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dc.contributor.authorTan, C.
dc.contributor.authorLoo, G.
dc.contributor.authorPua, Y.
dc.contributor.authorChong, H.
dc.contributor.authorYeo, W.
dc.contributor.authorOng, P.
dc.contributor.authorLo, N.
dc.contributor.authorAllison, Garry
dc.identifier.citationTan, C. and Loo, G. and Pua, Y. and Chong, H. and Yeo, W. and Ong, P. and Lo, N. et al. 2014. Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool. Physiotherapy. 100 (2): pp. 176-181.

Objective: To explore the use of the Risk Assessment and Predictor Tool (RAPT) as a pre-operative tool to predict postoperative discharge destination and length of stay for patients undergoing total knee replacement (TKR) in Singapore. Participants and setting: A cohort of 569 patients undergoing primary TKR at the Singapore General Hospital were recruited prospectively from November 2009 to June 2010. Intervention: All patients completed a modified RAPT questionnaire pre-operatively, and underwent standard clinical pathway guidelines for TKR throughout the study. Main outcome measures: Actual discharge destination (ADDest) and length of stay (LOS). Design: Total RAPT score and preferred discharge destination (PDD) were recorded pre-operatively, while ADDest and LOS were obtained immediately after discharge. Multivariable logistic regression and multivariable regression analysis were used to determine whether the RAPT items and score could predict the discharge outcomes. Results: Total RAPT score was a significant predictor of LOS for patients following TKR (R = 0.24, P < 0.001); the higher the RAPT score, the longer the LOS. Total RAPT score was also a significant predictor of actual discharge to home [odds ratio (OR) 2.32, 95% confidence interval (CI) 1.11 to 4.85]. PDD was a significant predictor for LOS (R = 0.22, P < 0.001) and ADDest (R = 0.33, P < 0.001). Patients who chose to be discharged home were more likely to be directly discharged home (OR 9.79, 95% CI 5.07 to 18.89, P < 0.001). Conclusion: Total RAPT score and PDD were significant predictors of ADDest and LOS for patients following TKR in Singapore. The ability to predict discharge outcomes following TKR could assist caregivers, healthcare professionals and administrators in optimising care and resource allocations for patients.

dc.publisherElsevier Ltd
dc.subjectTotal knee replacement
dc.subjectLength of stay
dc.subjectRisk Assessment and Predictor Tool
dc.titlePredicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
dc.typeJournal Article
curtin.departmentSchool of Physiotherapy
curtin.accessStatusFulltext not available

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