A Bayesian Approach to Aid in Formulary Decision Making: Incorporating Institution-Specific Cost-Effectiveness Data with Clinical Trial Results

Shelby D. Reed, Peter W. Dillingham, Andrew H. Briggs, David L. Veenstra and Sean D. Sullivan

Medical Decision Making, 2003, vol. 23, issue 3, 252-264

Abstract: Pharmacy and therapeutics committees commonly cite a lack of generalizability as a reason for not incorporating cost-effectiveness information into decision making. To address this concern, many committees undertake site-specific economic evaluations, which are often limited by small sample sizes and nonrandomized designs. We show how 2 complementary approaches were used to minimize these limitations in an economic evaluation of abciximab at 1 institution. Using a propensity score methodology, we selected patients who did not receive abciximab for the comparison cohort. Then, we adopted a Bayesian, hierarchical, random-effects model to integrate site-specific and clinical trial data. We applied the posterior distributions of effectiveness with local cost data in a traditional decision-analytic model. In 74% of the simulations, abciximab was cost-effective at 1 institution at the $50,000 per life year saved threshold, assuming a 50:50 split of patients undergoing coronary stenting and angioplasty. Among patients undergoing coronary stenting, the cost-effectiveness ratio of the addition of abciximab was at or below the $50,000 per life year saved threshold in 66.0% of the simulations.

Date: 2003
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Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:23:y:2003:i:3:p:252-264

DOI: 10.1177/0272989X03023003007

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