW - Semantic Interoperability KW - Semantics KW - XML Database PB - NIH Public Access JF - International journal of semantic computing VL - 7 IS - 3 SP - 237 EP - 255 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - XML is ubiquitously used as an information exchange platform for web-based applications in healthcare, life sciences, and many other domains. Proliferating XML data are now managed through latest native XML database technologies. XML data sources conforming to common XML schemas could be shared and integrated with syntactic interoperability. Semantic interoperability can be achieved through semantic annotations of data models using common data elements linked to concepts from ontologies. In this paper, we present a framework and software system to support the development of semantic interoperable XML based data sources that can be shared through a Grid infrastructure. We also present our work on supporting semantic validated XML data through semantic annotations for XML Schema, semantic validation and semantic authoring of XML data. We demonstrate the use of the system for a biomedical database of medical image annotations and markups. ER - TY - JOUR T1 - An integrated framework to achieve interoperability in person-centric health management A1 - Vergari, F A1 - Salmon Cinotti, T A1 - D'Elia, A A1 - Roffia, L A1 - Zamagni, G A1 - Lamberti, C Y1 - 2011/// KW - Environmental contexts KW - Health care KW - Health management KW - Health-care system KW - High quality KW - Hospitals KW - Integrated frameworks KW - Interoperability KW - Ontology KW - Open sources KW - Real time monitoring KW - Research challenges KW - Semantic Web KW - Semantics KW - Socio-economic problems KW - User interfaces KW - Web data models KW - alarm monitoring KW - article KW - health care management KW - human KW - interpersonal communication KW - microprocessor KW - outpatient care KW - priority journal KW - telemedicine JF - International Journal of Telemedicine and Applications UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052674938&doi=10.1155%2F2011%2F549282&partnerID=40&md5=6a975d25fd217f5e2d940d32d7c56780 N1 - Cited By :18 Export Date: 10 September 2018 References: http://epp.eurostat.ec.europa.eu/, Population Project Europop; http://www.ihi.org/, Institute For Healthcare Improvement (ihi); Touche, D., (2000) The Emerging European Health Telematics IndustryHealth Information Society Technology Based Industry Study, , European Commission-Directorate General Information Society; Walker, J., Pan, E., Johnston, D., Adler-Milstein, J., Bates, D.W., Bates, B., The value of health care information exchange and interoperability (2005) Health Affairs, pp. W510-W518. , Suppl Web Exclusives; Park, J., Ram, S., Information systems interoperability: What lies beneath? (2004) ACM Transactions on Information Systems, 22 (4), pp. 595-632; http://www.sofia-project.eu/, Sofia (smart Object For Intelligence Applications); http://www.chiron-project.eu/, Chiron (cyclic And Person-Centric Health Management: Integrated Approach For Home Mobile And Clinical Environments) Project; Mark, R., Telemedicine system: The missing link between homes and hospitals? (1974) Modern Nursing Home, 32 (2), pp. 39-42; Finley, J.P., Human, D.G., Nanton, M.A., Roy, D.L., Macdonald, R.G., Marr, D.R., Chiasson, H., Echocardiography by telephone - Evaluation of pediatric heart disease at a distance (1989) American Journal of Cardiology, 63 (20), pp. 1475-1477. , DOI 10.1016/0002-9149(89)90011-8; http://www.oldes.eu/, Oldes (older Peoples E-Services Ah Home); Noury, N., AILISA: Experimental platforms to evaluate remote care and assistive technologies in gerontology Proceedings of the 7th IEEE International Workshop on Enterprise Networking and Computing in Healthcare Industry June 2005 Busan, South Korea, pp. 23-25; Jiang, L., Liu, D.Y., Yang, B., Smart home research Proceedings of the 2004 International Conference on Machine Learning and Cybernetics August 2004 Shanghai, China, 2, pp. 659-663; Noury, N., Virone, G., Barralon, P., Ye, J., Rialle, V., Demongeot, J., New trends in health smart homes Proceedings of the 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (Healthcom '03) June 2003, pp. 118-127; http://www.monami.info/, Mainstreaming On Ambient Intelligence (monami) Project; http://www.urmc.rochester.edu/future-health/index.cfm, Smart Medical Home Research Laboratory Center For Future Health University Of Rochester; Kidd, C., Orr, R., Abowd, G., The aware home: A living laboratory for ubiquitous computing research Proceedings of the 2nd International Workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture October 1999, pp. 191-198; Knoefel, F., Emerson, V., Schulman, B., TAFETA: An inclusive design for tele-health Proceedings of the Technology and Persons with Disabilities Conference Month Year San Diego, Calif, USA; Helal, S., Mann, W., El-Zabadani, H., King, J., Kaddoura, Y., Jansen, E., The Gator tech smart house: A programmable pervasive space (2005) Computer, 38 (3), pp. 50-60. , DOI 10.1109/MC.2005.107; http://www.smarthome.duke.edu/, Home Depot Smart Home Pratt School Of Engineering Duke University; Bartolomeu, P., Fonseca, J., Santos, V., Mota, A., Silva, V., Sizenando, M., Automating home appliances for elderly and impaired people: The B-live approach Proceedings of the 2nd International Conference on Software Development for Enhancing Accessibility and Fighting Info-exclusion (DSAI '07) November 2007; Chan, M., Estve, D., Escriba, C., Campo, E., A review of smart homes-present state and future challenges (2008) Computer Methods and Programs in Biomedicine, 91 (1), pp. 55-81; Hsu, C., Bouziane, M., Cheung, W., Rattner, L., Yee, L., Metadatabase modeling for enterprise information integration (1992) Journal of Systems Integration, 2 (1), pp. 5-37; Weiser, M., The computer for the 21st century (2002) IEEE Pervasive Computing, 99 (1), pp. 19-25; Ieee std 610.12-1990 Ieee Standard Glossary of Software Engineering Terminology, , http://standards.ieee.org/reading/ieee/stdpublic/description/se/610. 12-1990desc.html, Ieee Standards Committee; Lappetelinen, A., Tuupola, J.-M., Palin, A., Eriksson, T., Networked systems, services and information the ultimate digital convergence Proceedings of the 1st International NoTA Conference June 2008 Helsinki, Finland; Zimmermann Hubert, OSI reference modelthe ISO model of architecture for open systems interconnection (1980) IEEE transactions on communications systems, COM-28 (4), pp. 425-432; http://sourceforge.net/projects/smart-m3, Smart-M3 Public Source Code; Honkola, J., Hannu, L., Brown, R., Tyrkk, O., Smart-M3 Information Sharing Platform, pp. 1041-1046. , Computers and Communications, 2010 IEEE Symposium on (ISCC '10) June 2010 Riccione, Italy; http://en.wikipedia.org/wiki/Smart-M3, Smart-M3 Wikipedia; http://www.sofia-project.eu/node/329, Sofia Deliverable 5.11: Interoperability Platform Principles; http://www.w3.org/, World Wid Web Consortium; Lassila, O., Horrocks, I., Hendler, J., Taking the RDF model theory out for a spin Proceedings of the First International Semantic Web Conference(ISWC '02) June 2002 Sardinia, Italy Springer Number 2342 in Lecture Notes in Computer Science, pp. 307-317; Noy, N.F., McGuinness, D.L., Ontology development 101: A guide to creating your first ontology (2001) KSL-01-05, , Stanford Knowledge Systems Laboratory; Vergari, F., Bartolini, S., Spadini, F., D'Elia, A., Zamagni, G., Roffia, L., Cinotti, T.S., A smart space application to dynamically relate medical and environmental information Design, Automation and Test in Europe Conference and Exhibition(DATE '10), pp. 1542-1547. , March 2010 Dresden, Germany; Kyle, W., Rand, B., Kolar, M., The human bioclimate of Hong Kong (1994) Proceedings of the Contemporary Climatology Conference, pp. 345-350; Roffia, L., D'Elia, A., Vergari, F., A smart-M3 lab course: Approach and design style to support student projects Proceedings of the 8th FRUCT Conference of Open Innovations Framework Program (FRUCT.10) 2010 Saint-Petersburg, Finland State University of Aerospace Instrumentation (SUAI), pp. 142-153 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The need for high-quality out-of-hospital healthcare is a known socioeconomic problem. Exploiting ICT's evolution, ad-hoc telemedicine solutions have been proposed in the past. Integrating such ad-hoc solutions in order to cost-effectively support the entire healthcare cycle is still a research challenge. In order to handle the heterogeneity of relevant information and to overcome the fragmentation of out-of-hospital instrumentation in person-centric healthcare systems, a shared and open source interoperability component can be adopted, which is ontology driven and based on the semantic web data model. The feasibility and the advantages of the proposed approach are demonstrated by presenting the use case of real-time monitoring of patients' health and their environmental context. Copyright © 2011 Fabio Vergari et al. ER - TY - JOUR T1 - Differing Strategies to Meet Information-Sharing Needs: Publicly Supported Community Health Information Exchanges Versus Health Systems' Enterprise Health Information Exchanges A1 - Vest, J R A1 - Kash, B A Y1 - 2016/// KW - health information exchange KW - health information systems KW - integrated delivery systems KW - qualitative research JF - Milbank Quarterly VL - 94 IS - 1 SP - 77 EP - 108 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84963944000&doi=10.1111%2F1468-0009.12180&partnerID=40&md5=0316b36f986d2c2375fd445314f94cf5 N1 - Cited By :7 Export Date: 1 February 2018 Cited By :7 Cited By :7 Cited By :7 Export Date: 1 February 2018 Export Date: 1 February 2018 Export Date: 1 February 2018 Cited By :7 Cited By :7 Cited By :7 Export Date: 1 February 2018 Export Date: 1 February 2018 Export Date: 1 February 2018 Cited By :12 Export Date: 10 September 2018 References: (2008) Report to the Office of the National Coordinator for Health Information Technology on Defining Key Health Information Technology Terms, , http://healthit.hhs.gov/portal/server.pt?open=18&objID=848133&parentname=CommunityPage&parentid=5&mode=2&in_hi_userid=10741&cached=true, Accessed March 3, 2010; Office of the National Coordinator for Health Information Technology, (2012) State Health Information Exchange Cooperative Agreement Program, , http://healthit.hhs.gov/portal/server.pt?open=512&objID=1488&mode=2, Accessed October 5, 2015; Furukawa, M.F., Patel, V., Charles, D., Swain, M., Mostashari, F., Hospital electronic health information exchange grew substantially in 2008-12 (2013) Health Aff, 32 (8), pp. 1346-1354; Furukawa, M.F., King, J., Patel, V., Hsiao, C.-J., Adler-Milstein, J., Jha, A.K., Despite substantial progress in EHR adoption, health information exchange and patient engagement remain low in office settings (2014) Health Aff, 33 (9), pp. 1672-1679; US Department of Health & Human Services, 45 CFR Part 170. 2014 Edition Release 2 Electronic Health Record (EHR) Certification Criteria and the ONC HIT Certification Program; Regulatory Flexibilities, Improvements, and Enhanced Health Information Exchange. Final Rule (2014) Federal Register, 79 (176); Vest, J., Gamm, L.D., Health information exchange: Persistent challenges & new strategies (2010) JAMIA, 17 (3), pp. 288-294; Rubin, R.D., The community health information movement: Where it's been, where it's going (2003) Public Health Informatics & Information Systems, , O'Carroll P.W. Yasnoff W.A. Ward M.E. Ripp L.H. Martin E.L. eds. New York, NY: Springer; Harris Healthcare Solutions, (2012) Harness the Power of Enterprise HIE, , Melbourne, FL: Harris Healthcare Solutions; Centers for Medicare & Medicaid Services, (2014) Frequently Asked Questions (FAQ7697), , https://questions.cms.gov/faq.php?faqId=7697, Accessed December 18, 2015; Merriam, S.B., (2009) Qualitative Research: a Guide to Design and Implementation, , San Francisco, CA: Jossey-Bass; Saldaña, J., (2013) The Coding Manual for Qualitative Researchers, , 2nd ed. Thousand Oaks, CA: Sage Publications; QSR, (2014) Vivo10 for Windows Help, , http://help-nv10.qsrinternational.com/desktop/procedures/run_a_coding_comparison_query.htm, Accessed February 12, 2014; Sinclair, J., Cardew-Hall, M., The folksonomy tag cloud: When is it useful? (2008) J Inf Sci, 34 (1), pp. 15-29; Bateman, S., Gutwin, C., Nacenta, M., Seeing things in the clouds: The effect of visual features on tag cloud selections (2008) Proceedings of the 19th ACM Conference on Hypertext and Hypermedia, , Pittsburgh, PA; Halvey, M.J., Keane, M.T., An assessment of tag presentation techniques (2007) Proceedings of the 16th International Conference on World Wide Web, , Banff, AB, Canada; Rivadeneira, A.W., Gruen, D.M., Muller, M.J., Millen, D.R., Getting our head in the clouds: Toward evaluation studies of tagclouds (2007) Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, , San Jose, CA; Jackson, C.T., Trygstad, T.K., DeWalt, D.A., DuBard, C.A., Transitional care cut hospital readmissions for North Carolina Medicaid patients with complex chronic conditions (2013) Health Aff, 32 (8), pp. 1407-1415; DeVore, S., Champion, R.W., Driving population health through accountable care organizations (2011) Health Aff, 30 (1), pp. 41-50; Williams, C., Mostashari, F., Mertz, K., Hogin, E., Atwal, P., From the Office of the National Coordinator: The strategy for advancing the exchange of health information (2012) Health Aff, 31 (3), pp. 527-536; Starr, P., Smart technology, stunted policy: Developing health information networks (1997) Health Aff, 16 (3), pp. 91-105; Cook, K., Shortell, S.M., Conrad, D.A., Morrisey, M.A., A theory of organizational response to regulation: The case of hospitals (1983) Acad Manage Rev, 8 (2), pp. 193-205; Adler-Milstein, J., Bates, D.W., Jha, A.K., Operational health information exchanges show substantial growth, but long-term funding remains a concern (2013) Health Aff, 32 (8), pp. 1486-1492; Ancker, J.S., Miller, M.C., Patel, V., Kaushal, R., Sociotechnical challenges to developing technologies for patient access to health information exchange data (2014) JAMIA, 21 (4), pp. 664-670; National Opinion Research Center (NORC), (2014) Evaluation of the State Health Information Exchange Cooperative Research Agreement Program. State Approaches to Enabling HIE: Typology Brief, , Bethesda, MD: NORC; Lenert, L., Sundwall, D., Lenert, M.E., Shifts in the architecture of the Nationwide Health Information Network (2012) JAMIA, 19 (4), pp. 498-502; Shapiro, J.S., Mostashari, F., Hripcsak, G., Soulakis, N., Kuperman, G., Using health information exchange to improve public health (2011) Am J Public Health, 101 (4), pp. 616-623; Kleinke, J.D., Dot-gov: Market failure and the creation of a national health information technology system (2005) Health Aff, 24 (5), pp. 1246-1262; Vest, J., Campion, T.R., Jr., Kaushal, R., Challenges, alternatives, and paths to sustainability for health information exchange efforts (2013) J Med Syst, 37 (6), p. 9987; Miller, R.H., Satisfying patient-consumer principles for health information exchange: Evidence from California case studies (2012) Health Aff, 31 (3), pp. 537-547; Office of the National Coordinator for Health Information Technology, (2013) Principles and Strategy for Accelerating Health Information Exchange (HIE), , Washington, DC: Centers for Medicare & Medicaid Services; Office of the National Coordinator for Health Information Technology, (2014) Federal Health IT Strategic Plan 2015-2020, , Washington, DC; Adler-Milstein, J., Bates, D.W., Jha, A.K., U.S. regional health information organizations: Progress and challenges (2009) Health Aff, 28 (2), pp. 483-492; National Opinion Research Center (NORC), (2012) Evaluation of the State Health Information Exchange Cooperative Agreement Program: Early Findings from a Review of Twenty-Seven States, , Bethesda, MD: NORC; Chokshi, D.A., Rugge, J., Shah, N.R., Redesigning the regulatory framework for ambulatory care services in New York (2014) Milbank Q, 92 (4), pp. 776-795; Medicare Access and CHIP Reauthorization Act of 2015 (2015) STAT., 87; Office of the National Coordinator for Health Information Technology, (2015) Report to Congress: Report on Health Information Blocking, , Washington, DC: US Department of Health and Human Services; April; Allen, A., (2015) Doctors Say Data Fees Are Blocking Health Reform, , http://www.politico.com/story/2015/02/data-fees-health-care-reform-115402.html#ixzz3SwzncooP, Accessed February 27, 2015; Payne, T.H., Corley, S., Cullen, T.A., Report of the AMIA EHR 2020 Task Force on the status and future direction of EHRs (2015) JAMIA, , http://dx.doi.org/10.1093/jamia/ocv066; JASON, (2014) A Robust Health Data Infrastructure, , AHRQ Publication No. 14-0041. Rockville, MD: Agency for Healthcare Research and Quality; Ramaiah, M., Subrahmanian, E., Sriram, R.D., Lide, B.B., Workflow and electronic health records in small medical practices (2012) Perspectives in Health Information Management / American Health Information Management Association, 9 (Spring), p. 1d; Chen, C., Garrido, T., Chock, D., Okawa, G., Liang, L., The Kaiser Permanente electronic health record: Transforming and streamlining modalities of care (2009) Health Aff, 28 (2), pp. 323-333; Gurbaxani, V., Whang, S., The impact of information systems on organizations and markets (1991) Community ACM, 34 (1), pp. 59-73; Berwick, D.M., Nolan, T.W., Whittington, J., The triple aim: Care, health, and cost (2008) Health Aff, 27 (3), pp. 759-769 RAYYAN-INCLUSION: {"Fernanda"=>true} | RAYYAN-LABELS: HIE N2 - Policy Points: Community health information exchanges have the characteristics of a public good, and they support population health initiatives at the state and national levels. However, current policy equally incentivizes health systems to create their own information exchanges covering more narrowly defined populations. Noninteroperable electronic health records and vendors' expensive custom interfaces are hindering health information exchanges. Moreover, vendors are imposing the costs of interoperability on health systems and community health information exchanges. Health systems are creating networks of targeted physicians and facilities by funding connections to their own enterprise health information exchanges. These private networks may change referral patterns and foster more integration with outpatient providers. Context The United States has invested billions of dollars to encourage the adoption of and implement the information technologies necessary for health information exchange (HIE), enabling providers to efficiently and effectively share patient information with other providers. Health care providers now have multiple options for obtaining and sharing patient information. Community HIEs facilitate information sharing for a broad group of providers within a region. Enterprise HIEs are operated by health systems and share information among affiliated hospitals and providers. We sought to identify why hospitals and health systems choose either to participate in community HIEs or to establish enterprise HIEs. Methods We conducted semistructured interviews with 40 policymakers, community and enterprise HIE leaders, and health care executives from 19 different organizations. Our qualitative analysis used a general inductive and comparative approach to identify factors influencing participation in, and the success of, each approach to HIE. Findings Enterprise HIEs support health systems' strategic goals through the control of an information technology network consisting of desired trading partners. Community HIEs support obtaining patient information from the broadest set of providers, but with more dispersed benefits to all participants, the community, and patients. Although not an either/or decision, community and enterprise HIEs compete for finite organizational resources like time, skilled staff, and money. Both approaches face challenges due to vendor costs and less-than-interoperable technology. Conclusions Both community and enterprise HIEs support aggregating clinical data and following patients across settings. Although they can be complementary, community and enterprise HIEs nonetheless compete for providers' attention and organizational resources. Health policymakers might try to encourage the type of widespread information exchange pursued by community HIEs, but the business case for enterprise HIEs clearly is stronger. The sustainability of a community HIE, potentially a public good, may necessitate ongoing public funding and supportive regulation. © 2016 Milbank Memorial Fund. ER - TY - JOUR T1 - An evidence-based strategy to achieve equivalency and interoperability for social-behavioral determinants of health assessment, storage, exchange, and use A1 - Wetta, R E A1 - Severin, R D A1 - Gruhler, H Y1 - 2019/// JF - Health Informatics Journal DO - 10.1177/1460458219882265 N2 - ©The Author(s) 2019. The interoperable exchange of social-behavioral determinants of health data is challenging due to complex factors including multiple recommendations, multiple tools with varying domains, scoring, and cutpoints, and lack of terminology code sets for storing assessments and findings. This article describes a strategy that permits scoring by social-behavioral determinants of health domain to create interoperability and equivalency across tools, settings, and populations. The three-tier scoring strategy converts social-behavioral determinants of health data to (1) be used immediately at point of care by identifying social needs or social risk factors, (2) be consumed within analytics and algorithms and for secondary analysis, and (3) produce total scores that reflect social determinant burden and behavioral determinant burden across populations and settings within a healthcare system. The strategy supports the six uses recommended by the National Academy of Medicine, provides flexibility in choice of social-behavioral determinants of health tool, and leverages the power of social-behavioral determinants of health data in healthcare delivery. ER - TY - JOUR T1 - Tapping the vast potential of the data Deluge in small-scale food-animal production businesses: Challenges to near real-time data analysis and interpretation A1 - Vial, F A1 - Tedder, A Y1 - 2017/// KW - Agribusiness KW - Animal Shells KW - Animals KW - Antimicrobial usage KW - Digitization KW - Farm data KW - Food-animal production KW - Information Storage and Retrieval JF - Frontiers in Veterinary Science VL - 4 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85038844560&doi=10.3389%2Ffvets.2017.00120&partnerID=40&md5=d81b696effb8fad688f14bae9311d16a L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Vial, Tedder - 2017 - Tapping the vast potential of the data Deluge in small-scale food-animal production businesses Challenges to ne(2).pdf N1 - Export Date: 10 September 2018 References: Bogaardt, M., Poppe, K., Viool, V., van Zuidam, E., (2016) Cybersecurity in the Agrifood Sector, , Utrecht: Capgemini Consulting; Charlebois, S., Sterling, B., Haratifar, S., Naing, S.K., Comparison of global food traceability regulations and requirements (2014) Compr Rev Food Sci Food Saf, 13 (5), pp. 1104-1123; Wu, L., Wang, H., Zhu, D., Hu, W., Wang, S., Chinese consumers' willingness to pay for pork traceability information-the case of Wuxi (2016) Agric Econ, 47 (1), pp. 71-79; Van Boeckel, T.P., Brower, C., Gilbert, M., Grenfell, B.T., Levin, S.A., Robinson, T.P., Global trends in antimicrobial use in food animals (2015) Proc Natl Acad Sci U S A, 112 (18), pp. 5649-5654; Guidelines for the prudent use of antimicrobials in veterinary medicine (2015/C-299/04) (2015) Off J Eur Union, p. 7; So, A.D., Reshma Ramachandran, D.C.L., Korinek, A., Fry, J.P., Heaney, C.D., (2016) A Framework for Costing the Lowering of Antimicrobial Use in Food Animal Production (Commissioned Paper for UK Review on AMR), , Baltimore, MD: Johns Hopkins Center for a Livable Future; Chapter 5: Livestock production (2015) World Agriculture: Towards 2015/2030: An FAO Perspective, pp. 158-175. , Bruinsma J, editor. London: Earthscan Publications Ltd; Gray, J.O., Davis, S.T., Chapter 2: Robotics in the food industry: an introduction (2012) Robotics and Automation in the Food Industry: Current and Future Technologies, pp. 21-35. , Caldwell D, editor. 1st ed. Woodhead Publishing; Smith, D., Lyle, S., Berry, A., Manning, N., Zaki, M., Neely, A., (2015) The Internet of Animal Health Things: Opportunities and Challenges, , UK: Cambridge Service Alliance; (2016) Data Revolution: Emerging New Data-Driven Business Models in the Agri-Food Sector, , Sofia, Bulgaria: EIP-AGRI seminar on Data Revolution; Wilkinson, M.D., Dumontier, M., Aalbersberg, I.J., Appleton, G., Axton, M., Baak, A., The FAIR guiding principles for scientific data management and stewardship (2016) Sci Data, 3; Dórea, F.C., Dupuy, C., Vial, F., Revie, C., Lindberg, A., Standardising syndromic classification in animal health data (2015) Online J Public Health Inform, 7 (1); Stubbs, M., (2016) Big Data in U.S, , Agriculture. Washington, DC: Congressional Research Service; Fan, J., Han, F., Liu, H., Challenges of big data analysis (2014) Natl Sci Rev, 1 (2), pp. 293-314; Roth, A., Dwork, C., The algorithmic foundations of differential privacy (2014) Found Trends® Theor Comput Sci, 9 (3-4), pp. 211-407; Anderson, J.W., Kennedy, K.E., Ngo, L.B., Luckow, A., Apon, A.W., (2014) Synthetic data generation for the internet of things, pp. 171-176. , 2014 IEEE International Conference on Big Data (Big Data). Washington, DC: IEEE; (2017) Report Prepared for a Joint G20 German Presidency/OECD Conference, , Berlin, Germany; Carbonell, I.M., The ethics of big data in big agriculture (2015) Internet Policy Rev, 5 (1) RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Food-animal production businesses are part of a data-driven ecosystem shaped by stringent requirements for traceability along the value chain and the expanding capabilities of connected products. Within this sector, the generation of animal health intelligence, in particular, in terms of antimicrobial usage, is hindered by the lack of a centralized framework for data storage and usage. In this Perspective, we delimit the 11 processes required for evidence-based decisions and explore processes 3 (digital data acquisition) to 10 (communication to decision-makers) in more depth. We argue that