Providing Full Semantic Interoperability for the Fast Healthcare Interoperability Resources Schemas with Resource Description Framework

The Fast Healthcare Interoperability Resources (FHIR) is an open suite of specifications and software implementations of the Health Level 7 version 3 (HL7v3) standard. It has been proposed to provide a consistent API for the HL7v3 CDA. However, the core issues of HL7v3 are not solved at the API level. The community around the project are proposing the adoption of RDF technologies to overcome the current challenges in interoperating with linked data. However, RDF triples nor ontologies provide semantic interoperability by themselves, a more robust information infrastructure, such as the Multilevel Model-Driven (MMD) approach, is required. An XML implementation of the MMD was used to model the FHIR Schemas as Domain Models (DMs) against a generic Reference Model (RM) to provide syntactic validation. RDF triples were included in the domain models to provide missing semantics. The XML data instances were validated against their Domain Models. The DMs do not create any new types, they only express constraints of the RM types, this provides consistent query and data analysis capability across all DMs. RDF triples were extracted from the DMs and added to a triple store graph with the RM ontology. The XML data is also expressed as Literals in the graph. This study shows the feasibility of using MMD solutions to provide full operational semantic interoperability for the FHIR ecosystem.

I. Introduction

The key to clinical decision support is having access to all relevant data about an individual (or a population). It cannot be known a priora what relevant means in any given context. In addition to access to the data, the decision support engine must have access to the semantics that describe the data. This includes complete ontological, spatial and temporal information. This then will provide operational semantic interoperability.