Developing an HL7 FHIR Implementation Guide for Rare Cancers: The IDEA4RC Project Experience

Area of Science:

• Health Informatics
• Oncology Data Standards

Background:

• Rare cancers present significant challenges for data sharing and secondary use due to low incidence and fragmented data sources.
• Existing data sharing initiatives often lack the specific longitudinal and episode-based representations required for European rare cancer research.

Purpose of the Study:

• To present the IDEA4RC Health Level Seven (HL7) FHIR Implementation Guide (IG).
• To operationalize the IDEA4RC common data model into computable specifications for semantic and computational interoperability in rare cancer research.

Main Methods:

• Development of a federated ecosystem for harmonized data exchange across European Centers of Excellence.
• Creation of the IDEA4RC HL7 FHIR IG, integrating logical models, constrained resource profiles, terminology bindings, and ConceptMaps.
• Mapping of 279 clinical variables across 19 entities from the common data model to HL7 FHIR profiles.

Main Results:

• The IDEA4RC HL7 FHIR IG provides computable specifications for a rare cancer common data model.
• The IG enables semantic and computational interoperability for rare cancer data exchange.
• The approach enhances longitudinal and episode-based data representation compared to existing standards like mCODE.

Conclusions:

• The IDEA4RC HL7 FHIR IG facilitates robust rare cancer data sharing within a federated ecosystem.
• This work supports broader harmonization efforts across oncology data standards.
• The IG lays the groundwork for future convergence with initiatives like the HL7 Cancer Common Model Project.