small agribusinesses disproportionally face challenges related to economies of scale given the high price of equipment and services. There are two main areas of concern regarding the collection and usage of digital farm data. First, recording platforms must be developed with the needs and constraints of small businesses in mind and move away from local data storage, which hinders data accessibility and interoperability. Second, such data are unstructured and exhibit properties that can prove challenging to its near real-time preprocessing and analysis in a sector that is largely lagging behind others in terms of computing infrastructure and buying into digital technologies. To complete the digital transformation of this sector, investment in rural digital infrastructure is required alongside the development of new business models to empower small businesses to commit to near real-time data capture. This approach will deliver critical information to fill gaps in our understanding of emerging diseases and antimicrobial resistance in production animals, eventually leading to effective evidence-based policies. © 2017 Vial and Tedder. ER - TY - JOUR T1 - Design and prototype of an interoperable online air quality information system A1 - Wiemann, S A1 - Brauner, J A1 - Karrasch, P A1 - Henzen, D A1 - Bernard, L Y1 - 2016/// KW - Air quality KW - Air quality modeling KW - Decision making KW - Design and Development KW - Early Warning System KW - Health risks KW - Information Systems KW - Interoperability KW - Potential health risks KW - Quality information KW - Quality information system KW - Real time monitoring KW - Risk assessment KW - Search engines KW - Sensor observations KW - Spatial data infrastructure KW - World Wide Web KW - air quality KW - ambient air KW - atmospheric modeling KW - design method KW - early warning system KW - information system KW - sensor KW - spatial data JF - Environmental Modelling and Software VL - 79 SP - 354 EP - 366 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960251200&doi=10.1016%2Fj.envsoft.2015.10.028&partnerID=40&md5=8d2b17b21e6f1c89bb4fcbfb3b15fb90 L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Wiemann et al. - 2016 - Design and prototype of an interoperable online air quality information system.pdf N1 - Cited By :8 Export Date: 10 September 2018 References: Bastin, L., Cornford, D., Jones, R., Heuvelink, G.B., Pebesma, E., Stasch, C., Nativi, S., Williams, M., Managing uncertainty in integrated environmental modelling: the uncertweb framework (2013) Environ. Model. Softw., 39, pp. 116-134; Bernard, L., Mäs, S., Müller, M., Henzen, C., Brauner, J., Scientific geodata infrastructures: challenges, approaches and directions (2014) Int. J. Digital Earth, 7 (7), pp. 613-633; Boulos, M.N.K., Resch, B., Crowley, D.N., Breslin, J.G., Sohn, G., Burtner, R., Pike, W.A., Chuang, K.S., Crowdsourcing, citizen sensing and sensor web technologies for public and environmental health surveillance and crisis management: trends, OGC standards and application examples (2011) Int. J. Health Geogr., 10, p. 67; Bröring, A., Maué, P., Janowicz, K., Nüst, D., Malewski, C., Semantically-enabled sensor plug & play for the sensor web (2011) Sensors, 11, pp. 7568-7605; Burrough, P.A., Development of intelligent geographical information systems (1992) Int. J. Geogr. Inf. Sci., 6 (1), pp. 1-11; Castronova, A.M., Goodall, J.L., Elag, M.M., Models as web services using the open geospatial consortium (OGC) web processing service (WPS) standard (2013) Environ. Model. Softw., 41, pp. 72-83; Craglia, M., de Bie, K., Jackson, D., Pesaresi, M., Remetey-Fülöpp, G., Wang, C., Annoni, A., Woodgate, P., Digital Earth 2020: towards the vision for the next decade (2012) Int. J. Digital Earth, 5 (1), pp. 4-21; De Longueville, B., Annoni, A., Schade, S., Ostlaender, N., Whitmore, C., Digital Earth's nervous system for crisis events: real-time sensor web enablement of volunteered geographic information (2010) Int. J. Digital Earth, 3 (3), pp. 242-259; (2012) Air Quality in Europe - 2012 Report, , European Environment Agency, Technical Report; Emili, E., Popp, C., Petitta, M., Riffler, M., Wunderle, S., Zebisch, M., PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European alpine region (2010) Remote Sens. Environ., 114, pp. 2485-2499; Emeis, E., Schäfer, K., Remote sensing methods to investigate boundary-layer structures relevant to air pollution in cities (2006) Bound. Layer Meteorol., 121 (2), pp. 377-385; Engel-Cox, J., Oanh, N.T.K., Van Donkelaar, A., Martin, R.V., Zell, E., Toward the next generation of air quality monitoring: Particulate Matter (2013) Atmos. Environ., 80, pp. 584-590; (2008) Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on Ambient Air Quality and Cleaner Air for Europe; Foerster, T., Schaeffer, B., Baranski, B., Brauner, J., Geospatial web services for distributed processing: applications and scenarios (2011) Geospatial Web Services: Advances in Information Interoperability, pp. 245-286. , IGI Global, Hershey, PA, P. Zhao, L. Di (Eds.); Goodchild, M.F., Citizens as sensors: the world of volunteered geography (2007) GeoJournal, 69 (4), pp. 211-221; Gulliver, J., de Hoogh, K., Fecht, D., Vienneau, D., Briggs, D., Comparative assessment of GIS-based methods and metrics for estimating long-term exposures to air pollution (2011) Atmos. Environ., 45, pp. 7072-7080; Hamilton, S.H., ElSawah, S., Guillaume, J.H.A., Jakeman, A.J., Pierce, S.A., Integrated assessment and modelling: overview and synthesis of salient dimensions (2015) Environ. Model. Softw., 64, pp. 215-229; Hänel, G., The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air (1976) Adv. Geophys., 19, pp. 73-188; Henzen, C., Mäs, S., Bernard, L., Provenance information in geodata infrastructures (2013) Geographic Information Science at the Heart of Europe, 2013. Lecture Notes in Geoinformation and Cartography, pp. 133-151. , Springer, D. Vandenbroucke, B. Bucher, J. Crompvoets (Eds.); Hoek, G., Beelen, R., de Hoogh, K., Vienneau, D., Gulliver, J., Fischer, P., Briggs, D., A review of land-use regression models to assess spatial variation of outdoor air pollution (2008) Atmos. Environ., 42, pp. 7561-7578; Hoff, R.H., Christopher, S.A., Remote sensing of particulate pollution from space: have we reached the promised land? (2009) J. Air Waste Manag. Assoc., 59 (6), pp. 645-675; Hubanks, P.A., (2007) MODIS Atmosphere QA Plan for Collection 005 - Deep Blue Aerosol Update. Version 3.5, , NASA, Technical Report; Janssen, N., Mehta, S., (2006) Human Exposure to Air Pollution, pp. 61-85. , World Health Organization, (Chapter 3); Janssen, S., Dumont, G., Fierens, F., Mensink, C., Spatial interpolation of air pollution measurements using corine land cover data (2008) Atmos. Environ., 42, pp. 4884-4903; Jirka, S., Bröring, A., Kjeld, P., Maidens, J., Wytzisk, A., A lightweight approach for the sensor observation service to share environmental data across Europe (2012) Trans. GIS, 16, pp. 293-312; Johansson, L., Epitropou, V., Karatzas, K., Karppinen, A., Wanner, L., Vrochidis, S., Bassoukos, A., Kompatsiaris, I., Fusion of meteorological and air quality data extracted from the web for personalized environmental information services (2015) Environ. Model. Softw., 64, pp. 143-155; Klingner, M., Sähn, E., Prediction of PM10 concentration on the basis of high resolution weather forecasting (2008) Meteorol. Z., 17, pp. 263-272; Koelemeijer, R., Homan, C., Matthijsen, J., Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe (2006) Atmos. Environ., 40, pp. 5304-5315; Laniak, G.F., Olchin, G., Goodall, J., Voinov, A., Hill, M., Glynn, P., Whelan, G., Hughes, A., Integrated environmental modeling: a vision and roadmap for the future (2013) Environ. Model. Softw., 39, pp. 3-23; MacEachren, A.M., Robinson, A., Hopper, S., Gardner, S., Murray, R., Gahegan, M., Hetzler, E., Visualizing geospatial information uncertainty: what we know and what we need to know (2005) Cartogr. Geogr. Inf. Sci., 32 (3), pp. 139-160; Martin, R., Satellite remote sensing of surface air quality (2008) Atmos. Environ., 2, pp. 7823-7843; McGregor, G., Identification of air quality affinity areas in Birmingham, UK (1996) Appl. Geogr., 16, pp. 109-122; Müller, M., Bernard, L., Kadner, D., Moving code - sharing geoprocessing logic on the web (2013) ISPRS J. Photogrammetr. Remote Sens., 83, pp. 193-203; Nativi, S., Mazzetti, P., Geller, G.N., Environmental model access and interoperability: the GEO ModelWeb initiative (2013) Environ. Model. Softw., 39, pp. 214-228; Ostro, B., (2004) Outdoor Air Pollution, , World Health Organization, Technical Report; Pebesma, E., Cornford, D., Dubois, G., Heuvelink, G., Hristopulos, D., Pilz, J., Stöhlker, U., Skøien, J., Intamap: the design and implementation of an interoperable automated interpolation web service (2011) Comput. Geosci., 37, pp. 343-352; Randriamiarisoa, H., Chazette, P., Couvert, P., Sanak, J., Mégie, G., Relative humidity impact on aerosol parameters in a Paris suburban area (2006) Atmos. Chem. Phys., 6, pp. 1389-1407; Remer, L.A., Kaufman, Y.J., Tanré, D., Mattoo, S., Chu, D.A., Martins, J.V., Li, R.-R., Holben, B.N., The MODIS aerosol algorithm, products, and validation (2005) J. Atmos. Sci., 62 (4), pp. 947-973; Ryan, P.H., LeMasters, G.K., A review of land-use regression models for characterizing intraurban air pollution exposure (2007) Inhal. Toxicol., 19, pp. 127-133; Schulte-Braucks, R., Observing the land beyond (2013) Int. Innov., pp. 44-47; Shepard, D., A two-dimensional interpolation function for irregularly spaced data (1968) Proceedings of the 1968 23rd ACM National Conference, ACM, New York, NY, USA, pp. 517-524; Thunis, P., Georgieva, E., Pederzoli, A., A tool to evaluate air quality model performances in regulatory applications (2012) Environ. Model. Softw., 38, pp. 220-230; Tobler, W., A computer movie simulating urban growth in the Detroit region (1970) Econ. Geogr., 46, pp. 234-240; Van Donkelaar, A., Martin, R.V., Brauer, M., Kahn, R., Levy, R., Verduzco, C., Villeneuve, P.J., Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application (2010) Environ. Health Perspect., 118, pp. 847-855; Vienneau, D., Briggs, D.J., Delimiting affinity zones as a basis for air pollution mapping in Europe (2013) Environ. Int., 51, pp. 106-115; Vitolo, C., Elkhatib, Y., Reusser, D., Macleod, C.J.A., Buytaert, W., Web technologies for environmental big data (2015) Environ. Model. Softw., 63, pp. 185-198; Williams, M., Cornford, D., Bastin, L., Pebesma, E., (2009) Uncertainty Markup Language (UnCertML), , OpenGIS Discussion Paper. Version 0.6; (2009) Global Health Risks: Mortality and Burden of Disease Attributable to Selected Major Risks, , World Health Organization, Technical Report; (2013) Review of Evidence on Health Aspects of Air Pollution - REVIHAAP Project, , World Health Organization, Regional Office for Europe, Technical Report; Yue, P., Zhang, M., Tan, Z., A geoprocessing workflow system for environmental monitoring and integrated modelling (2015) Environ. Model. Softw., 69, pp. 128-140 RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - This paper focuses on the design and development of a Spatial Data Infrastructure (SDI)-compliant online system for air quality information retrieval, including support for real-time monitoring. This system assesses exposure to ambient air to mitigate potential health risks, which is crucial for susceptible individuals, health practitioners and decision makers. Particular attention is paid to the development of an interoperable, applicable and transferrable approach to the application of robust and flexible air quality modeling as required for early warning systems on the Web. Moreover, the design provides different access levels to system components for both non-expert and scientific users and supports extension with external standard compliant services. The developed Web-client Time2Maps enables the user to view, analyze and download requested air quality information and serves as a portal to the designed online system. © 2015 Elsevier Ltd. ER - TY - JOUR T1 - SADI, SHARE, and the in silico scientific method A1 - Wilkinson, Mark D A1 - McCarthy, Luke A1 - Vandervalk, Benjamin A1 - Withers, David A1 - Kawas, Edward A1 - Samadian, Soroush Y1 - 2010/// KW - Algorithms KW - Bioinformatics KW - Combinatorial Libraries KW - Computational Biology/Bioinformatics KW - Computer Appl. in Life Sciences KW - Computer Simulation KW - Microarrays KW - Semantics PB - BioMed Central JF - BMC Bioinformatics VL - 11 SP - S7 EP - S7 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England UR - http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-11-S12-S7 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The emergence and uptake of Semantic Web technologies by the Life Sciences provides exciting opportunities for exploring novel ways to conduct in silico science. Web Service Workflows are already becoming first-class objects in “the new way”, and serve as explicit, shareable, referenceable representations of how an experiment was done. In turn, Semantic Web Service projects aim to facilitate workflow construction by biological domain-experts such that workflows can be