Deconstructing the Interoperability Stack: A Comparative Technical Analysis of HL7 v2, CDA, and the FHIR Resource
Vibha Tiwari1,2, Shreecha Jha1, Rebakah Geddam2,3
1Centre for Artificial Intelligence, Madhav Institute of Technology and Science, Gwalior, India.
Abstract:
This structured scoping review aims to provide a technical comparison of the development of interoperability standards in healthcare, from the early electronic health record systems, HL7 v2, HL7 v3/Clinical Document Architecture, to Fast Healthcare Interoperability Resources (FHIR). The review considers architectural foundations, semantic models, interoperability mechanisms, and conformance approaches of these standards in a consistent comparative context. With the introduction of the event-driven message paradigm (based on segments and trigger events), HL7 v2 became widely adopted in healthcare institutions; yet, a lot of customization at the local level often resulted in semantic incompleteness over the various environments within the healthcare industry. This led to the development of model-driven and document-centric semantic architectures such as HL7 v3 and Clinical Document Architecture to facilitate greater interoperability, but with implementation complexity and architectural rigidity, these were not widely embraced. FHIR then built on the experience of previous generations of interoperability, including the introduction of light-weight resource-oriented architectures, the RESTful way of interacting with resources, the profiling mechanism, and the introduction of a computable implementation guide that fits with web-native healthcare ecosystems. In contrast to the previous reviews, which concentrated mostly on individual interoperability standards or implementation areas, this review comparatively synthesizes technical and semantic development of interoperability architectures and investigates the treatment of any shortcomings found in preexisting architectures by the following standards. The synthesis indicates that FHIR currently represents one of the most scalable and implementation-oriented foundations for contemporary healthcare interoperability and future digital health integration.
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