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- Title
Design and validation of a FHIR-based EHR-driven phenotyping toolbox.
- Authors
Brandt, Pascal S; Pacheco, Jennifer A; Adekkanattu, Prakash; Sholle, Evan T; Abedian, Sajjad; Stone, Daniel J; Knaack, David M; Xu, Jie; Xu, Zhenxing; Peng, Yifan; Benda, Natalie C; Wang, Fei; Luo, Yuan; Jiang, Guoqian; Pathak, Jyotishman; Rasmussen, Luke V
- Abstract
<bold>Objectives: </bold>To develop and validate a standards-based phenotyping tool to author electronic health record (EHR)-based phenotype definitions and demonstrate execution of the definitions against heterogeneous clinical research data platforms.<bold>Materials and Methods: </bold>We developed an open-source, standards-compliant phenotyping tool known as the PhEMA Workbench that enables a phenotype representation using the Fast Healthcare Interoperability Resources (FHIR) and Clinical Quality Language (CQL) standards. We then demonstrated how this tool can be used to conduct EHR-based phenotyping, including phenotype authoring, execution, and validation. We validated the performance of the tool by executing a thrombotic event phenotype definition at 3 sites, Mayo Clinic (MC), Northwestern Medicine (NM), and Weill Cornell Medicine (WCM), and used manual review to determine precision and recall.<bold>Results: </bold>An initial version of the PhEMA Workbench has been released, which supports phenotype authoring, execution, and publishing to a shared phenotype definition repository. The resulting thrombotic event phenotype definition consisted of 11 CQL statements, and 24 value sets containing a total of 834 codes. Technical validation showed satisfactory performance (both NM and MC had 100% precision and recall and WCM had a precision of 95% and a recall of 84%).<bold>Conclusions: </bold>We demonstrate that the PhEMA Workbench can facilitate EHR-driven phenotype definition, execution, and phenotype sharing in heterogeneous clinical research data environments. A phenotype definition that integrates with existing standards-compliant systems, and the use of a formal representation facilitates automation and can decrease potential for human error.
- Subjects
LANGUAGE &; languages; RESEARCH funding; PHENOTYPES
- Publication
Journal of the American Medical Informatics Association, 2022, Vol 29, Issue 9, p1449
- ISSN
1067-5027
- Publication type
journal article
- DOI
10.1093/jamia/ocac063