OMOP CDM
One common shape for observational health data — load your EHR into it and every OHDSI analysis ever written runs on your data.
In one line
The OMOP Common Data Model is a standard relational schema (person, condition_occurrence, drug_exposure, measurement…) plus standardised vocabularies, so observational data from any source becomes analysable by shared, reusable code.
How it works
You ETL your source (EHR, claims, registry) into OMOP's tables, mapping local codes to standard concepts (SNOMED CT for conditions, RxNorm for drugs, LOINC for measurements) via the OMOP vocabulary tables. The payoff is the OHDSI ecosystem: ATLAS for cohort definitions, validated methods libraries, and network studies where dozens of institutions run the same analysis locally and share only results — federated evidence at global scale.
Where it shows up in digital health
Real-world evidence for drug safety and effectiveness; multi-country studies (OHDSI network sites span every continent, India included); and the pragmatic answer to "our data is in seventeen formats" — make OMOP the analysis layer. The division of labour: FHIR moves one patient's data for care; OMOP shapes millions of patients' data for research.