Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study.

Journal: BMJ health & care informatics
Published Date: Apr 22, 2024

Abstract

BACKGROUND: High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach.

Authors

  • Chih-Wei Sung
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
  • Joshua Ho
    Center of Intelligent Healthcare, National Taiwan University Hospital, Taipei, Taiwan.
  • Cheng-Yi Fan
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
  • Ching-Yu Chen
    Department of Emergency Medicine, National Taiwan University Hospital Yun-Lin Branch, Douliou, Taiwan.
  • Chi-Hsin Chen
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
  • Shao-Yung Lin
    Department of Emergency Medicine, National Taiwan University Hospital, Taipei, Taiwan.
  • Jia-How Chang
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
  • Jiun-Wei Chen
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan.
  • Edward Pei-Chuan Huang
    Department of Emergency Medicine, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan edward56026@gmail.com.

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