On the evaluation of drug benefits policy changes with longitudinal claims data: the policy maker's versus the clinician's perspective
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Cost containment in pharmaceutical-benefit plans are often controversially debated for their potential of unintended consequences on health and overall expenditures. Thorough evaluations are needed but hypotheses and design considerations are complex. Our objective is to provide a structured framework for the evaluation of drug-benefit changes using longitudinal claims data. Differential cost sharing (DCS) will serve as a recent example. Benefit-plan managers are mainly interested in the overall performance of their plan. In a policy model, any observed policy-related effects may be compared with what would have happened had the intervention not been implemented by extrapolating the pre-policy trend from the same patients. These estimates will reflect the global consequences of the policy maker's decision. However, such estimates represent summary effects of benefits and harms, separately identifiable in those complying with the intended policy and those not complying. Results from a policy model apply only to a specific policy implementation and tend to underestimate effects when non-compliance is high. Clinical-decision makers and patients, by contrast, are interested in the consequences of patients' actual compliance to the policy. A clinical model assesses the effects of DCS depending on the actual treatment in contrast to the treatment intended by the policy. However, this model must sometimes make, unprovable assumptions about the appropriate control of selection factors. In conclusion, both policy and clinical models should be tested with a clear understanding of their perspectives, hypotheses, and interpretations, using quasi-experimental time-series designs to evaluate the effects of drug cost-containment policies.
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