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Implementation of a HL7-CQL Engine Using the Graph Database Neo4J.

Georg Fette1,2, Mathias Kaspar2, Leon Liman1

  • 1University of Würzburg, Chair of Computer Science 6.

Studies in Health Technology and Informatics
|September 5, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a method to execute Clinical Quality Language (CQL) queries on FHIR data using the Neo4j graph database. The approach translates CQL to Cypher, enabling efficient querying of complex health data structures.

Keywords:
FHIRNeo4Jgraph databasequery engine

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Area of Science:

  • Health Informatics
  • Database Management
  • Clinical Informatics

Background:

  • Clinical Quality Language (CQL) is vital for querying FHIR data.
  • Limited availability of CQL execution engines hinders data access.
  • FHIR data's graph structure presents unique querying challenges.

Purpose of the Study:

  • To develop and evaluate a novel approach for executing CQL queries on FHIR data.
  • To leverage graph database technology for efficient health data retrieval.
  • To bridge the gap between CQL query definition and FHIR data accessibility.

Main Methods:

  • Storing FHIR data within the Neo4j graph database.
  • Translating Clinical Quality Language (CQL) queries into Neo4j's Cypher query language.
  • Re-translating Cypher query results back into FHIR representations.

Main Results:

  • Successfully implemented and tested a CQL to Cypher translation mechanism.
  • Demonstrated the feasibility of querying FHIR data stored in Neo4j using translated CQL queries.
  • Validated the approach on public FHIR servers with example queries.

Conclusions:

  • The proposed method offers a viable solution for executing CQL queries on FHIR data via Neo4j.
  • This approach enhances the utility of CQL for complex health data analysis.
  • The Neo4j-based engine improves accessibility and querying of graph-structured FHIR data.