PhenoFit: a framework for determining computable phenotyping algorithm fitness for purpose and reuse

Background: 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...

Full description

Saved in:
Bibliographic Details
Main Authors: Wiley, Laura K. (Author) , Rasmussen, Luke V (Author) , Levinson, Rebecca T. (Author) , Malinowski, Jennnifer (Author) , Manemann, Sheila M (Author) , Wilson, Melissa P (Author) , Chapman, Martin (Author) , Pacheco, Jennifer A (Author) , Walunas, Theresa L (Author) , Starren, Justin B (Author) , Bielinski, Suzette J (Author) , Richesson, Rachel L (Author)
Format: Article (Journal)
Language:English
Published: February 2026
In: Journal of the American Medical Informatics Association
Year: 2026, Volume: 33, Issue: 2, Pages: 536-542
ISSN:1527-974X
DOI:10.1093/jamia/ocaf195
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1093/jamia/ocaf195
Verlag, kostenfrei, Volltext: https://academic.oup.com/jamia/article/33/2/536/8321897
Get full text
Author Notes:Laura K. Wiley, PhD, Luke V. Rasmussen, MS, Rebecca T. Levinson, PhD, Jennnifer Malinowski, PhD, Sheila M. Manemann, MPH, Melissa P. Wilson, MS, Martin Chapman, PhD, Jennifer A. Pacheco, MS, Theresa L. Walunas, PhD, Justin B. Starren, MD, PhD, Suzette J. Bielinski, PhD, Rachel L. Richesson, PhD
Description
Summary:Background: 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. - Objective: To develop a framework for assessing phenotyping algorithm fitness for purpose and reuse. Fitness for Purpose: Phenotyping algorithms are fit for purpose when they identify the intended population with performance characteristics appropriate for the intended application. Fitness for Reuse: 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. - Conclusions: 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.
Item Description:Veröffentlicht: 12 November 2025
Gesehen am 09.03.2026
Physical Description:Online Resource
ISSN:1527-974X
DOI:10.1093/jamia/ocaf195