Early, accurate prediction of discharge destination from the acute hospital assists individual patients and the wider hospital system. The Trauma Rehabilitation and Prediction Tool (TRaPT), developed using registry data, determines probability of inpatient rehabilitation discharge for patients with isolated lower limb fractures.
The aims of this study were: (1) to prospectively validatate the TRaPT, (2) to assess whether its performance could be improved by adding additional demographic data, and (3) to simplify it for use as a bedside tool.
This was a cohort, measurement-focused study.
Patients with isolated lower limb fractures (N=114) who were admitted to a major trauma center in Melbourne, Australia, were included. The participants' TRaPT scores were calculated from admission data. Performance of the TRaPT score alone, and in combination with frailty, weight-bearing status, and home supports, was assessed using measures of discrimination and calibration. A simplified TRaPT was developed by rounding the coefficients of variables in the original model and grouping age into 8 categories. Simplified TRaPT performance measures, including specificity, sensitivity, and positive and negative predictive values, were evaluated.
Prospective validation of the TRaPT showed excellent discrimination (C-statistic=0.90 [95% confidence interval=0.82, 0.97]), a sensitivity of 80%, and specificity of 94%. All participants able to weight bear were discharged directly home. Simplified TRaPT scores had a sensitivity of 80% and a specificity of 88%.
Generalizability may be limited given the compensation system that exists in Australia, but the methods used will assist in designing a similar tool in any population.
The TRaPT accurately predicted discharge destination for 80% of patients and may form a useful aid for discharge decision making, with the simplified version facilitating its use as a bedside tool.