Proposed Schema Extensions and ETL Pathways for Integrating Wearable and Patient-Reported PGHD into OMOP-CDM for Secondary Use

Abstract

The rapid expansion of wearable sensing technologies and patient-reported outcomes (PROs) has revealed a persistent gap between high-frequency, context-rich patient-generated health data (PGHD) and standardized data models used for secondary analysis. Although the OMOP Common Data Model (OMOP-CDM) supports large-scale observational research, it does not natively capture key PGHD characteristics such as device provenance, calibration parameters, temporal resolution, and contextual metadata. This paper introduces an extension layer for OMOP-CDM and a direct extract-transform-load (ETL) pathway that enhances its capacity to handle heterogeneous, time-series, and PRO data while maintaining semantic consistency. The approach preserves device traceability, enables flexible data compression, and links PRO instruments with OMOP constructs without altering the core schema, remaining fully compatible with OHDSI analytical tools and aligned with FAIR principles. The model has strong potential for community discussion and future OMOP updates on PGHD.