edited, re-purposed, and re-published by non-informaticians. However the aspects of the scientific method relating to explicit discourse, disagreement, and hypothesis generation have remained relatively impervious to new technologies. Here we present SADI and SHARE - a novel Semantic Web Service framework, and a reference implementation of its client libraries. Together, SADI and SHARE allow the semi- or fully-automatic discovery and pipelining of Semantic Web Services in response to ad hoc user queries. The semantic behaviours exhibited by SADI and SHARE extend the functionalities provided by Description Logic Reasoners such that novel assertions can be automatically added to a data-set without logical reasoning, but rather by analytical or annotative services. This behaviour might be applied to achieve the “semantification” of those aspects of the in silico scientific method that are not yet supported by Semantic Web technologies. We support this suggestion using an example in the clinical research space. ER - TY - JOUR T1 - The Semantic Automated Discovery and Integration (SADI) Web service Design-Pattern, API and Reference Implementation A1 - Wilkinson, Mark D A1 - Vandervalk, Benjamin A1 - McCarthy, Luke Y1 - 2011/// KW - Algorithms KW - Bioinformatics KW - Combinatorial Libraries KW - Computational Biology KW - Computational Biology/Bioinformatics KW - Computer Appl. in Life Sciences KW - Data Mining and Knowledge Discovery KW - Semantics PB - BioMed Central JF - Journal of Biomedical Semantics VL - 2 IS - 1 SP - 8 EP - 8 CY - Department of Orthopaedics and Rheumatology, University Hospital Marburg, Baldingerstrasse, Marburg, Germany. efet@med.uni-marburg.de England UR - http://jbiomedsem.biomedcentral.com/articles/10.1186/2041-1480-2-8 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The complexity and inter-related nature of biological data poses a difficult challenge for data and tool integration. There has been a proliferation of interoperability standards and projects over the past decade, none of which has been widely adopted by the bioinformatics community. Recent attempts have focused on the use of semantics to assist integration, and Semantic Web technologies are being welcomed by this community. SADI - Semantic Automated Discovery and Integration - is a lightweight set of fully standards-compliant Semantic Web service design patterns that simplify the publication of services of the type commonly found in bioinformatics and other scientific domains. Using Semantic Web technologies at every level of the Web services "stack", SADI services consume and produce instances of OWL Classes following a small number of very straightforward best-practices. In addition, we provide codebases that support these best-practices, and plug-in tools to popular developer and client software that dramatically simplify deployment of services by providers, and the discovery and utilization of those services by their consumers. SADI Services are fully compliant with, and utilize only foundational Web standards; are simple to create and maintain for service providers; and can be discovered and utilized in a very intuitive way by biologist end-users. In addition, the SADI design patterns significantly improve the ability of software to automatically discover appropriate services based on user-needs, and automatically chain these into complex analytical workflows. We show that, when resources are exposed through SADI, data compliant with a given ontological model can be automatically gathered, or generated, from these distributed, non-coordinating resources - a behaviour we have not observed in any other Semantic system. Finally, we show that, using SADI, data dynamically generated from Web services can be explored in a manner very similar to data housed in static triple-stores, thus facilitating the intersection of Web services and Semantic Web technologies. ER - TY - JOUR T1 - Public health delivery in the information age: the role of informatics and technology A1 - Williams, F A1 - Oke, A A1 - Zachary, I Y1 - 2019/// JF - Perspectives in Public Health VL - 139 IS - 5 SP - 236 EP - 254 DO - 10.1177/1757913918802308 N2 - ©Royal Society for Public Health 2019. Aim: Public health systems have embraced health informatics and information technology as a potential transformational tool to improve real-time surveillance systems, communication, and sharing of information among various agencies. Global pandemic outbreaks like Zika and Ebola were quickly controlled due to electronic surveillance systems enabling efficient information access and exchange. However, there is the need for a more robust technology to enhance adequate epidemic forecasting, data sharing, and effective communication. The purpose of this review was to examine the use of informatics and information technology tools and its impact on public health delivery. Method: Investigators searched six electronic databases. These were MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) Complete, Cochrane Database of Systematic Reviews, COMPENDEX, Scopus, and Academic Search Premier from January 2000 to 31 March 2016. Results: A total of 60 articles met the eligibility criteria for inclusion. These studies were organized into three areas as (1) definition of the term public health informatics; (2) type of public health surveillance systems and implications for public health; and (3) electronic surveillance systems functionality, capability, training, and challenges. Our analysis revealed that due to the growing expectations to provide real-time response and population-centered evidence-based public health in this information-driven age there has been a surge in informatics and information technology adoption. Education and training programs are now available to equip public health students and professionals with skills in public health informatics. However, obstacles including interoperability, data standardization, privacy, and technology transfer persist. Conclusion: Re-engineering the delivery of public health is necessary to meet the demands of the 21st century and beyond. To meet this expectation, public health must invest in workforce development and capacity through education and training in informatics. ER - TY - CONF T1 - Towards a SOA infrastructure for statistically analysing public health data A1 - Vittorini, P A1 - Necozione, S A1 - Di Orio, F Y1 - 2007/// KW - Biomedical data KW - Caching mechanism KW - Data sets KW - Health KW - Health informatics KW - High level languages KW - Information Systems KW - Information science KW - Information systems KW - Knowledge management KW - Large datasets KW - Markup languages KW - Public health KW - Query languages KW - SOA KW - Standardization KW - Statistical analysis KW - Statistical packages KW - Statistical tests KW - Statistics KW - Web services KW - XML KW - XML data SP - 11 EP - 16 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954343428&doi=10.1145%2F1317353.1317357&partnerID=40&md5=6edce196d47b05e1d8164294bd2f8278 N1 - Cited By :3 Export Date: 10 September 2018 References: Berglund, A., Boag, S., Chamberlin, D., Fernández, M.F., Kay, M., Robie, J., Siméon, J., (2007) XML Path Language (Xpath) 2.0, , http://www.w3.org/TR/2005/CR-xpath20/; Boag, S., Chamberlin, D., Fernández, M.F., Florescu, D., Robie, J., Siméon, J., (2007) Xquery 1.0: An XML Query Language, , http://www.w3.org/TR/xquery/; Boncz, P., Grust, T., Van Keulen, M., Manegold, S., Rittinger, J., Teubner, J., Monetdb/xquery: A fast xquery processor powered by a relational engine (2006) 2006 SIGMOD Int'l Conference on Management of Data; Bray, T., Paoli, J., Sperberg-McQueen, C.M., Maler, E., Yergeau, F., (2006) Extensible Markup Language (XML) 1.0, , (fourth edition) W3C recommendation, Aug; Corporation, S., (2003) Stata Base Reference Manual, 4. , Stata Press; Dawson-Saunders, B., Trapp, R.G., (1994) Basic & Clinical Biostatistics, pp. 329-333. , chapter Appendix C: Flowcharts for relating reseach questions to statistical methods, Appleton & Lange; Dittrich, J.-P., Kossmann, D., Kreutz, A., Bridging the gap between OLAP and SQL (2005) 31st International Conference on Very Large Data Bases; Dolin, R.H., Alschuler, L., Boyer, S., Beebe, C., Behlen, F.M., Biron, P.V., Shabo, A., HL7 Clinical document architecture, Release 2 (2006) Journal of the Americal Medical Informatics Association, 13 (1), pp. 30-39; Ferris, C., Farrell, J., What are web services? (2003) Communications of the ACM, 46 (6), p. 31; Ford, E.W., Menachemi, N., Phillips, T., Predicting the adoption of electronic health records by physicians: When will health care be paperless? (2006) The Journal of the American Medical Informatics Association, 13, pp. 106-112; Gudgin, M., Hadley, M., Mendelsohn, N., Moreau, J.-J., Nielsen, H.F., (2005) SOAP Version 1.2, , http://www.w3.org/TR/soap12-part1/; Loonsk, J.W., McGarvey, S.R., Conn, L.A., Johnson, J., The Public Health Information Network (PHIN) preparedness initiative (2006) Journal of the American Medical Informatics Association, 13 (1), pp. 1-4; Malhotra, A., Melton, J., Walsh, N., (2007) Xquery 1.0 and Xpath 2.0 Functions and Operators (Aggregate Functions), , http://www.w3.org/TR/xquery-operators/#aggregatefunctions; Meier, W., EXist: An open source native XML database (2003) Lecture Notes in Computer Science, , Springer Berlin/Heidelberg; Mili, H., Mili, A., Yacoub, S., Addy, E., (2002) Reuse Based Software Engineering: Techniques, Organizations, and Measurement, , Wiley, January; (2005) EbXML, , http://www.ebxml.org/, OASIS; Olken, F., Rotem, D., (1995) Random Sampling from Databases - A Survey; (2007) Oracle Statistical Functions, , ORACLE; Sackett, D., Rosenberg, W., Gray, J., Haynes, B., Richardson, S., Evidence based medicine: What it is and what it isn't (1996) British Medical Journal, 312 (7023), pp. 71-72. , Jan; (2006) Biomedical Informatics: Computer Applications in Health Care and Biomedicine, , E. H. Shortliffe and J. J. Cimino, editors. Health Informatics. Springer-Verlag New York Inc; Vittorini, P., Orio, F.D., Data management in medicine: The EPIweb information system, a case study and some open issues (2006) Current Trends in Database Technology - EDBT 2006 Workshops, pp. 423-432. , T. G. et.al. editor, volume 4254/2006 of Lecture Notes in Computer Science, Springer-Verlag; Weerawarana, S., Curbera, F., Leymann, F., Storey, T., Ferguson, D.F., Web services platform architecture: SOAP, WSDL, WS-policy (2005) WS-Addressing, WS-BPEL, WS-Reliable Messaging, and More, , Prentice Hall PTR RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - To respond to the need for interoperable information systems in public health, several proposals based on XML-related technologies are currently available. For instance, the CDA [8] is an architecture developed by the HL7 organization for representing and managing clinical documents, while the PHIN [12] is a CDC infrastructure whose aim is to automatically exchange XML data between public health partners through ebXML compliant SOAP web services [16, 11]. Despite the large efforts spent in developing standards and infrastructures - though not conclusive - useful to achieve more effective interoperability among public health information systems, to the best of our knowledge, there are no researches produced so far to statistically analyse biomedical data represented as XML documents. Among the languages which can query XML documents, XPath can perform only basic statistics (e.g. mean, minimum, maximum [13]), while it is known that high-level tests are mandatory for every common analysis. Thus, the sole current possibility is to convert the data stored into such documents into a tabular format, and to use a standard statistical package to perform the analysis. To overcome this limitation, the paper proposes a complete SOA infrastructure, with major concern with the following components: (i) the XFNSE web-service which contains a list of operations implementing the statistical analyses reported in [6]; (ii) a prototype of a service consumer - called JXFNSE - which uses the operations exposed by XFNSE to statistically analyse a dataset; (iii) an eXist [14] module which extends XPath by adding a list of functions "tracing" the XFNSE operations. Finally, by computing several performances, the authors discuss the drawbacks of using services while analysing large datasets, and show a possible improvement in terms of a caching mechanism. ER - TY - JOUR T1 - LOINC®: A universal catalogue of individual clinical observations and uniform representation of enumerated collections A1 - Vreeman, D J A1 - McDonald, C J A1 - Huff, S M Y1 - 2010/// KW - Clinical observations KW - Data sets KW - Framework KW - Health information technology KW - Logical Observation Identifiers Names and Codes KW - Patient assessments KW - Patient data KW - Public health KW - Research KW - Standards KW - Terminology JF - International Journal of Functional Informatics and Personalised Medicine VL - 3 IS - 4 SP - 273 EP - 291 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865157207&doi=10.1504%2FIJFIPM.2010.040211&partnerID=40&md5=9ea31df1fe05f9856367a107d2938520 N1 - Cited By :19 Export Date: 10 September 2018 References: