Combining Archetypes with Fast Health Interoperability Resources in Future-proof Health Information Systems

Area of Science:

• Health Informatics
• Clinical Informatics
• Information Systems Engineering

Background:

• Health Level Seven version 2 (HL7 v2) is a widely adopted messaging standard for health information systems.
• HL7 Fast Healthcare Interoperability Resources (FHIR) was developed to enhance semantic interoperability in healthcare.
• Dual model methodology offers a precise approach to clinical information modeling.

Purpose of the Study:

• To demonstrate the application of dual model methodology to HL7 FHIR.
• To explore the utility of this approach for data transformation between FHIR and other healthcare standards.
• To analyze the implications of defining archetypes over FHIR.

Main Methods:

• Applying dual model methodology principles to HL7 FHIR.
• Evaluating data transformation capabilities between FHIR and standards like HL7 CDA, EN ISO 13606, and openEHR.
• Developing a testing data server supporting FHIR resources and archetypes.

Main Results:

• The dual model methodology can be effectively applied to HL7 FHIR.
• This approach facilitates data transformation between FHIR and diverse healthcare specifications.
• The study provides insights into the advantages and disadvantages of FHIR archetypes.

Conclusions:

• Applying dual model methodology to FHIR enhances interoperability and data transformation.
• Defining archetypes over FHIR presents specific advantages and disadvantages that warrant careful consideration.
• The developed testing server validates the practical implementation of this integrated approach.