Analytic Interoperability Framework for High-Fidelity Representation of Perioperative Electronic Health Record Data in the OMOP Common Data Model Using Clinical Representation and Analytic Concept Reconstruction

OMOP CDM mapping of perioperative EHR concepts achieved 97.4% “equal” classifications under lenient criteria and >99% cohort concordance across 31,158 elective adult surgical encounters.

• Why it matters: Vocabulary-level equivalence alone may miss clinically meaningful analytic meaning, limiting high-fidelity perioperative research interoperability.
• What they did: They extracted data from an academic Epic Clarity database, manually mapped 538 source concepts to OMOP via Athena, then used SQL workflows to reconstruct clinical representations and analytic concepts validated against native Epic.
• The result: Reconstructed analytic variables from 31,083 shared encounters showed high agreement, with remaining discordance mainly tied to vasopressor infusion identification, BMI selection, payer assignment, and admission source.

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