Bonander, J., Gates, S., Public health in an era of personal health records: Opportunities for innovation and new partnerships (2010) Journal of Medical Internet Research, 12 (3). , http://www.jmir.org/2010/3/e33/, [Accessed 18 March, 2011]; Brandt, C.A., Deshpande, A.M., Lu, C., Ananth, G., Sun, K., Gadagkar, R., Morse, R., Nadkarni, P.M., Center for medical informatics. TrialDB: A web-based clinical study data management system (2003) AMIA Annu Symp Proc. 2003, p. 794. , Washington DC. PubMed PMID: 14728299; PubMed Central PMCID: PMC1480035; Brandt, C.A., Cohen, D.B., Shifman, M.A., Miller, P.L., Nadkarni, P.M., Frawley, S.J., Approaches and informatics tools to assist in the integration of similar clinical research questionnaires (2004) Methods of Information in Medicine, 43 (2), pp. 156-162; (2011) Public Health Case Reporting - PhConnect, , http://www.phconnect.org/group/phcasereporting, Case Reporting Standardization Workgroup [Accessed 18 March, 2011]; (2011) NHANES - National Health and Nutrition Examination Survey Homepage, , http://cdc.gov/nchs/nhanes.htm, [Accessed 18 March, 2011]; (2011) MDS 3.0 for Nursing Homes and Swing Bed Providers, , http://www.cms.gov/nursinghomequalityinits/25_nhqimds30.asp, [Accessed 18 March, 2011]; (2008) Study Data Tabulation Model Version 1.2, , http://www.cdisc.org/sdtm, [Accessed 18 March, 2011]; (2008) Clinical Data Acquisition Standards Harmonization (CDASH) Standard Version 1.0, , http://www.cdisc.org/cdash, [Accessed 18 March, 2011]; Covitz, P.A., Hartel, F., Schaefer, C., De Coronado, S., Fragoso, G., Sahni, H., Gustafson, S., Buetow, K.H., CaCORE: A common infrastructure for cancer informatics (2003) Bioinformatics, 19 (18), pp. 2404-2412; Dugas, M., Thun, S., Frankewitsch, T., Heitmann, K.U., LOINC codes for hospital information systems documents: A case study (2009) Journal of the American Medical Informatics Association: JAMIA, 16 (3), pp. 400-403; Harris, P.A., Taylor, R., Thielke, R., Payne, J., Gonzalez, N., Conde, J.G., Research electronic data capture (REDCap) - A metadata driven methodology and workflow process for providing translational research informatics support (2009) Journal of Biomedical Informatics, 42 (2), pp. 377-381; (2011) C83 - CDA Content Modules Component v2.0.1, , http://www.hitsp.org/ConstructSet_Details.aspx?&PrefixAlpha= 4&PrefixNumeric=83, [Accessed 18 March, 2011]; Initial set of standards, implementation specifications, and certification criteria for electronic health record technology (2010) Federal Register, 75 (144), p. 44650. , Health Information Technology; (2011) HL7 DSTU Comments, , http://www.hl7.org/dstucomments/, [Accessed 18 March, 2011]; Huff, S.M., Rocha, R.A., McDonald, C.J., De Moor, G.J.E., Fiers, T., Bidgood Jr., W.D., Forrey, A.W., Baenziger, J., Development of the logical observation identifier names and codes (LOINC) vocabulary (1998) Journal of the American Medical Informatics Association: JAMIA, 5 (3), pp. 276-292; Hyun, S., Shapiro, J.S., Melton, G., Schlegel, C., Stetson, P.D., Johnson, S.B., Bakken, S., Iterative evaluation of the health level 7-Logical observation identifiers names and codes clinical document ontology for representing clinical document names: A case report (2009) Journal of the American Medical Informatics Association: JAMIA, 16 (3), pp. 395-399; Kroenke, K., Spitzer, R.L., Williams, J.B., The PHQ-9: Validity of a brief depression severity measure (2001) Journal of General Internal Medicine, 16 (9), pp. 606-613; (2011) The NLM Personal Health Record (PHR), , http://tinyurl.com/NLMPHROverview, Lister Hill National Center for Biomedical Communications - US National Library of Medicine - National Institutes of Health [Accessed 18 March, 2011]; McDonald, C.J., The barriers to electronic medical record systems and how to overcome them (1997) Journal of the American Medical Informatics Association: JAMIA, 4 (3), pp. 213-221; McDonald, C.J., Huff, S., Mercer, K., Hernandez, J.A., Vreeman, D.J., (2010) Logical Observation Identifiers Names and Codes (LOINC®) User's Guide, , http://loinc.org/downloads/files/LOINCManual.pdf, [Accessed 18 March, 2011]; McDonald, C.J., Huff, S.M., Suico, J.G., Hill, G., Leavelle, D., Aller, R., Forrey, A., Maloney, P., LOINC, a universal standard for identifying laboratory observations: A 5-year update (2003) Clinical Chemistry, 49 (4), pp. 624-633; (2011) Templates, , http://wiki.medical-objects.com.au/index.php/TEMPLATES, [Accessed 18 March, 2011]; (2011) Medical Event Reporting System - Total Health System, , http://www.mers-international.com/mers_usa.html, [Accessed 18 March, 2011]; (2011) DEEDS Publication, , http://www.cdc.gov/ncipc/pub-res/deedspage.htm, National Center for Injury Prevention and Control [Accessed 18 March, 2011]; (2011) Consolidated Health Informatics Standards Adoption Recommendation: Functioning and Disability, , http://www.ncvhs.hhs.gov/061128lt.pdf, [Accessed 18 March, 2011]; (2011) Welcome to the North American Association of Central Cancer Registries, , http://www.naaccr.org/Home.aspx, NAACCR, Inc. [Accessed 18 March, 2011]; (2011) PhenX Home Page, , https://www.phenx.org, [Accessed 18 March, 2011]; Powsner, S., Powsner, D., Cognition, copyright, and the classroom (2005) The American Journal of Psychiatry, 162 (3), pp. 627-628; (2011) PROMIS Home Page, , http://www.nihpromis.org/default.aspx, [Accessed 18 March, 2011]; Smith, P.C., Araya-Guerra, R., Bublitz, C., Parnes, B., Dickenson, L.M., Van Vorst, R., Westfall, J.M., Pace, W.D., Missing clinical information during primary care visits (2005) JAMA the Journal of the American Medical Association, 293 (5), pp. 565-571; (2011) Standards and Certification Criteria Final Rule, , http://tinyurl.com/standardscertfinalrule, US Department of Health and Human Services [Accessed 18 March, 2011]; Vreeman, D.J., Finnell, J.T., Overhage, J.M., A rationale for parsimonious laboratory term mapping by frequency (2007) AMIA Annual Symposium Proceedings/AMIA Symposium, AMIA Symposium, pp. 771-775. , Chicago, IL; Vreeman, D.J., McDonald, C.J., A comparison of intelligent mapper and document similarity scores for mapping local radiology terms to LOINC (2006) AMIA Annual Symposium, Proceedings/AMIA Symposium, AMIA Symposium, pp. 809-813. , Washington DC; Vreeman, D.J., McDonald, C.J., Automated mapping of local radiology terms to LOINC (2005) AMIA Annual Symposium Proceedings/AMIA Symposium, AMIA Symposium, pp. 769-773. , Austin, TX; Vreeman, D.J., McDonald, C.J., Huff, S.M., Representing patient assessments in LOINC® (2010) AMIA Annual Symposium Proceedings/AMIA Symposium, AMIA Symposium, pp. 832-836. , Washington DC; Van Walraven, C., Taljaard, M., Bell, C.M., Etchells, E., Zarnke, K.B., Stiell, I.G., Forster, A.J., Information exchange among physicians caring for the same patient in the community (2008) CMAJ: Canadian Medical Association Journal, 179 (10), pp. 1013-1018; Westra, B.L., Subramanian, A., Hart, C., Matney, S.A., Wilson, P.S., Huff, S.M., Huber, D.L., Delaney, C.W., Achieving 'meaningful use' of electronic health records through the integration of the nursing management minimum data set' (2010) The Journal of Nursing Administration, 40 (7-8), pp. 336-343; (2011) WHO - Patient Monitoring Guidelines for HIV Care and Antiretroviral Therapy, , http://www.who.int/hiv/pub/imai/patientguide/en/, [Accessed 18 March, 2011] RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - In many areas of practice and research, clinical observations are recorded on data collection forms by asking and answering questions, yet without being represented in accepted terminology standards these results cannot be easily shared among clinical care and research systems. LOINC contains a well-developed model for representing variables, answer lists and the collections that contain them. We have successfully added many assessments and other collections of variables to LOINC in this model. By creating a uniform representation and distributing it worldwide at no cost, LOINC aims to lower the barriers to interoperability among systems and make this valuable data available across settings when and where it is needed. Copyright © 2010 Inderscience Enterprises Ltd. ER - TY - JOUR T1 - SANDS: A service-oriented architecture for clinical decision support in a National Health Information Network A1 - Wright, A A1 - Sittig, D F Y1 - 2008/// KW - Administrative data processing KW - Architectural design KW - Architecture KW - Artificial intelligence KW - Clinical decision making KW - Computer communication networks/standards KW - Computer networks KW - Computer-assisted decision support techniques KW - Computerized decision support systems KW - Decision Support Systems, Clinical KW - Decision making KW - Decision support systems KW - Decision theory KW - Drug interactions KW - Health KW - Health risks KW - Hospital information systems KW - Information Services KW - Information services KW - Information systems KW - Information systems/organization & administration/ KW - Information theory KW - Knowledge representation KW - Management information systems KW - Medical Records Systems, Computerized KW - Medical records systems KW - Network architecture KW - Network protocols KW - Problem solving KW - Records management KW - Sand KW - Systems integration KW - United States KW - Web services KW - article KW - clinical decision making KW - computer system KW - decision support system KW - electronic medical record KW - hospital information system KW - medical information system KW - priority journal JF - Journal of Biomedical Informatics VL - 41 IS - 6 SP - 962 EP - 981 DO - 10.1016/j.jbi.2008.03.001 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-55549135012&doi=10.1016%2Fj.jbi.2008.03.001&partnerID=40&md5=cecc7d72e78946636b55a3667ac0e5f4 N1 - Cited By :28 Export Date: 5 April 2018 N2 - In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:. 1.Greater modularity than other architectures, allowing for work to be distributed.2.The potential for creating and sustaining a commercial market for clinical decision support.3.Reduced cost and risk of trying new decision support systems because of its ability to easily integrate a variety of decision support services, and to easily remove them, if desired, as well.4.Significant freedom for developers of clinical decision support systems to choose the way they represent knowledge and internally implement their system, in comparison to other approaches which constrain such developers to a particular knowledge representation formalism.5.Unification of the direction and agenda of decision support research and development with promising near-term efforts to improve interoperability of clinical systems. © 2008 Elsevier Inc. All rights reserved. ER - TY - JOUR T1 - FHIR PIT: an open software application for spatiotemporal integration of clinical data and environmental exposures data A1 - Xu, H A1 - Cox, S A1 - Stillwell, L A1 - Pfaff, E A1 - Champion, J A1 - Ahalt, S C A1 - Fecho, K Y1 - 2020/// JF - BMC medical informatics and decision making VL - 20 IS - 1 SP - 53 EP - 53 DO - 10.1186/s12911-020-1056-9 N2 - BACKGROUND: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease. RESULTS: We have developed an open-source software application-FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)-to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution's clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations. CONCLUSIONS: While FHIR PIT was developed to support our driving use case on asthma, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines. ER - TY - JOUR T1 - Development of an open metadata schema for prospective clinical research (openPCR) in China A1 - Xu, W A1 - Guan, Z A1 - Sun, J A1 - Wang, Z A1 - Geng, Y Y1 - 2014/// KW - Archetype KW - Biomedical Research KW - China KW - Clinical research (CR) KW - Data Collection KW - Database Management Systems KW - Datasets as Topic KW - Dublin Core Metadata Element Set (DC Metadata Elem KW - Electronic Health Records KW - Electronic health record (EHR) KW - Humans KW - Information Storage and Retrieval KW - Metadata KW - Prospective Studies KW - data base KW - electronic medical record KW - human KW - information processing KW - information retrieval KW - medical research KW - organization and management KW - procedures KW - prospective study JF - Methods of Information in Medicine VL - 53 IS - 1 SP - 39 EP - 46 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892410079&doi=10.3414%2FME13-01-0008&partnerID=40&md5=89fa316071aa840c06b2239af3d23fb7 N1 - Cited By :2 Export Date: 10 September 2018 References: Kohl, C.D., Garde, S., Knaup, P., Facilitating secondary use of medical data by using openEHR archetypes (2010) Stud Health Technol Inform, 160 (PART 2), pp. 1117-1121; Xu, W., Li, T., Wu, C., Current situation on the reporting quality of randomized controlled trials in 5 leading Chinese medical journals Original Research Article (2009) Journal of Medical Colleges of PLA, 24 (2), pp. 105-111; Babre, D., Electronic data capture-Narrowing the gap between clinical and data management (2011) Perspect Clin Res, 2 (1), pp. 1-3; (2006) The Future Vsion of Electronic Health Records as eSource for Clinical