Development, Implementation, and Evaluation of a Personalized Machine Learning Algorithm for Clinical Decision Support: Case Study With Shingles Vaccination.

Journal: Journal of medical Internet research
Published Date: Apr 29, 2020

Abstract

BACKGROUND: Although clinical decision support (CDS) alerts are effective reminders of best practices, their effectiveness is blunted by clinicians who fail to respond to an overabundance of inappropriate alerts. An electronic health record (EHR)-integrated machine learning (ML) algorithm is a potentially powerful tool to increase the signal-to-noise ratio of CDS alerts and positively impact the clinician's interaction with these alerts in general.

Authors

  • Ji Chen
    Department of Population Health, New York University School of Medicine, New York, NY, United States.
  • Sara Chokshi
    Department of Population Health, New York University School of Medicine, New York, NY, United States.
  • Roshini Hegde
    Department of Population Health, New York University School of Medicine, New York, NY, United States.
  • Javier González
    Department of Urology, Hospital General Universitario Gregorio Marañón, Madrid, Spain.
  • Eduardo Iturrate
    New York University School of Medicine, Department of Internal Medicine, New York, NY, United States.
  • Yin Aphinyanaphongs
    Department of Population Health, New York University School of Medicine, New York, NY, United States.
  • Devin Mann
    Department of Population Health, New York University School of Medicine, New York, NY, United States.

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