• Marie-Josée Sirois, André Lavoie, and Clermont E Dionne.
• Research Center of the Centre hospitalier affilié universitaire de Québec, Quebec City, Canada.
• Am J Phys Med Rehabil. 2007 Jul 1;86(7):563-73.

ObjectivesTo conduct a population-based survey among trauma survivors on accessibility to rehabilitation services in metropolitan, urban, and rural areas in Quebec (Canada), we attempted to use trauma registries as a sampling frame of subjects discharged to rehabilitation. Discharge destinations were inaccurate in many registries, preventing straightforward identification of the survey subjects. Using the best registry data, we aimed to identify predictors of rehabilitation discharge and to use them to specify a reliable sampling frame for the survey.DesignA logistic predictive model of rehabilitation discharge was developed. This model was applied to data from metropolitan, urban, and rural trauma centers to identify all subjects predicted to be discharged to a rehabilitation facility.ResultsAge, acute-care length of stay, injury-severity score, lower-limb injuries, and seven other predictors were included in the model that generated an area under the ROC curve (AUC) of 0.83 and a classification accuracy of 76.6%. The metropolitan, urban, and rural frames were slightly different. They included, respectively, 808, 798, and 929 subjects.ConclusionsThe procedure helped us bypass largely inaccurate data from trauma registries. The sampling frames reflected severely injured trauma survivors who were likely to have been referred to postacute rehabilitation.

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