A Typology of Existing Machine Learning-Based Predictive Analytic Tools Focused on Reducing Costs and Improving Quality in Health Care: Systematic Search and Content Analysis.

Journal: Journal of medical Internet research
Published Date: Jun 22, 2021

Abstract

BACKGROUND: Considerable effort has been devoted to the development of artificial intelligence, including machine learning-based predictive analytics (MLPA) for use in health care settings. The growth of MLPA could be fueled by payment reforms that hold health care organizations responsible for providing high-quality, cost-effective care. Policy analysts, ethicists, and computer scientists have identified unique ethical and regulatory challenges from the use of MLPA in health care. However, little is known about the types of MLPA health care products available on the market today or their stated goals.

Authors

  • Ariadne A Nichol
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Jason N Batten
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Meghan C Halley
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Julia K Axelrod
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.
  • Pamela L Sankar
    Department of Medical Ethics and Health Policy, Perelman School of Medicine, Philadelphia, PA, United States.
  • Mildred K Cho
    Stanford School of Medicine, Stanford Center for Biomedical Ethics, Stanford, CA, United States.

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