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The article compares two statistical prospective hospital reimbursement models: the diagnosis-related group (DRG) model and the prospective individualized reimbursement (PIR) model. Both models are applied to the same variables from the same data set, a random sample of 10,000 hospital discharges in Maryland in 1983. For comparative purposes, the two statistical models are allowed to differ only in their treatment of the predictive variable, "patient age." The criteria of comparison and results (DRG and PIR, respectively) are: number of patient groups required (469 and 337); accuracy of prediction of length of stay (38 percent and 45 percent of the total variation is explained by the models); correction for sampling bias (0 and 2.4 percent additional explained variation); and accuracy of prediction of total charges ($526 and $262 average error per patient).