Applying computable phenotypes within a common data model to identify heart failure patients for an implantable cardiac device registry.

Background: Use of existing data in electronic health records (EHRs) could be used more extensively to better leverage real world data for clinical studies, but only if standard, reliable processes are developed. Numerous computable phenotypes have been validated against manual chart review, and common data models (CDMs) exist to aid implementation of such phenotypes across platforms and sites. Our objective was to measure consistency between data that had previously been manually collected for an implantable cardiac device registry and CDM-based phenotypes for the condition of heart failure (HF).