A risk-adjusted measure of hospitalization rates for evaluating community mental health program performance

The authors describe the use of risk-adjusted hospitalization rates to measure community mental health treatment outcomes. The risk adjustment involves comparing rates of hospitalization subsequent to treatment with rates of hospitalization prior to treatment. The research uses a probabilistic methodology that reliably estimates caseload overlap by comparing the distribution of the dates of birth observed in data sets to the distribution of dates of birth in the general population. Findings indicate that risk-adjusted hospitalization rates are substantially different than unadjusted rates. Half of the community programs in one state consistently achieved positive outcomes in four consecutive years; other programs had mixed results or no change.