Natural Language Processing to Identify Home Health Care Patients at Risk for Becoming Incapacitated With No Evident Advance Directives or Surrogates.

Journal: Journal of the American Medical Directors Association
PMID: 38754475

Abstract

OBJECTIVES: Home health care patients who are at risk for becoming Incapacitated with No Evident Advance Directives or Surrogates (INEADS) may benefit from timely intervention to assist them with advance care planning. This study aimed to develop natural language processing algorithms for identifying home care patients who do not have advance directives, family members, or close social contacts who can serve as surrogate decision-makers in the event that they lose decisional capacity.

Authors

  • Jiyoun Song
    School of Nursing, Columbia University, New York, New York, USA.
  • Maxim Topaz
    Division of General Internal Medicine and Primary Care, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA.
  • Aviv Y Landau
    Data Science Institute, Columbia University, New York, New York, United States of America.
  • Robert L Klitzman
    Columbia University College of Physicians and Surgeons, New York, NY, USA; Columbia University Joseph Mailman School of Public Health, New York, NY, USA.
  • Jingjing Shang
    School of Nursing, Columbia University, New York City, New York, USA.
  • Patricia W Stone
    Columbia University School of Nursing, New York, NY, USA.
  • Margaret V McDonald
    The Visiting Nurse Service of New York, New York, NY, USA.
  • Bevin Cohen
    Center for Nursing Research and Innovation, Mount Sinai Health System, New York, New York, United States of America.

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