Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Journal: Internal and emergency medicine
Published Date: Jun 22, 2024

Abstract

Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In this implementation study, such an artificial intelligence algorithm was coupled with a multidisciplinary discharge facilitation team on weekend shifts. This approach was implemented in a tertiary hospital, and then compared to a historical cohort from the same time the previous year. There were 3990 patients included in the study. There was a significant increase in the proportion of inpatients who received weekend discharges in the intervention group compared to the control group (median 18%, IQR 18-20%, vs median 14%, IQR 12% to 17%, P = 0.031). There was a corresponding higher absolute number of weekend discharges during the intervention period compared to the control period (P = 0.025). The studied intervention was associated with an increase in weekend discharges and economic analyses support this approach as being cost-effective. Further studies are required to examine the generalizability of this approach to other centers.

Authors

  • Brandon Stretton
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.
  • Andrew E C Booth
    SA Health, Adelaide, SA, 5000, Australia.
  • Shrirajh Satheakeerthy
    SA Health, Adelaide, SA, 5000, Australia.
  • Sarah Howson
    SA Health, Adelaide, SA, 5000, Australia.
  • Shaun Evans
    SA Health, Adelaide, SA, 5000, Australia.
  • Joshua Kovoor
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.
  • Waqas Akram
    Lyell McEwin Hospital, Elizabeth Vale, SA, 5112, Australia.
  • Keith McNeil
    Commission on Excellence and Innovation in Health, Adelaide, South Australia, Australia.
  • Ashley Hopkins
    Flinders University, Bedford Park, SA, 5042, Australia.
  • Kathryn Zeitz
    SA Health, Adelaide, SA, 5000, Australia.
  • Alasdair Leslie
    SA Health, Adelaide, SA, 5000, Australia.
  • Peter Psaltis
    SA Health, Adelaide, SA, 5000, Australia.
  • Aashray Gupta
    Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
  • Sheryn Tan
    University of Adelaide, Adelaide, South Australia, Australia.
  • Melissa Teo
    Lyell McEwin Hospital, Elizabeth Vale, SA, 5112, Australia.
  • Andrew Vanlint
    Adelaide Medical School, The University of Adelaide, Adelaide, South Australia, Australia.
  • Weng Onn Chan
    Faculty of Health & Medical Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
  • Andrew Zannettino
    University of Adelaide, Adelaide, SA, 5005, Australia.
  • Patrick G O'Callaghan
    University of Adelaide, Adelaide, South Australia, Australia.
  • John Maddison
    Institute for Cancer Genetics and Informatics, Oslo University Hospital, Oslo, Norway.
  • Samuel Gluck
    Neurology Department, Royal Adelaide Hospital, Port Road, Adelaide, SA, 5000, Australia.
  • Toby Gilbert
    Neurology Department, Royal Adelaide Hospital, Port Road, Adelaide, SA, 5000, Australia.
  • Stephen Bacchi
    Faculty of Health and Medical Sciences, Adelaide Medical School, University of Adelaide, Adelaide, SA 5000 Australia.

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