Methods:

Studies that use observational, longitudinal data provide an opportunity for research to focus on questions not able to be addressed by randomized control trials. Medicare collects information on millions of beneficiaries, which when linked, provides data on inpatients, outpatients, and prescription use. Medicare data for comparative effectiveness research is challenging; as with all administrative data, it is not possible to capture every factor that contributes to prescribing decisions, and patients are not randomly assigned to treatments. Current data sets include Part D event data, beneficiary summary data, beneficiary annual summary data, Part D drug characteristics, pharmacy characteristics, and prescriber characteristics. Limitations to such data include potential for selection biases, and variations such as geographic variation and confounding. Therefore, analyses based on simple comparisons are not preferred. Refining policies for time to data release, provision of additional data elements, and linkage with more beneficiary level information would improve the value and usability of these data. Improving the transparency and reproducibility of findings, and potential open access for qualified stakeholders are also important policy considerations. Data needs must be reconciled with current policies and goals.