FHIR Lens: A Graph-Based Approach to Semantic EHR Exploration

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Achieving interoperability in healthcare data remains challenging, particularly when exploring complex relationships modeled using Fast Healthcare Interoperability Resources (FHIR). Traditional visualization methods often fail to capture the full semantic richness of FHIR-modeled data. This paper proposes 'FHIR Lens,' an interactive graph-based platform designed to enhance FHIR exploration through RDF. It addresses these limitations by visualizing FHIR resources as interconnected nodes and edges, thereby making complex relationships discoverable. The platform utilizes SPARQL for dynamic query execution and employs recursive graph expansion to traverse structured healthcare data, effectively handling issues like blank nodes and inconsistent references. By supporting advanced data analysis, relationship discovery, and decision support, FHIR Lens contributes significantly to semantic interoperability in healthcare. The tool facilitates an intuitive understanding of complex clinical relationships by bridging standard data models (FHIR) with powerful graph-based modeling techniques. Performance evaluation on large FHIR datasets confirms its ability to handle exploration and summarization efficiently.