Training and Interpreting Machine Learning Algorithms to Evaluate Fall Risk After Emergency Department Visits.

Journal: Medical care
Published Date: Jul 1, 2019

Abstract

BACKGROUND: Machine learning is increasingly used for risk stratification in health care. Achieving accurate predictive models do not improve outcomes if they cannot be translated into efficacious intervention. Here we examine the potential utility of automated risk stratification and referral intervention to screen older adults for fall risk after emergency department (ED) visits.

Authors

  • Brian W Patterson
    UW Health, Madison, USA.
  • Collin J Engstrom
    Department of Computer Sciences, University of Wisconsin-Madison.
  • Varun Sah
    Department of Computer Sciences, University of Wisconsin-Madison.
  • Maureen A Smith
    Health Innovation Program.
  • Eneida A Mendonca
    University of Wisconsin-Madison, USA.
  • Michael S Pulia
    BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health.
  • Michael D Repplinger
    BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health.
  • Azita G Hamedani
    BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • David Page
    Duke University, Department of Biostatistics and Bioinformatics, Durham, NC, USA.
  • Manish N Shah
    BerbeeWalsh Department of Emergency Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.

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