Enhancing Interoperability of HL7 Resources Using Namespaces in Graph Databases

The adoption of the FHIR (Fast Healthcare Interoperability Resources) standard has led to an exponential growth of modular healthcare data that needs to be managed efficiently. Graph databases such as Neo4j offer an effective way to store and query this data, but can become complex when dealing with FHIR resources that contain numerous extensions. We explore the use of namespaces in Neo4j graph databases to manage FHIR resources and compare it with the existing tool, CyFHIR. We demonstrate that by embedding extensions using the namespace concept, the complexity of the graph can be significantly reduced. Furthermore, we evaluate our approach on a generated dataset and show that the use of namespaces in Neo4j outperforms CyFHIR conventional methods for storing FHIR resources in graph databases. Our findings suggest that the use of namespaces can be a valuable addition to Neo4j graph databases for managing complex FHIR resources.