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Observational Health Data Sciences and Informatics

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Observational Health Data Sciences and Informatics (OHDSI)
AbbreviationOHDSI
TypeInternational collaborative
PurposeTo improve health by empowering a community to collaboratively generate evidence that promotes better health decisions and better care.
HeadquartersColumbia University
Region served
International
Websitewww.ohdsi.org

The Observational Health Data Sciences and Informatics, or OHDSI (pronounced "Odyssey") is an international collaborative effort aimed at improving health outcomes through large-scale analytics of health data.[1] The OHDSI effort includes diverse researchers and health databases worldwide, with its central coordinating center located at Columbia University.[2]

The group was derived from the Observational Medical Outcomes Partnership (OMOP), a public-private consortium based in the United States of America, created with the goal of improving the state of observational health data for better drug development, which started in response to the U.S. Food and Drug Administration (FDA) Amendments Act of 2007.[3][4] OMOP developed a Common Data Model (CDM), standardizing the way observational data is represented.[3] After OMOP ended, this standard started being maintained and updated by OHDSI.[1]

As of February 2024, the most recent CDM is at version 6.0, while version 5.4 is the stable version used by most tools in the OMOP ecosystem.[5]

See also

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References

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  1. ^ a b Hripcsak, George; Duke, Jon D; Shah, Nigam H; Reich, Christian G; Huser, Vojtech; Schuemie, Martijn J; Suchard, Marc A; Park, Rae Woong; Wong, Ian Chi Kei; Rijnbeek, Peter R; van der Lei, Johan; Pratt, Nicole; Norén, G Niklas; Li, Yu-Chuan; Stang, Paul E (2015). "Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers". Studies in Health Technology and Informatics. 216: 574–578. ISSN 0926-9630. PMC 4815923. PMID 26262116.
  2. ^ "Observational Health Data Sciences and Informatics (OHDSI)". Programs in Global Health. 2020-10-23. Retrieved 2024-02-01.
  3. ^ a b Overhage, J Marc; Ryan, Patrick B; Reich, Christian G; Hartzema, Abraham G; Stang, Paul E (2012). "Validation of a common data model for active safety surveillance research". Journal of the American Medical Informatics Association. 19 (1): 54–60. doi:10.1136/amiajnl-2011-000376. ISSN 1067-5027. PMC 3240764. PMID 22037893.
  4. ^ Stang, Paul E.; Ryan, Patrick B.; Racoosin, Judith A.; Overhage, J. Marc; Hartzema, Abraham G.; Reich, Christian; Welebob, Emily; Scarnecchia, Thomas; Woodcock, Janet (2010-11-02). "Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership". Annals of Internal Medicine. 153 (9): 600–606. doi:10.7326/0003-4819-153-9-201011020-00010. ISSN 1539-3704. PMID 21041580.
  5. ^ "OMOP CDM v6.0". ohdsi.github.io. Retrieved 2024-02-01.
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