PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 41223026.
- Also identified by DOI 10.1093/jamia/ocaf195 and PMC identifier 12844593.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Computational phenotyping from electronic health records (EHRs) is essential for clinical research, decision support, and quality/population health assessment, but the proliferation of algorithms for the same conditions makes it difficult to identify which algorithm is most appropriate for reuse. To develop a framework for assessing phenotyping algorithm fitness for purpose and reuse. Phenotyping algorithms are fit for purpose when they identify the intended population with performance characteristics appropriate for the intended application. Phenotyping algorithms are fit for reuse when the algorithm is implementable and generalizable-that is, it identifies the same intended population with similar performance characteristics when applied to a new setting. The PhenoFit framework provides a structured approach to evaluate and adapt phenotyping algorithms for new contexts increasing efficiency and consistency of identifying patient populations from EHRs.
Medical subject headings
- Algorithms
- Electronic Health Records
- Phenotype