The authors discuss a system that describes the resources needed to treat different subgroups of the population under age 65, based on burden of disease. It is based on 173 conditions, each with up to 3 severity levels, and contains models that combine prospective diagnoses with retrospectively determined elements. They used data from four different payers and standardized the cost of most services. Analyses showed that the models are replicable, are reasonably accurate, explain costs across payers, and reduce rewards for biased selection. A prospective model with additional payments for birth episodes and for serious problems in newborns would be an effective risk adjuster for Medicaid programs.
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