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Aim: To explore the association between systemic lupus erythematosus (SLE) with the risk of cancer development and subsequent 5‐year mortality in Western Australia (WA). Methods: Population‐level, data linkage study of SLE patients (n = 2111) and general population comparators (n = 21 110) hospitalized between 1980 and 2014. SLE patients (identified by ICD‐9‐CM: 695.4, 710.0, and ICD‐10‐AM: L93.0, M32.0) were nearest matched (10:1) for age, sex, Aboriginality, and temporality. Follow up was from time zero (index SLE hospitalization) to cancer development, death or 31 December 2014. We assessed the risk of cancer development and subsequent 5‐year mortality between SLE patients and comparators with univariate and multivariate‐adjusted Cox proportional hazards regression models. Results: SLE patients had similar multivariate‐adjusted risk (adjusted hazard ratio [aHR] 1.03, 95% confidence interval [CI] 0.93–1.15; p =.583) of cancer development. Cancer development risk was higher in SLE patients <40 years old (aHR 1.58, 95% CI 1.29–1.94; p <.001), and from 1980 to 1999 (aHR 1.16, 95% CI 1.02–1.31; p <.001). SLE patients had higher risk of developing cancer of the oropharynx (aHR 2.13, 95% CI 1.30–3.50), vulvo‐vagina (aHR 3.22, 95% CI 1.34–7.75), skin (aHR 1.20, 95% CI 1.01–1.43), musculoskeletal tissues (aHR 2.26, 95% CI 1.16–4.40), and hematological tissues (aHR 1.78 95% CI 1.25–2.53), all p <.05. After cancer development, SLE patients had increased risk of 5‐year mortality (aHR 1.31, 95% CI 1.06–1.61); highest in patients <50 years old (aHR 2.03, 95% CI 1.03–4.00), and in those with reproductive system and skin cancers. Conclusions: Hospitalized SLE patients had increased risk of multiple cancer sub‐types. Following cancer development, SLE patients had increased risk of 5‐year mortality. There is scope to improve cancer prevention and surveillance in SLE patients. Trial registration: Not applicable. This low‐risk risk study used de‐identified administrative linked health data. [ABSTRACT FROM AUTHOR]

Objectives: Transitional care program in Australia targets older patients in hospitals requiring ongoing slow‐stream restorative care prior to discharge. Poststroke patients often require extended care and are transferred to these facilities. Transitional care providers require a predicted discharge destination. The aim of this study was to assess the accuracy of this prediction. Methodology: This study included all patients transferred to transitional care from a stroke rehabilitation unit over eight years. Information regarding the predicted final discharge destination was collected from medical records, and the actual discharge destination was obtained from the transitional care registry. Results: Final destination prediction was equivalent between medical and multidisciplinary teams (κ = 0.87). However, only 60% of the predictions were accurate. Subgroup analysis, as measured by the Modified Barthel Index, suggested that functional gain was a better predictor of final destination. Other characteristics, such as age, sex and type of stroke, did not demonstrate good correlation with the final destination. Conclusion: Functional improvement, that is the Modified Barthel Index, is the best predictor of final destination after transitional care. [ABSTRACT FROM AUTHOR]