A reusable ontology for primitive and complex HL7 FHIR data types

Area of Science:

• Computer Science
• Bioinformatics
• Health Informatics

Background:

• The Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard offers advanced interoperability solutions.
• Representing complex healthcare data types within existing semantic frameworks presents significant challenges.

Purpose of the Study:

• To develop a standalone Resource Description Framework (RDF) vocabulary as an OWL ontology for FHIR data types.
• To define primitive and complex FHIR data types and their validation rules within an ontological structure.
• To ensure semantic cohesion with the FHIR standard for broader healthcare data integration.

Main Methods:

• Development of a formal OWL ontology to model FHIR data types.
• Representation of FHIR primitive and complex types using RDF constructs.
• Definition of validation rules within the OWL ontology.

Main Results:

• A comprehensive RDF vocabulary and OWL ontology for FHIR data types has been created.
• The ontology provides a coherent and complete representation of FHIR data types as RDF/OWL constructs.
• The proposed ontology successfully integrates validation rules for FHIR data types.

Conclusions:

• The developed ontology serves as a foundational framework for FHIR data representation, particularly when full Electronic Health Record (EHR) complexity is not needed.
• It maintains semantic consistency with the established FHIR standard.
• This work can be extended to form the basis for a complete ontological representation of the FHIR model.