A general framework for developing computable clinical phenotype algorithms.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Aug 1, 2024

Abstract

OBJECTIVE: To present a general framework providing high-level guidance to developers of computable algorithms for identifying patients with specific clinical conditions (phenotypes) through a variety of approaches, including but not limited to machine learning and natural language processing methods to incorporate rich electronic health record data.

Authors

  • David S Carrell
    Group Health Research Institute, Seattle, WA, 98101, USA.
  • James S Floyd
  • Susan Gruber
    Innovation in Medical Evidence Development and Surveillance (IMEDS), Reagan-Udall Foundation for the FDA, Washington, District of Columbia.
  • Brian L Hazlehurst
  • Patrick J Heagerty
    Department of Biostatistics, University of Washington, Seattle, WA, USA.
  • Jennifer C Nelson
  • Brian D Williamson
    Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA.
  • Robert Ball
    Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, United States.

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