Development and implementation of an entity relationship diagram for perinatal data.

OBJECTIVE: Severe maternal morbidity and mortality are higher in the United States than in other high-income countries, and unacceptable disparities persist. To facilitate research on these outcomes, we developed a standardized approach for extracting perinatal data from electronic health records (EHRs). MATERIALS AND METHODS: To support data model building and validation, we harmonized perinatal EHR data in a common data model, building on lessons learned from multiple prior projects. RESULTS: We developed an Entity Relationship Diagram (ERD) that aggregates perinatal EHR data at appropriate granularities (ie, mothers, infants, encounters) with indexing of observations to gestational age and time from delivery. We then developed a standard approach to extract, transform, and load pregnancy-related observations from EHRs for inclusion in PCORnet® Common Data Model tables. DISCUSSION: Our ERD can facilitate cross-institutional research to identify populations at risk and prompt interventions to improve perinatal outcomes. CONCLUSION: A structured approach can accelerate the use of EHR data for perinatal research.

Duke Scholars

Author David Page Biostatistics & Bioinformatics, Division of Biostatistics