Prediction of return to work by rehabilitation professionals

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Abstract
Rehabilitation therapists made predictions of return to work for 57 patients evaluated prior to beginning a work-hardening program. These predictions, along with 14 specific demographic, injury, and physical function measures were entered into a stepwise discriminant analysis to develop a predictive model for return to work. Therapists correctly predicted the eventual return to work for 47 (73.7%) of the 57 subjects. Therapist prediction was the most powerful variable in the model, explaining 29% of the variance (p≤.0001). Only two other variables, self-report of pain severity and injury type, contributed significantly to the prediction model, accounting respectively for 12% and 9% of the variance (p's<.05). These data highlight the predictive acuity of rehabilitation therapists and suggest that the process involved in formulating clinical predictions merits further study. The findings also suggest that weighing information such as self-report of pain severity and injury type might further enhance the practitioner's ability to predict return to work.