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Stud Health Technol Inform ; 301: 12-17, 2023 May 02.
Article in English | MEDLINE | ID: mdl-37172145

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®.


Subject(s)
Electronic Health Records , Quality Indicators, Health Care , Humans , Vaccination Coverage , Language , Information Storage and Retrieval , Health Level Seven
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