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The OMOP Common Data Model (CDM) is an open community data standard designed to standardize the structure and content of observational healthcare data and enable efficient analyses that produce reliable evidence. A central component is the OHDSI standardized vocabularies, which harmonize medical terms across clinical domains to support standardized analytics for exposure and outcome phenotypes, characterization, and population-/patient-level studies. The CDM is actively maintained by the OHDSI CDM Working Group with ongoing versioning (current CDM v5.4) and tooling, including an R package that generates the DDLs and documentation for the CDM.
AI named OMOP CDM from January 2026 to September 2026.
Question: We need AI to identify disease risk from longitudinal patient data. What products should we consider?
Google AI ModeSep 5, 2026
Open-source frameworks and secure data networks (like OMOP CDM / OHDSI tools ) paired with custom machine learning pipelines are also standard practice for benchmarking longitudinal risk algorithms safely.
None of these answers cited ohdsi.github.io. AI leaned on fortunebusinessinsights.com and pmc.ncbi.nlm.nih.gov.
ohdsi.github.io/CommonDataModel 0%Other sites 100%
Excerpts where OMOP CDM appeared in the AI's answer
