BMJ Open (Dec 2022)

Identification of risk factors associated with prolonged hospital stay following primary knee replacement surgery: a retrospective, longitudinal observational study

  • Martin Pitt,
  • Andrew Judge,
  • Tim Jones,
  • Rebecca Wilson,
  • Chris Penfold,
  • Andrew Elliott,
  • Ruta Margelyte,
  • Ashley Blom,
  • Maria Theresa Redaniel,
  • Alison Harper,
  • Emily Eyles,
  • Tim Keen

DOI
https://doi.org/10.1136/bmjopen-2022-068252
Journal volume & issue
Vol. 12, no. 12

Abstract

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Objectives To identify risk factors associated with prolonged length of hospital stay and staying in hospital longer than medically necessary following primary knee replacement surgery.Design Retrospective, longitudinal observational study.Setting Elective knee replacement surgeries between 2016 and 2019 were identified using routinely collected data from an NHS Trust in England.Participants There were 2295 knee replacement patients with complete data included in analysis. The mean age was 68 (SD 11) and 60% were female.Outcome measures We assessed a binary length of stay outcome (>7 days), a continuous length of stay outcome (≤30 days) and a binary measure of whether patients remained in hospital when they were medically fit for discharge.Results The mean length of stay was 5.0 days (SD 3.9), 15.4% of patients were in hospital for >7 days and 7.1% remained in hospital when they were medically fit for discharge. Longer length of stay was associated with older age (b=0.08, 95% CI 0.07 to 0.09), female sex (b=0.36, 95% CI 0.06 to 0.67), high deprivation (b=0.98, 95% CI 0.47 to 1.48) and more comorbidities (b=2.48, 95% CI 0.15 to 4.81). Remaining in hospital beyond being medically fit for discharge was associated with older age (OR=1.07, 95% CI 1.05 to 1.09), female sex (OR=1.71, 95% CI 1.19 to 2.47) and high deprivation (OR=2.27, 95% CI 1.27 to 4.06).Conclusions The regression models could be used to identify which patients are likely to occupy hospital beds for longer. This could be helpful in scheduling operations to aid hospital efficiency by planning these patients’ operations for when the hospital is less busy.