Research., , http://www.esi-bethesda.com/ncrrworkshops/clinicalresearch/pdf/catherineceligrantpaper.pdf, The eClinical Forum and PhRMAEDC Task Group. (Homepage on the Internet). (Updated May 3, 2006; cited Sept 20, 2009). Available from; (2007) EHR/CR Functional Profile. Informative Level Ballot Release 1., , http://www.ehrcr.org/Docs/EHR-CR_Functional_Profile.pdf, EHR/CR Functional Profile Working Group. (Updated Aug 2007; cited Sept 20, 2009). Available from; Ohmann, C., Kuchinke, W., Future developments of medical informatics from the viewpoint of networked clinical research. Interoperability and integration (2009) Methods Inf Med, 48 (1), pp. 45-54; Knaup, P., Garde, S., Merzweiler, A., Towards shared patient records: An architecture for using routine data for nationwide research (2006) Int J Med Inform, 75 (3-4), pp. 191-200; Chen, R., Enberg, G., Klein, G.O., Julius-a template based supplementary electronic health record system (2007) BMC Med Inform Decis Mak, 7, p. 10; Matsumura, Y., Kuwata, S., Yamamoto, Y., Template-based data entry for general description in medical records and data transfer to data warehouse for analysis (2007) Stud Health Technol Inform, 129 (PART 1), pp. 412-416; Jianming, L., Brief analysis the difference on the good clinical practice in ICH and China (2010) Chin J Clin Pharmacol, 26 (9), pp. 707-710; Drug Clinical Trial and the Quality Control Standard of China., , http://www.sfda.gov.cn/WS01/CL0053/24473.html, (Cited Nov 20, 2012). Avail-able from; Evans, T., Gülmezoglu, M., Pang, T., Registering clinical trials: An essential role for WHO (2004) Lancet, 363 (9419), pp. 1413-1414; Liu, X., Li, Y., Wu, T., Liu, G., Li, J., A Survey of the Status of Funding of Registered Chinese Clinical Trials Survey of registration of funded clinical trial in China (2008) Chinese Journal of Evidence-Based Medicine, 8 (5), pp. 305-311; (2013) Notification of using the web based electronic Clinical Research Manager., , http://f1.clinicaltrialecrf.org/doc/2012/9/4/16450816900265829955.pdf, (April 12). Available from; Kirklin, J.W., Vicinanza, S.S., Metadata and computerbased patient records (1999) Ann Thorac Surg, 68 (3 SUPPL.), pp. S23-S24; Brandt, C.A., Morse, R., Matthews, K., Metadatadriven creation of data marts from an EAV-modeled clinical research database (2002) Int J Med Inform, 65 (3), pp. 225-241; (2006) ISO 23081-1 Information and documentation-Records management processes-Metadata for records-Part 1: Principles, , [S] Geneva: ISO copyright office; Beale, T., Heard, S., (2008) Architecture Overview., , http://www.openehr.org/releases/1.0.2/architecture/overview.pdf, openEHR Architecture: (Updated Nov 13, 2008; cited Sept 20, 2009). Available from; Beale, T., (2002) Archetypes: Constraint-based Domain Models for Future-proof Information Systems., , http://www.openehr.org/publications/archetypes/archetypes_beale_oopsla_2002.pdf, (Updated 2002; cited May 5, 2011.) Available from; Garde, S., Knaup, P., Schuler, T., Hovenga, E., Can openEHR Archetypes Empower Multi-Centre Clinical Research? (2005) Stud Health Technol Inform, 116, pp. 971-976; Coyle, K., Baker, T., (1995) Guidelines for Dublin Core Application Profiles., , http://dublincore.org/documents/2009/05/18/profile-guidelines/, (Updated May 18, 2009; cited Sept. 20, 2009.) Available from; (2005) Ottawa Statement on Trial Registration., , http://ottawagroup.ohri.ca/index.html, (April 12, 2013.) Available from; (2006) Information and documentation-Managing metadata for records-Part 2: Conceptual and implementation issues, , ISO 23081-2: [S] Geneva: ISO copyright office; Beale, T., Heard, S., Kalra, D., Lloyd, D., (2007) The openEHR Reference Model: Support Information Model., , http://www.openehr.org/releases/1.0.2/architecture/rm/support_im.pdf, (Updated April 8, 2007; cited Aug 9, 2012.) Available from; Tu, S.W., Carini, S., Rector, A., OCRe: An On-tology of Clinical Research., , http://protege.stanford.edu/conference/2009/abstracts/S8P2Tu.pdf, (Cited July 9, 2013.) Available from; Hassanzadeh, O., Kementsietsidis, A., Lim, L., Miller, R.J., Wang, M., LinkedCT: A Linked Data Space for Clinical Trials, , (Cited July 9, 2013.) Available from ftp://ftp.cs.toronto.edu/pub/reports/csri/596/ LinkedCT.pdf; http://www.openehr.org/ckm/; Diane, H., (2005) Using Dublin Core., , http://www.dublincore.org/documents/usageguide/, (Updated Nov 7, 2005; cited Aug 9, 2012.) Available from; Darmoni, S.J., Thirion, B.J., Leroy, P., The use of Dublin Core metadata in a structured health resource guide on the Internet (2001) Bull Med Libr Assoc, 89 (3), pp. 297-301; Robertson, W.D., Leadem, E.M., Dube, J., (2005) Design and implementation of the National Institute of Environmental Health Sciences Dublin Core Metadata Schema., , http://dcpapers.dublincore.org/pubs/article/view/658/654, (Updated Oct 2001; cited Aug 9, 2012.) Available from; A Framework of Guidance for Building Good Digital Collections., , http://framework.niso.org/node/5, NISO: (Cited April 12, 2013). Available from RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Objectives: In China, deployment of electronic data capture (EDC) and clinical data management system (CDMS) for clinical research (CR) is in its very early stage, and about 90% of clinical studies collected and submitted clinical data manually. This work aims to build an open metadata schema for Prospective Clinical Research (openPCR) in China based on openEHR archetypes, in order to help Chinese researchers easily create specific data entry templates for registration, study design and clinical data collection. Methods: Singapore Framework for Dublin Core Application Profiles (DCAP) is used to develop openPCR and four steps such as defining the core functional requirements and deducing the core metadata items, developing archetype models, defining metadata terms and creating archetype records, and finally developing implementation syntax are followed. Results: The core functional requirements are divided into three categories: requirements for research registration, requirements for trial design, and requirements for case report form (CRF). 74 metadata items are identified and their Chinese authority names are created. The minimum metadata set of openPCR includes 3 documents, 6 sections, 26 top level data groups, 32 lower data groups and 74 data elements. The top level container in openPCR is composed of public document, internal document and clinical document archetypes. A hierarchical structure of openPCR is established according to Data Structure of Electronic Health Record Architecture and Data Stand - ard of China (Chinese EHR Standard). Metadata attributes are grouped into six parts: identification, definition, representation, relation, usage guides, and administration. Discussions and Conclusion: OpenPCR is an open metadata schema based on research registration standards, standards of the Clinical Data Interchange Standards Consortium (CDISC) and Chinese healthcare related stand - ards, and is to be publicly available throughout China. It considers future integration of EHR and CR by adopting data structure and data terms in Chinese EHR Standard. Archetypes in openPCR are modularity models and can be separated, recombined, and reused. The authors recommend that the method to develop openPCR can be referenced by other countries when designing metadata schema of clinical research. In the next steps, openPCR should be used in a number of CR projects to test its applicability and to continuously improve its coverage. Besides, metadata schema for research protocol can be developed to structurize and standardize protocol, and syntactical interoperability of openPCR with other related standards can be considered. © Schattauer 2014. ER - TY - JOUR T1 - Medshare: A Novel Hybrid Cloud for Medical Resource Sharing among Autonomous Healthcare Providers A1 - Yang, Y A1 - Li, X A1 - Qamar, N A1 - Liu, P A1 - Ke, W A1 - Shen, B A1 - Liu, Z Y1 - 2018/// JF - IEEE Access VL - 6 SP - 46949 EP - 46961 DO - 10.1109/ACCESS.2018.2865535 N2 - ©2013 IEEE. Legacy electronic health record systems were not developed with the level of connectivity expected from them nowadays. Therefore, interoperability weakness inherent in the legacy systems can result in poor patient care and waste of financial resources. Simultaneously, healthcare providers are not yet ready to dispose of them. Large hospitals are also less likely to share their data with external care providers due to economic and political reasons. To overcome the barriers in the effective medical data exchange process, we present a novel hybrid cloud called MedShare, dealing with interoperability issues among disconnected but autonomously functioning healthcare providers. The proposed system architecture and its implementation is based upon: 1) custom data extractors to extract legacy medical data from the three hemodialysis centers under consideration; 2) negotiated and converted to a common data model in each of the private cloud of a provider; 3) indexed patient information using the HashMap technique into the public cloud that operates on private clouds, called a hybrid cloud; and 4) a set of services and tools installed as a coherent environment to exchange information smoothly. This paper enables healthcare professionals to appropriately access and securely share a patient's medical information. MedShare allows the healthcare providers and administrators to maintain the control of their patient data, which is always the primary concern in building a trustworthy environment for exchanging patient information. Medshare effectively addresses primary security and privacy concerns surrounding the deployment of data exchange process by including patient consent and a two-way authorization process. ER - TY - CONF T1 - Integrating data using open standards A1 - Young, D Y1 - 2019/// JF - 91st Annual Water Environment Federation Technical Exhibition and Conference, WEFTEC 2018 SP - 3218 EP - 3221 SN - 9781510877474 N2 - Copyright ©2018 Water Environment Federation Water managers and the public need data to make decisions. From decisions about the health of a given waterbody or whether or not it's safe to recreate in a stream. Many different entities are collecting data to answer these questions, but those data collection efforts are either not coordinated or the data collected cannot be easily put together to tell a cohesive story. Several efforts have been undertaken to better integrate water data, from leveraging data standards and ontologies to tying data to common hydrography to allow discoverability. This paper provides a high-level overview of some components to water data interoperability and discoverability and efforts that EPA has taken in partnership with other federal agencies, states, and tribes. ER - TY - JOUR T1 - An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies A1 - Yuksel, M A1 - Gonul, S A1 - Laleci Erturkmen, G B A1 - Sinaci, A A A1 - Invernizzi, P A1 - Facchinetti, S A1 - Migliavacca, A A1 - Bergvall, T A1 - Depraetere, K A1 - De Roo, J Y1 - 2016/// KW - Delivery of Health Care KW - Electronic Health Records KW - Humans KW - Patient Safety KW - Pharmacovigilance KW - case study KW - clinical research KW - clinical trial KW - data base KW - drug surveillance program KW - electronic health record KW - health care delivery KW - human KW - information model KW - major clinical study KW - mediator KW - nomenclature KW - patient safety KW - safety KW - scientist KW - signal detection KW - statistics and numerical data JF - BioMed Research International VL - 2016 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84971386816&doi=10.1155%2F2016%2F6741418&partnerID=40&md5=74efb10c41ec620c4f897416531e122e L1 - file:///C:/Users/fernanda.dorea/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/Yuksel et al. - 2016 - An Interoperability Platform Enabling Reuse of Electronic Health Records for Signal Verification Studies.pdf N1 - Cited By :1 Export Date: 10 September 2018 References: (2015) AstraZeneca Abandons Blood Thinner, Citing Risk Exanta Dropped because of Risks, , http://articles.philly.com/2006-02-15/business/254085841exantairessa-crestor, Philadelphia Inquirer June; Hazell, L., Shakir, S.A.W., Under-reporting of adverse drug reactions: A systematic review (2006) Drug Safety, 29 (5), pp. 385-396; Heijden Der Van, P.G.M., Van Puijenbroek, E.P., Van Buuren, S., Hofstede Der Van, J.W., On the assessment of adverse drug reactions from spontaneous reporting systems: The influence of under-reporting on odds ratios (2002) Statistics in Medicine, 21 (14), pp. 2027-2044; Bates, D.W., Evans, R.S., Murff, H., Stetson, P.D., Pizzifferri, L., Hripcsak, G., Detecting adverse events using information technology (2003) Journal of the American Medical Informatics Association, 10 (2), pp. 115-128; Cullen, D.J., Bates, D.W., Small, S.D., Cooper, J.B., Nemeskal, A.R., Leape, L.L., The incident reporting systemdoes not detect adverse drug events: A problem for quality improvement (1995) The Joint Commission Journal on Quality Improvement, 21 (10), pp. 541-548; Lindquist, M., Data quality management in pharmacovigilance (2004) Drug Safety, 27 (12), pp. 857-870; AHRQ Patient Safety Network, Voluntary Patient Safety Event Reporting (Incident Reporting), , http://www.psnet.ahrq.gov/primer.aspx?primerID=13; Norén, G.N., Edwards, I.R., Opportunities and challenges of adverse drug reaction surveillance in electronic patient records (2010) PharmacoVigilance Review, 4 (1), pp. 17-20; Norén, G.N., Edwards, I.R., Modern methods of pharmacovigilance: Detecting adverse effects of drugs (2009) Clinical Medicine, Journal of the Royal College of Physicians of London, 9 (5), pp. 486-489; Norén, G.N., Hopstadius, J., Bate, A., Star, K., Edwards, I.R., Temporal pattern discovery in longitudinal electronic patient records (2010) Data Mining and Knowledge Discovery, 20 (3), pp. 361-387; (2015) SALUS: Scalable, Standard Based Interoperability Framework for Sustainable Proactive PostMarket Safety Studies, , http://www.salusproject.eu/, June; Turisco, F., Keogh, D., Stubbs, C., Glaser, J., Crowley, W.F., Jr., Current status of integrating information technologies into the clinical research enterprise within US academic health centers: Strategic value and opportunities for investment (2005) Journal of Investigative Medicine, 53 (8), pp. 425-433; Powell, J., Buchan, I., Electronic health records should support clinical research (2005) Journal of Medical Internet Research, 7; West, S.L., Blake, C., Liu, Z., McKoy, J.N., Oertel, M.D., Carey, T.S., Reflections on the use of electronic health record data for clinical research (2009) Health Informatics Journal, 15 (2), pp. 108-121; Ohmann, C., Kuchinke, W., Future developments of medical informatics from the viewpoint of networked clinical research. Interoperability and integration (2009) Methods of Information in Medicine, 48 (1), pp. 45-54; Prokosch, H.