A Bayesian approach to aid in formulary decision making: incorporating institution-specific cost-effectiveness data with clinical trial results.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Reed, SD; Dillingham, PW; Briggs, AH; Veenstra, DL; Sullivan, SD

Published Date

  • May 2003

Published In

Volume / Issue

  • 23 / 3

Start / End Page

  • 252 - 264

PubMed ID

  • 12809323

Pubmed Central ID

  • 12809323

Electronic International Standard Serial Number (EISSN)

  • 1552-681X

International Standard Serial Number (ISSN)

  • 0272-989X

Digital Object Identifier (DOI)

  • 10.1177/0272989x03023003007

Language

  • eng