Place up to three profiles side by side. Compare their architectural role, lifecycle reach, and first limitation to test. No single standard covers every layer.
Working set
Choose profiles
1 of 3 selected
01
OMOP CDMData model / schema
Decision lens
Compare roles before choosing an implementation.
The useful question is not “Which standard wins?” It is “Which job must this part of the architecture perform, and what remains uncovered?”
01
Start with the job
Decide whether you need guidance, a domain payload, exchange, semantics, governance, or a reusable release.
02
Map lifecycle reach
Use the matrix to see where each profile has a direct role. A filled cell is coverage, not a quality score.
03
Test the boundary
Read what each option leaves unresolved before judging maturity or implementation fit.
Assessment
Review lifecycle coverage and practical fit.
Read left to right. Lifecycle reach comes first; a maturity label never overrides a scope mismatch.
01 · Lifecycle reach
Where each profile contributes directly
Coverage shows a recorded role at that readiness stage. It does not imply end-to-end implementation.
Readiness-stage coverage for OMOP Common Data Model
Relational structure, conventions, and standardized vocabularies for longitudinal observational health data.
Best fitMulti-source cohort analytics, patient-level prediction, characterization, and network studies after ETL.
Readiness stages
HarmonizeLearn + reuse
AI-ready contribution
A consistent longitudinal feature surface is valuable for ML, but label design, missingness, site shift, and temporal leakage remain local responsibilities.
First limitation to test
ETL is expensive, source nuance can be compressed, and vocabulary maintenance is an ongoing operational dependency.