{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:30:38Z","timestamp":1750185038515},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,6,6]]},"abstract":"<jats:p>The heterogeneity of electronic health records model is a major problem: it is necessary to gather data from various models for clinical research, but also for clinical decision support. The Observational Medical Outcomes Partnership \u2013 Common Data Model (OMOP-CDM) has emerged as a standard model for structuring health records populated from various other sources. This model is proposed as a relational database schema. However, in the field of decision support, formal ontologies are commonly used. In this paper, we propose a translation of OMOP-CDM into an ontology, and we explore the utility of the semantic web for structuring EHR in a clinical decision support perspective, and the use of the SPARQL language for querying health records. The resulting ontology is available online.<\/jats:p>","DOI":"10.3233\/shti220035","type":"book-chapter","created":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:30:04Z","timestamp":1654594204000},"source":"Crossref","is-referenced-by-count":1,"title":["Translating the Observational Medical Outcomes Partnership \u2013 Common Data Model (OMOP-CDM) Electronic Health Records to an OWL Ontology"],"prefix":"10.3233","author":[{"given":"Lamy","family":"Jean-Baptiste","sequence":"first","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, LIMICS, Sorbonne Universit\u00e9, INSERM, UMR 1142, F-93000, Bobigny, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdelmalek","family":"Mouazer","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, LIMICS, Sorbonne Universit\u00e9, INSERM, UMR 1142, F-93000, Bobigny, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Karima","family":"Sedki","sequence":"additional","affiliation":[{"name":"Universit\u00e9 Sorbonne Paris Nord, LIMICS, Sorbonne Universit\u00e9, INSERM, UMR 1142, F-93000, Bobigny, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rosy","family":"Tsopra","sequence":"additional","affiliation":[{"name":"INSERM, Universit\u00e9 de Paris, Sorbonne Universit\u00e9, Centre de Recherche des Cordeliers, Information Sciences to support Personalized Medicine, F-75006 Paris, France"},{"name":"Department of Medical Informatics, H\u00f4pital Europ\u00e9en Georges-Pompidou, AP-HP, Paris, France"},{"name":"INRIA Paris, 75012 Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2021: One World, One Health \u2013 Global Partnership for Digital Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220035","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,7]],"date-time":"2022-06-07T09:30:04Z","timestamp":1654594204000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220035"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,6]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220035","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,6]]}}}