Machine Learning Prediction for Postdischarge Falls in Older Adults: A Multicenter Prospective Study.

Journal: Journal of the American Medical Directors Association
PMID: 39701553

Abstract

OBJECTIVES: The study aimed to develop a machine learning (ML) model to predict early postdischarge falls in older adults using data that are easy to collect in acute care hospitals. This may reduce the burden imposed by complex measures on patients and health care staff.

Authors

  • Yuko Takeshita
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Mai Onishi
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Hirotada Masuda
    Department of Cardiovascular Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Mizuki Katsuhisa
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Kasumi Ikuta
    Tokyo Medical and Dental University Graduate School of Health Care Sciences, Tokyo, Japan.
  • Yuichiro Saizen
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Misaki Fujii
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Misaki Kasamatsu
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Nobuyuki Inaizumi
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Yuzuki Maeizumi
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Yoshinobu Kishino
    Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan.
  • Tsuneo Nakajima
    Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan.
  • Eriko Koujiya
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan.
  • Miyae Yamakawa
    Department of Evidence-Based Clinical Nursing, Division of Health Sciences, Graduate School of Medicine, Osaka University, 1-1 Yamadaoka, Suita, Osaka 565-0871, Japan.
  • Yoichi Takami
    Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan.
  • Koichi Yamamoto
    Department of Geriatric and General Medicine, Graduate School of Medicine, Osaka University, Osaka, Japan.
  • Yumi Umeda-Kameyama
    Department of Geriatric Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Shosuke Satake
    Department of Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, Japan.
  • Hiroyuki Umegaki
    Department of Community Healthcare and Geriatrics, Graduate School of Medicine, Nagoya University, Nagoya, Japan.
  • Yasushi Takeya
    Division of Health Sciences, Osaka University Graduate School of Medicine, Osaka, Japan. Electronic address: ytakeya@sahs.med.osaka-u.ac.jp.

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