Loading…
A Bayesian Approach to Aid in Formulary Decision Making: Incorporating Institution-Specific Cost-Effectiveness Data with Clinical Trial Results
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 an...
Saved in:
Published in: | Medical decision making 2003-05, Vol.23 (3), p.252-264 |
---|---|
Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | 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. |
---|---|
ISSN: | 0272-989X 1552-681X |
DOI: | 10.1177/0272989X03023003007 |