From Heterogeneity to Uniformity: A Metadata-Driven ETL Process for Transforming FHIR Data into OMOP CDM

Heterogeneous data formats complicate unified analysis in multisite clinical studies. Standardizing data in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) requires Extract-Transform-Load (ETL) processes, which are complex and time-consuming to develop, especially with different source data specifications. The aim of our work is to develop a generalized, metadata-driven ETL process to transform Fast Healthcare Interoperability Resources (FHIR) into OMOP CDM. In this paper, we present first results of the developed metadata-driven ETL process on the example of two different Patient FHIR specifications.