Abstract
BACKGROUND: Improved identification of patients with complex needs early during hospitalisation may help target individuals at risk of delayed discharge with interventions to prevent iatrogenic complications, reduce length of stay and increase the likelihood of a successful discharge home. METHODS: In this retrospective cohort study, we linked home care assessment records based on the Resident Assessment Instrument for Home Care (RAI-HC) of 210 931 hospitalised patients with their Discharge Abstract Database records. We then undertook multivariable logistic regression analyses to identify preadmission predictive factors for delayed discharge from hospital. RESULTS: Characteristics that predicted delayed discharge included advanced age (OR: 2.72, 95% CI 2.55 to 2.90), social vulnerability (OR: 1.27, 95% CI 1.08 to 1.49), Parkinsonism (OR: 1.34, 95% CI 1.28 to 1.41) Alzheimer's disease and related dementias (OR: 1.27, 95% CI 1.23 to 1.31), need for long-term care facility services (OR: 2.08, 95% CI 1.96 to 2.21), difficulty in performing activities of daily living and instrumental activities of daily living, falls (OR: 1.16, 95% CI 1.12 to 1.19) and problematic behaviours such as wandering (OR: 1.29, 95% CI 1.22 to 1.38). CONCLUSION: Predicting delayed discharge prior to or on admission is possible. Characteristics associated with delayed discharge and inability to return home are easily identified using existing interRAI home care assessments, which can then facilitate the targeting of pre-emptive interventions immediately on hospital admission.