FHIRconnect: Towards a seamless integration of openEHR and FHIR

2025-11-18

AI Summary

Interoperability between openEHR and HL7 FHIR is hindered by fundamental differences in their data modeling paradigms. Method: This paper proposes a formal, extensible bidirectional transformation framework. It introduces the first domain-specific language (DSL) tailored for openEHR–FHIR mapping, implements a three-layer architecture—semantic alignment, structural mapping, and API adaptation—and delivers an open-source execution engine (openFHIR) alongside a reusable mapping library. Contribution/Results: The framework enables systematic, semantics-driven mapping between international openEHR archetypes and FHIR profiles, supporting both community-driven standardization and local customization. Evaluated across seven clinical domains, it successfully maps 24 openEHR archetypes to 15 FHIR profiles, achieving a 65% mapping reuse rate. This significantly reduces ETL development effort while improving consistency and efficiency in cross-standard clinical data exchange.

Technology Category

• Knowledge Representation and Reasoning: Description Logics
• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Security and Privacy: Data transparency and provenance

Abstract

Healthcare interoperability between openEHR and HL7 FHIR remains challenging due to fundamental differences in their data modeling approaches and the absence of standardized transformation mechanisms. This paper presents FHIRconnect, a novel domain-specific language and open-source transformation engine that enables standardized, bidirectional data exchange between openEHR and FHIR. Our approach addresses critical interoperability gaps through a triple-layered architecture that achieves 65% mapping reuse across projects by leveraging international archetype-based foundations while supporting local customizations. Using this framework, FHIRconnect successfully mapped 24 international archetypes to 15 FHIR profiles across seven clinical domains. Key contributions include the first comprehensive DSL for openEHR-FHIR transformation with a formal specification, an open-source execution engine (openFHIR), and an accessible mapping library covering high-impact clinical archetypes. Together, these components establish the technical basis for community-driven mapping standardization, reducing reliance on custom ETL solutions and advancing syntactic and semantic interoperability in healthcare IT systems built on open standards.

Problem

• Enabling bidirectional data exchange between openEHR and FHIR standards
• Addressing interoperability gaps through standardized transformation mechanisms
• Reducing reliance on custom ETL solutions for healthcare systems

Innovation

• A domain-specific language for openEHR-FHIR transformation
• Triple-layered architecture enabling bidirectional data exchange
• Open-source engine with reusable archetype-based mapping library