Using machine learning to selectively highlight patient information.

Journal: Journal of biomedical informatics
Published Date: Dec 1, 2019

Abstract

BACKGROUND: Electronic medical record (EMR) systems need functionality that decreases cognitive overload by drawing the clinician's attention to the right data, at the right time. We developed a Learning EMR (LEMR) system that learns statistical models of clinician information-seeking behavior and applies those models to direct the display of data in future patients. We evaluated the performance of the system in identifying relevant patient data in intensive care unit (ICU) patient cases.

Authors

  • Andrew J King
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Gregory F Cooper
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Gilles Clermont
    Cardiopulmonary Research Laboratory, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
  • Harry Hochheiser
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Milos Hauskrecht
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Dean F Sittig
    Center for Innovations in Quality, Effectiveness and Safety, Michael E DeBakey Veterans Affairs Medical Center, Houston, Texas, USA.
  • Shyam Visweswaran
    University of Pittsburgh, Pittsburgh, PA, USA.

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