Statistical determination of cost-effectiveness frontier based on net health benefits

✍ Scribed by Eugene M. Laska; Morris Meisner; Carole Siegel; Joseph Wanderling

• Publisher: John Wiley and Sons
• