From Authoring to Evaluating an Electronic Health Quality Measure - Applying Logic to FHIR® with CQL for Calculating Immunization Coverage

Stud Health Technol Inform. 2023 May 2:301:12-17. doi: 10.3233/SHTI230004.

Abstract

Background: Current monitoring and evaluation methods challenge the healthcare system. Specifically for the use case of immunization coverage calculation, person-level data retrieval is required instead of inaccurate aggregation methods. The Clinical Quality Language (CQL) by HL7®, has the potential to overcome current challenges by offering an automated generation of quality reports on top of an HL7® FHIR® repository.

Objectives: This paper provides a method to author and evaluate an electronic health quality measure as demonstrated by a proof-of-concept on immunization coverage calculation.

Methods: Five artifact types were identified to transform unstructured input into CQL, to define the terminology, to create test data, and to evaluate the new quality measures.

Results: CQL logic and FHIR® test data were created and evaluated by using the different approaches of manual evaluation, unit testing in the HAPI FHIR project, as well as showcasing the functionality with a developed user interface for immunization coverage analysis.

Conclusion: Simple, powerful, and transparent evaluations on a small population can be achieved with existing open-source tools, by applying CQL logic to FHIR®.

Keywords: Clinical Quality Language CQL; Clinical Quality Measures; Health Level 7 HL7; Immunization Coverage.

MeSH terms

  • Electronic Health Records*
  • Health Level Seven
  • Humans
  • Information Storage and Retrieval
  • Language
  • Quality Indicators, Health Care*
  • Vaccination Coverage