{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T18:07:34Z","timestamp":1774980454422,"version":"3.50.1"},"reference-count":50,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,1,4]],"date-time":"2024-01-04T00:00:00Z","timestamp":1704326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000092","name":"National Library of Medicine","doi-asserted-by":"publisher","award":["R01 LM006910"],"award-info":[{"award-number":["R01 LM006910"]}],"id":[{"id":"10.13039\/100000092","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Food and Drug Administration CBER BEST Initiative","award":["75F40120D00039"],"award-info":[{"award-number":["75F40120D00039"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,2,16]]},"abstract":"Abstract<\/jats:title>\n \n Importance<\/jats:title>\n The Observational Health Data Sciences and Informatics (OHDSI) is the largest distributed data network in the world encompassing more than 331 data sources with 2.1 billion patient records across 34 countries. It enables large-scale observational research through standardizing the data into a common data model (CDM) (Observational Medical Outcomes Partnership [OMOP] CDM) and requires a comprehensive, efficient, and reliable ontology system to support data harmonization.<\/jats:p>\n <\/jats:sec>\n \n Materials and methods<\/jats:title>\n We created the OHDSI Standardized Vocabularies\u2014a common reference ontology mandatory to all data sites in the network. It comprises imported and de novo-generated ontologies containing concepts and relationships between them, and the praxis of converting the source data to the OMOP CDM based on these. It enables harmonization through assigned domains according to clinical categories, comprehensive coverage of entities within each domain, support for commonly used international coding schemes, and standardization of semantically equivalent concepts.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The OHDSI Standardized Vocabularies comprise over 10 million concepts from 136 vocabularies. They are used by hundreds of groups and several large data networks. More than 8600 users have performed 50\u200a000 downloads of the system. This open-source resource has proven to address an impediment of large-scale observational research\u2014the dependence on the context of source data representation. With that, it has enabled efficient phenotyping, covariate construction, patient-level prediction, population-level estimation, and standard reporting.<\/jats:p>\n <\/jats:sec>\n \n Discussion and conclusion<\/jats:title>\n OHDSI has made available a comprehensive, open vocabulary system that is unmatched in its ability to support global observational research. We encourage researchers to exploit it and contribute their use cases to this dynamic resource.<\/jats:p>\n <\/jats:sec>","DOI":"10.1093\/jamia\/ocad247","type":"journal-article","created":{"date-parts":[[2024,1,4]],"date-time":"2024-01-04T17:52:01Z","timestamp":1704390721000},"page":"583-590","source":"Crossref","is-referenced-by-count":108,"title":["OHDSI Standardized Vocabularies\u2014a large-scale centralized reference ontology for international data harmonization"],"prefix":"10.1093","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3641-055X","authenticated-orcid":false,"given":"Christian","family":"Reich","sequence":"first","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"OHDSI Center at the Roux Institute, Northeastern University , Portland ME 04101, United States"},{"name":"Department of Medical Informatics, Erasmus University Medical Center , 3015 GD Rotterdam, The Netherlands"}]},{"given":"Anna","family":"Ostropolets","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Department of Biomedical Informatics, Columbia University Medical Center , New York City NY 10032, United States"},{"name":"Odysseus Data Services , Cambridge MA 02142, United States"}]},{"given":"Patrick","family":"Ryan","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Department of Biomedical Informatics, Columbia University Medical Center , New York City NY 10032, United States"},{"name":"Observational Health Data Analytics, Janssen Research & Development , Titusville NJ 08560, United States"}]},{"given":"Peter","family":"Rijnbeek","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Department of Medical Informatics, Erasmus University Medical Center , 3015 GD Rotterdam, The Netherlands"}]},{"given":"Martijn","family":"Schuemie","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Observational Health Data Analytics, Janssen Research & Development , Titusville NJ 08560, United States"}]},{"given":"Alexander","family":"Davydov","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Odysseus Data Services , Cambridge MA 02142, United States"}]},{"given":"Dmitry","family":"Dymshyts","sequence":"additional","affiliation":[{"name":"Coordinating Center, Observational Health Data Sciences and Informatics , New York City NY 10032, United States"},{"name":"Observational Health Data 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