Unsupervised Machine Learning of Topics Documented by Nurses about Hospitalized Patients Prior to a Rapid-Response Event.

Journal: Applied clinical informatics
PMID: 31853936

Abstract

BACKGROUND: In the hospital setting, it is crucial to identify patients at risk for deterioration before it fully develops, so providers can respond rapidly to reverse the deterioration. Rapid response (RR) activation criteria include a subjective component ("worried about the patient") that is often documented in nurses' notes and is hard to capture and quantify, hindering active screening for deteriorating patients.

Authors

  • Zfania Tom Korach
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
  • Kenrick D Cato
    School of Nursing, Columbia University, New York, New York, United States.
  • Sarah A Collins
    School of Nursing, Columbia University, New York, New York, United States.
  • Min Jeoung Kang
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
  • Christopher Knaplund
    School of Nursing, Columbia University, New York, New York, United States.
  • Patricia C Dykes
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
  • Liqin Wang
    Brigham and Women's Hospital, Boston, MA, USA.
  • Kumiko O Schnock
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
  • Jose P Garcia
    Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, United States.
  • Haomiao Jia
    School of Nursing, Columbia University, New York, New York, United States.
  • Frank Chang
    Shady Grove Fertility, Rockville, Maryland.
  • Jessica M Schwartz
    School of Nursing, Columbia University, New York, New York, United States.
  • Li Zhou
    School of Education, China West Normal University, Nanchong, Sichuan, China.

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