MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance

Abstract

Objective The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network. Current data partners create institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR provides a standards-based ETL approach using Health Language Seven's Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Materials and Methods The input data source was a research data warehouse (RDW) containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON language called Whistle, created FHIR R4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion OMOP-to-FHIR transformations passed validation with only minimal non-compliance issues. These resources provided the clinical and administrative data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR "facade" for accessing OMOP data. Conclusion MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-on-FHIR transformations provide an alternative mechanism for sharing OMOP data.