-U., Ganslandt, T., Perspectives for medical informatics. Reusing the electronic medical record for clinical research (2009) Methods of Information InMedicine, 48 (1), pp. 38-44; Breil, B., Semjonow, A., Dugas, M., HIS-based electronic documentation can significantly reduce the time from biopsy to final report for prostate tumours and supports quality management as well as clinical research (2009) BMC Medical Informatics and Decision Making, 9; Kush, R., Alschuler, L., Ruggeri, R., Implementing Single Source: The STARBRITE proof-of-concept study (2007) Journal of the American Medical Informatics Association, 14 (5), pp. 662-673; Murphy, E.C., Ferris, F.L., III, O'Donnell, W.R., An electronic medical records system for clinical research and the EMR-EDC interface (2007) Investigative Ophthalmology and Visual Science, 48 (10), pp. 4383-4389; El Fadly, A., Daniel, C., Bousquet, C., Dart, T., Lastic, P.-Y., Degoulet, P., Electronic healthcare record and clinical research in cardiovascular radiology. HL7 CDA and CDISC ODM interoperability (2007) AMIA Annual Symposium Proceedings, 2007, pp. 216-220; El Fadly, A., Rance, B., Lucas, N., Integrating clinical research with the Healthcare Enterprise: From the RE-USE project to the EHR4CR platform (2011) Journal of Biomedical Informatics, 44, pp. S94-S102; Murphy, S.N., Weber, G., Mendis, M., Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2) (2010) Journal of TheAmericanMedical Informatics Association, 17 (2), pp. 124-130; Reference InformationModel (RIM), , http://www.hl7.org/implement/standards/rim.cfm; (2008) ISO/CEN. en 13606-1, Health Informatics-Electronic Health Record Communication-Part 1: Reference Model; (2015) Operational Data Model (ODM), , http://www.cdisc.org/odm, June; Fridsma, D.B., Evans, J., Hastak, S., Mead, C.N., TheBRIDG Project: A technical report (2008) Journal of the American Medical Informatics Association, 15 (2), pp. 130-137; (2015) Observational Medical Outcomes Partnership (OMOP), , http://omop.org/, June; FDA. Sentinel Initiative-Mini-Sentinel, , http://mini-sentinel.org/; Lowe, H.J., Ferris, T.A., Hernandez, P.M., Weber, S.C., STRIDE-an integrated standards-based translational research informatics platform (2009) AMIA Annual Symposium Proceedings, 2009, pp. 391-395; Avillach, P., Dufour, J.-C., Diallo, G., Design and validation of an automated method to detect known adverse drug reactions in MEDLINE: A contribution from the EU-ADR project (2013) Journal of TheAmericanMedical InformaticsAssociation, 20 (3), pp. 446-452; Weber, G.M., Murphy, S.N., McMurry, A.J., The shared health research information network (SHRINE): A prototype federated query tool for clinical data repositories (2009) Journal of the American Medical Informatics Association, 16 (5), pp. 624-630; Rea, S., Pathak, J., Savova, G., Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: The SHARPn project (2012) Journal of Biomedical Informatics, 45 (4), pp. 763-771; Profiles, , http://www.ihe.net/profiles/; (2015) ASTM International, Continuity of Care Document (CCD) Release 1, , http://wiki.hl7.org/index.php?title=ProductCCD, June; http://www.ihe.net/TechnicalFramework/upload/IHEQRPHTFSupplementDrugSafetyContentDSCTI2009-08-10.pdf, Drug Safety Content Profile (DSC); (2015) Clinical ResearchDataCapture Profile (CRD), , http://wiki.ihe.net/index.php?title=ClinicalResearchDataCapture-(CRD), June; (2015) Clinical Data Acquisition Standards Harmonization (CDASH), , http://www.cdisc.org/cdash, June; (2001) Electronic Transmission of Individual Case Safety Reports Message Specification-E2B(R2), , International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals For Human Use (ICH); Dogac, A., Laleci, G.B., Kirbas, S., Artemis: Deploying semantically enriched web services in the healthcare domain (2006) Information Systems, 31 (4-5), pp. 321-339; Martin, L., Anguita, A., Graf, N., ACGT: Advancing clinico-genomic trials on cancer-four years of experience (2011) User Centred Networked Health Care Vol. 169 of Studies in Health Technology and Informatics, pp. 734-738. , IOS Press, Amsterdam, The Netherlands; Schober, D., Boeker, M., Bullenkamp, J., The DebugIT core ontology: Semantic integration of antibiotics resistance patterns (2010) Studies in Health Technology and Informatics, 160, pp. 1060-1064; Ouagne, D., Nadah, N., Schober, D., Ensuring HL7-based information model requirements within an ontology framework (2010) Studies in Health Technology and Informatics, 160, pp. 912-916; Lezcano, L., Sicilia, M.-A., Rodríguez-Solano, C., Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules (2011) Journal of Biomedical Informatics, 44 (2), pp. 343-353; (2015), http://www.epsos.eu/, Smart Open Services for European Patients (epSOS), June; Bodenreider, O., The unified medical language system (umls): Integrating biomedical terminology (2004) Nucleic Acids Research, 32, pp. D267-D270; (2015), https://wiki.nci.nih.gov/display/LexEVS/LexEVS, June; Laleci, G.B., Dogac, A., Yuksel, M., Personalized remote monitoring of the atrial fibrillation patients with electronic implant devices (2011) Journal of Healthcare Engineering, 2 (2), pp. 183-196; Patel, C., Gomadam, K., Khan, S., Garg, V., TrialX: Using semantic technologies to match patients to relevant clinical trials based on their personal health records (2010) Web Semantics: Science, Services and Agents on the World Wide Web, 8 (4), pp. 342-347; Patel, C., Cimino, J., Dolby, J., Matching patient records to clinical trials using ontologies (2007) The Semantic Web: 6th International Semantic Web Conference, pp. 816-829. , 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007. Proceedings vol. 4825 of Lecture Notes in Computer Science, Springer, Berlin, Germany; Rector, A.L., Qamar, R., Marley, T., Binding ontologies and coding systems to electronic health records and messages (2009) Applied Ontology-Biomedical Ontology in Action, 4 (1), pp. 51-69; Laleci, G.B., Yuksel, M., Dogac, A., Providing semantic interoperability between clinical care and clinical research domains (2013) IEEE Journal of Biomedical and Health Informatics, 17 (2), pp. 356-369; Ethier, J.F., Dameron, O., Curcin, V., A unified structural/ terminological interoperability framework based on Lex-EVS: Application to TRANSFoRm (2013) Journal of the American Medical Informatics Association, 20 (5), pp. 986-994; Yuksel, M., (2013) A Semantic Interoperability Framework for Reinforcing Post Market Safety Studies, , [Ph. D. Thesis in Computer Engineering], Middle East Technical University, Ankara, Turkey; (2015) Patient Care Coordination (PCC) CDA ContentModules, , http://www.ihe.net/TechnicalFramework/upload/IHEPCCSupplCDAContentModules.pdf, June; (2015) Resource Description Framework (RDF): Primer, , http://www.w3.org/TR/rdf-primer/, W3C, June; EpSOS: SmartOpen Services for European Patients, , http://www.epsos.eu/; (2015) Query for Existing Data Profile (QED), , http://www.ihe.net/TechnicalFramework/upload/IHEPCCQueryforExistingDataQEDSupplementTI2008-08-22.pdf, June; SALUS Deliverable 5. 2. 2, Query Based Interoperability Profiles and Open Source Toolsets-R2, , http://www.srdc.com.tr/projects/salus/docs/D5.2.2.pdf; (2015), http://www.hl7.org/implement/standards/productbrief.cfm?productid=97, Health Quality Measures Format (HQMF), June; (2015), https://github.com/srdc/ontmalizer, June; Clinical Document Architecture (CDA), Release 2, , http://www.hl7.org/implement/standards/cda.cfm; Berners-Lee, T., Connolly, D., (2015) Notation3 (N3): A Readable RDF Syntax, , http://www.w3.org/Team-Submission/n3/, June; (2015), http://www.w3.org/TR/rdf-sparql-query/, W3C, SPARQL Query Language for RDF, June; http://www.hitsp.org/ConstructSetDetails.aspx?&PrefixAlpha=4&PrefixNumeric=32, HITSP. C 32, HITSP Summary Documents Using HL7 Continuity of Care Document (CCD) Component; (2015) C 83-CDA ContentModules Component, , http://www.hitsp.org/ConstructSetDetails.aspx?&PrefixAlpha=4&PrefixNumeric=83, June; (2015), http://wiki.hl7.org/images/b/be/CDAConsolidationR12011.zip, Implementation Guide for CDA Release 2. 0-Consolidated CDA Templates (US Realm), June; (2015), http://75.101.131.161/download/loadfile.php?docname=CDM%20Specification%20V4.0, OMOP, Common Data Model (CDM) Specifications, June; Sinaci, A.A., Laleci, G.B., A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains (2013) Journal of Biomedical Informatics, 46 (5), pp. 784-794; (2011) Health Informatics, Harmonized Data Types for Information Interchange (21090), ISO Std; (2015) SALUS CIM Ontology, , http://www.salusproject.eu/ontology/salusCIMv2.n3, June; (2015), http://eulersharp.sourceforge.net/, Euler Yet another proof Engine (EYE), June; Sun, H., Depraetere, K., De Roo, J., De Vloed, B., Mels, G., Colaert, D., Semantic Integration and Analysis of Clinicaldata, , http://arxiv.org/abs/1210.4405; Declerck, G., Bousquet, C., Jaulent, M.-C., Automatic generation of MedDRA terms groupings using an ontology (2012) Quality of Life Through Quality of Information Vol. 180 of Studies in Health Technology and Informatics, pp. 73-77; SKOS: Simple Knowledge Organization System, , http://www.w3.org/2004/02/skos/, W3C; Connect Distributed Data Across the Web, , http://linkeddata.org/, Linked Data; Whetzel, P.L., Noy, N.F., Shah, N.H., BioPortal: Enhanced functionality via newWeb services from theNational Center for Biomedical Ontology to access and use ontologies in software applications (2011) Nucleic Acids Research, 39 (2), pp. W541-W545; (2015), http://ihtsdo.org/news/news-article/article/ihtsdowho-snomed-ct-to-icd-10-cross-map-technology-previewrelease/, IHTSDO/WHO SNOMED CT to ICD-10 Cross-Map Project, June; Sun, H., De Roo, J., Twagirumukiza, M., Validation Rules for Assessing Andimproving SKOS Mapping Quality, , http://arxiv.org/abs/1310.4156; (2015) D7. 2. 2 Validation Report for SALUS Pilot Application, , http://salusproject.eu/docs/D7.2.2PilotApplicationValidationv2.0FINAL.pdf, SALUS, June; (2015), http://www.cdc.gov/ehrmeaningfuluse/introduction.html, Meaningful Use, June; (2015) IT Infrastructure Technical Framework, , http://www.ihe.net/TechnicalFramework/upload/IHEITITFVol1.pdf, June; Dogac, A., Yuksel, M., Avcl, A., Electronic health record interoperability as realized in the Turkish health information system (2011) Methods of Information in Medicine, 50 (2), pp. 140-149; (2015) EpSOS: Point OfCareDatabase, , http://www.epsos.eu/point-of-care-database/poc-database.html, June; (2015) Virtuoso Universal Server, , http://virtuoso.openlinksw.com/, June; (2015) D2. 2. 