Using machine learning models to predict falls in hospitalised adults.

Journal: International journal of medical informatics
PMID:

Abstract

BACKGROUND: Identifying patients at high risk of falling is crucial in implementing effective fall prevention programs. While the integration of information systems is becoming more widespread in the healthcare industry, it poses a significant challenge in analysing vast amounts of data to identify factors that could enhance patient safety.

Authors

  • S Jahandideh
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
  • A F Hutchinson
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Epworth HealthCare, Richmond, Victoria, Australia.
  • T K Bucknall
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Alfred Health, Prahran, Victoria, Australia.
  • J Considine
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Eastern Health, Box Hill, Victoria, Australia.
  • A Driscoll
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
  • E Manias
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
  • N M Phillips
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
  • B Rasmussen
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Western Health, Sunshine, Victoria, Australia.
  • N Vos
    Monash Health, Clayton, Victoria, Australia.
  • A M Hutchinson
    School of Nursing and Midwifery, Centre for Quality and Patient Safety Research in the Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Barwon Health, Geelong, Victoria, Australia. Electronic address: alison.hutchinson@deakin.edu.au.