ORGANIZATION: Premera Blue Cross Pharmacy and Therapeutics Committee (P&T). Premera is a 1.6 million member regional commercial health plan in the Pacific Northwest of the U.S. PROBLEM OR ISSUE ADDRESSED: Need to determine formulary status of Exenatide (Byetta), a recently marketed novel biologic agent for the treatment of Type 2 Diabetes. GOALS: To test the usefulness of manufacturer-provided disease-based cost-effectiveness models in helping formulary decision makers to determine the value and appropriate place in therapy for a new drug used to treat a chronic disease, when long-term outcomes data for the new product are unavailable due to the time required for long term sequelae of diabetes to be observed in clinical trials. OUTCOMES ITEMS USED IN THE DECISION: Reduction in hemoglobin A1c levels (A1c) and body mass index (BMI) observed in patients receiving exenatide. IMPLEMENTATION STRATEGY: Using the AMCP Format for Formulary Submission (v2.1), Premera requested detailed information from Amylin regarding the clinical and economic value of exenatide in a commercial health insurance population. Upon learning that Premera was requesting disease-based cost-effectiveness modeling, Amylin purchased Web-based access to the CORE Diabetes Model (CDM) for Premera staff. Amylin personnel arranged training in the use of the model by CORE but no one from Amylin participated in planning the modeling exercise, choosing the input data and assumptions, or specifying the analytic scenarios. An informal Premera work group evaluated various model scenarios and included a summary of the results in the formulary recommendations to the P&T Committee. RESULTS: The model predicted reduced long-term treatment costs in obese patients, driven by 11% decrease in cardiovascular disease burden over a 30-year period. The incremental cost-effectiveness ratio (ICER) for adding exenatide over 3 years was $35,000/QALY. Using a 30-year horizon, ICER values were $13,000/QALY versus insulin, $32,000 versus generic glyburide and $16,000 versus no additional treatment. Exenatide dominated pioglitazone. By comparison, the 30-year ICER for exenatide versus insulin in the non-obese cohort was $33,000. This is a large longitudinal extrapolation based on relatively short term trials, but it did help to confirm the hypothesis that the drug would benefit a subgroup of obese patients. The P&T committee found this information useful and accepted staff recommendation to add exenatide to formulary, with prior authorization restrictions; however, due to limitations in the logistics of implementation, the restrictions did not limit use to obese patients. LESSONS LEARNED: Predicting long-term clinical outcomes of a new drug from the results of short-term trials is challenging. Good disease-based pharmacoeconomic models help payers project costs, identify populations most likely to benefit from therapy, and perhaps craft restrictions that improve the potential for use of the drug in these populations, reducing the numbers needed to treat and improving incremental cost-effectiveness. In this context, a Format-compliant economic model can facilitate communication between manufacturer and health plan about the drug’s value.