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®.
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®.
| Original language | English |
|---|---|
| Title of host publication | dHealth 2023 |
| Subtitle of host publication | Proceedings of the 17th Health Informatics Meets Digital Health Conference |
| Publisher | IOS Press |
| Pages | 12-17 |
| Number of pages | 6 |
| Volume | 301 |
| Edition | 301 |
| ISBN (Electronic) | 978-1-64368-387-4 |
| ISBN (Print) | 978-1-64368-386-7 |
| DOIs | |
| Publication status | Published - 2 May 2023 |
| Event | dHealth 2023: Health Informatics meets Digital Health - Wien, Austria Duration: 16 May 2023 → 17 May 2023 https://dhealth.at/ |
Publication series
| Name | Studies in health technology and informatics |
|---|
Conference
| Conference | dHealth 2023 |
|---|---|
| Country/Territory | Austria |
| City | Wien |
| Period | 16.05.2023 → 17.05.2023 |
| Internet address |
Keywords
- Clinical Quality Language CQL
- Clinical Quality Measures
- Health Level 7 HL7
- Immunization Coverage