4 Guidance to Green Field Member States for Secondary Use of EHRs for Post Market Safety Studies, , http://salusproject.eu/docs/D2.2.4.pdf, SALUS, June; (2015) SALUS Starter-kit, , http://www.salusproject.eu/resources/salus-project.zip, June RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Depending mostly on voluntarily sent spontaneous reports, pharmacovigilance studies are hampered by low quantity and quality of patient data. Our objective is to improve postmarket safety studies by enabling safety analysts to seamlessly access a wide range of EHR sources for collecting deidentified medical data sets of selected patient populations and tracing the reported incidents back to original EHRs. We have developed an ontological framework where EHR sources and target clinical research systems can continue using their own local data models, interfaces, and terminology systems, while structural interoperability and Semantic Interoperability are handled through rule-based reasoning on formal representations of different models and terminology systems maintained in the SALUS Semantic Resource Set. SALUS Common Information Model at the core of this set acts as the common mediator. We demonstrate the capabilities of our framework through one of the SALUS safety analysis tools, namely, the Case Series Characterization Tool, which have been deployed on top of regional EHR Data Warehouse of the Lombardy Region containing about 1 billion records from 16 million patients and validated by several pharmacovigilance researchers with real-life cases. The results confirm significant improvements in signal detection and evaluation compared to traditional methods with the missing background information. © 2016 Mustafa Yuksel et al. ER - TY - JOUR T1 - Community-driven standards-based electronic laboratory data-sharing networks A1 - Zarcone, P A1 - Nordenberg, D A1 - Meigs, M A1 - Merrick, U A1 - Jernigan, D A1 - Hinrichs, S H Y1 - 2010/// KW - Centers for Disease Control and Prevention (U.S.) KW - Clinical Laboratory Information Systems KW - Computer Communication Networks KW - Disaster Planning KW - Humans KW - Information Dissemination KW - Population Surveillance KW - United States KW - United States Public Health Service KW - article KW - community care KW - computer network KW - data collection method KW - disaster planning KW - electronic data interchange KW - health care management KW - health care planning KW - health program KW - health survey KW - hospital information system KW - human KW - information processing KW - information technology KW - laboratory KW - medical informatics KW - organization and management KW - pandemic influenza KW - priority journal KW - professional standard KW - public health service KW - public-private partnership KW - review KW - standard KW - validation process JF - Public Health Reports VL - 125 SP - 47 EP - 56 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-77953951772&partnerID=40&md5=f8759de62dc798301430f7194b6dc4a3 N1 - Cited By :6 Export Date: 10 September 2018 References: (2007) 2007 State of Technology Adoption Survey, , Association of Public Health Laboratories. Silver Spring (MD): APHL; Bean, N.H., Martin, S.M., Bradford Jr., H., PHLIS: An electronic system for reporting public health data from remote sites (1992) Am J Public Health, 82, pp. 1273-1276; Wendel, A.M., Johnson, D.H., Sharapov, U., Grant, J., Archer, J.R., Monson, T., Multistate outbreak of Escherichia coli O157:H7 infection associated with consumption of packaged spinach, August-September 2006: The Wisconsin investigation (2009) Clin Infect Dis, 48, pp. 1079-1086; Effler, P., Ching-Lee, M., Bogard, A., Ieong, M.C., Nekomoto, T., Jernigan, D., Statewide system of electronic notifiable disease reporting from clinical laboratories: Comparing automated reporting with conventional methods (1999) JAMA, 282, pp. 1845-1850; Overhage, J.M., Suico, J., McDonald, C.J., Electronic laboratory reporting: Barriers, solutions and findings (2001) J Public Health Manag Pract, 7, pp. 60-66; Chute, C.G., Koo, D., Public health, data standards, and vocabulary: Crucial infrastructure for reliable public health surveillance (2002) J Public Health Manag Pract, 8, pp. 11-17; Moore, K.M., Reddy, V., Kapell, D., Balter, S., Impact of electronic laboratory reporting on hepatitis A surveillance in New York City (2008) J Public Health Manag Pract, 14, pp. 437-441; Overhage, J.M., Grannis, S., McDonald, C.J., A comparison of the completeness and timeliness of automated electronic laboratory reporting and spontaneous reporting of notifiable conditions (2008) American Journal of Public Health, 98 (2), pp. 344-350. , http://www.ajph.org/cgi/reprint/98/2/344, DOI 10.2105/AJPH.2006.092700; 3 C.F.R. § 13335 (2005); Ebeler, J.C., Bruno, M., Schmitt, T., (2007) Opportunities for Coordination and Clarity to Advance the National Health Information Agenda: A Brief Assessment of the Office of the National Coordinator for Health Information Technology - A Letter Report, , Institute of Medicine. Washington: The National Academies Press; (2009) American Recovery and Reinvestment Act of 2009, , Pub. L. No. 111-5; (2003) Requirements for Public Health Laboratory Information Management Systems: A Collaboration of State Public Health Laboratories, the Association of Public Health Laboratories and the Public Health Informatics Institute, , Association of Public Health Laboratories, Public Health Informatics Institute. Washington: APHL RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Public health laboratories (PHLs) are critical components of the nation's healthcare system, serving as stewards of valuable specimens, delivering important diagnostic results to support clinical and public health programs, supporting public health policy, and conducting research. This article discusses the need for and challenges of creating standards-based data-sharing networks across the PHL community, which led to the development of the PHL Interoperability Project (PHLIP). Launched by the Association of Public Health Laboratories and the Centers for Disease Control and Prevention in September 2006, PHLIP has leveraged a unique community-based collaborative process, catalyzing national capabilities to more effectively share electronic laboratory-generated diagnostic information and bolster the nation's health security. PHLIP is emerging as a model of accelerated innovation for the fields of laboratory science, technology, and public health. ©2010 Association of Schools of Public Health. ER - TY - CONF T1 - E-ID meets e-health on a pan-European level A1 - Zwattendorfer, B A1 - Zefferer, T A1 - Tauber, A Y1 - 2011/// KW - Computer science KW - Data privacy KW - Ehealth KW - Electronic identity KW - Government data processing KW - Health care KW - Identification (control systems) KW - Information systems KW - STORK KW - eHealth KW - eID KW - epSOS SP - 97 EP - 104 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84865087612&partnerID=40&md5=9e2bd597145301bd58ab085e218cf063 N1 - Cited By :1 Export Date: 10 September 2018 References: Ivkovic, M., Leitold, H., Rössler, T., Interoperable elektronische Identität in Europa (2009) Information Security Konferenz, 7, pp. 175-190. , Krems, Austria; Leitold, H., Zwattendorfer, B., STORK: Architecture, implementation and pilots (2010) ISSE 2010 Securing Electronic Business Processes: Highlights of the Information Security Solutions Europe 2010 Conference, pp. 131-142. , Berlin Germany. Deliverable; Alcalde-Moraño, J., (2010) D5.8.3b Interface Specification, , STORK consortium; Heider, G., (2010) D3.6.2 Final Identity Management Specification Definition, , epSOS consortium; Kolitsi, Z., Wilson, P., (2010) D2.1.2 Legal and Regulatory Constraints on EpSOS Design-Participating Member States, , epSOS consortium Journal; Siddhartha, A., National e-ID card schemes: A European overview (2008) Information Security Technical Report, 13, pp. 46-53. , Report; Campari, C., (2010) Report on Common Specifications for EHealth LSP, , STORK consortium Specification; Cantor, S., (2005) Assertions and Protocols for the OASIS Security Assertion Markup Language (SAML) V2.0, , OASIS Standard; Hughes, J., (2005) Profiles for the OASIS Security Assertion Markup Language (SAML) V2.0, , OASIS Standard; Pope, N., Carlos Cruellas, J., (2007) Digital Signature Service Core Protocols, Elements, and Bindings Version 1.0, , OASIS Standard Web Page; (2010) EpSOS - European Patients Smart Open Services, , http://www.epsos.eu/about-epsos.html RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - Information and communication technologies are more and more becoming an inherent part of our life. This is particularly manifested in the fields of electronic government and electronic health care. Identification, authentication, and data privacy protection are the key elements to ensure both secure and reliable transactions and trust in the applied technologies. So far, European governments and public administrations have rolled out eID (electronic identity) solutions and put in place proper eHealth infrastructures that are tailored to national needs. Globalization and the opening of the EU internal market have raised the demand for interoperable solutions across national borders in order to allow citizens to use own eGovernment and eHealth infrastructures also abroad. For this reason, the European Commission has started several initiatives with the aim to establish interoperability between different national solutions. The large scale pilot STORK strives for the goal to enable mutual recognition of electronic IDs between EU Member States. Another large scale pilot called epSOS provides a pan-European framework for the secure and reliable exchange of patient health data. In this paper we review and compare both large scale pilots from several perspectives. We further investigate how synergies between both pilots can be exploited so that epSOS can reap the benefits of STORK to replace paper-based identification procedures with a fully-fledged electronic one. © 2011 IADIS. ER - TY - ICOMM T1 - Statistical Data and Metadata Exchange - Health Domain (SDMX-HD) - Global Inventory of Statistical Standards UR - https://unstats.un.org/unsd/iiss/Statistical-Data-and-Metadata-Exchange-Health-Domain-SDMX-HD.ashx ER - TY - JOUR T1 - BUILDING A ROADMAP FOR HEALTH INFORMATION SYSTEMS INTEROPERABILITY FOR PUBLIC HEALTH ( Public Health Uses of Electronic Health Record Data ) WHITE PAPER Y1 - 2007/// KW - European Continental Ancestry Group KW - Information Systems SP - 1 EP - 52 N1 - RAYYAN-INCLUSION: {"Fernanda"=>true} ER - TY - GEN T1 - Definition of Interoperability Y1 - 2010/// JF - HIMSS Dictionary of Healthcare Information Technology Terms, Acronyms and Organizations ET - 2nd editio SP - 190 EP - 190 ER - TY - BOOK T1 - Studies in Health Technology and Informatics Y1 - 2019/// JF - Studies in Health Technology and Informatics VL - 258 SN - 9781614999584 N2 - The proceedings contain 64 papers. The topics discussed include: raising the impact of real world evidence; how to harness big data for the benefit of patients; towards interoperability in clinical research: enabling FHIR on the Open source research platform XNAT; towards a software tool for planning IHE-compliant information systems; query translation between openEHR and i2b2; an extension of the i2b2 data warehouse to support REDCap dynamic data pull; a REST service for the visualization of clinical time series data in the context of clinical decision support; an ontological framework to improve surveillance of adverse childhood experiences (ACEs); and complementing medical records with precalculated data items to facilitate decision support and phenotyping. ER - TY - JOUR T1 - Patient safety and health information technology Y1 - 2015/// KW - Article KW - Humans KW - Medical Informatics KW - Patient Safety KW - Systems Integration KW - disease surveillance KW - health care quality KW - human KW - medical informatics KW - patient safety KW - priority journal KW - standards KW - system analysis JF - Obstetrics and Gynecology VL - 125 IS - 1 SP - 282 EP - 283 UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925031795&partnerID=40&md5=d2c6041fc9cd8537fd01454005ec1b2e N1 - Cited By :2 Export Date: 10 September 2018 References: (2012) Health IT and Patient Safety: Building Safer Systems for Better Care, , Institute of Medicine. Washington, DC: The National Academies Press; Classen, D., Bates, D.W., Denham, C.R., Meaningful use of computerized prescriber order entry (2010) J Patient Saf, 6, pp. 15-23. , PubMed; Brokel, J.M., Harrison, M.I., Redesigning care processes using an electronic health record: A system's experience (2009) Jt Comm J Qual and Patient Saf, 35, pp. 82-92. , PubMed; (2008) Safely Implementing Health Information and Converging Technologies, (42). , http://www.jointcommission.org/assets/1/18/SEA_42.PDF, The Joint Commission. Sentinel Event Alert, Oakbrook Terrace (IL), Retrieved August 13, 2013; Wang, C.J., Huang, D.J., The HIPAA conundrum in the era of mobile health and communications (2013) JAMA, 310, pp. 1121-1122. , PubMed [Full Text]; Singh, H., Classen, D.C., Sittig, D.F., Creating an oversight infrastructure for electronic health record-related patient safety hazards (2011) J Patient Saf, 7, pp. 169-174. , PubMed [Full Text] RAYYAN-INCLUSION: {"Fernanda"=>true} N2 - The advantages of health information technology (IT) include facilitating communication between health care providers; improving medication safety, tracking, and reporting; and promoting quality of care through optimized access to and adherence to guidelines. Health IT systems permit the collection of data for use for quality management, outcome reporting, and public health disease surveillance and reporting. However, improvement is needed with all health IT, especially regarding design, implementation, and integration between platforms within the work environment. Robust interoperability is critical for safe care, but this goal has proved elusive. Significant patient safety concerns already have been recognized; it is important to keep patient safety and quality as the primary focus. Copyright © January 2015 by the American College of Obstetricians and Gynecologists. ER -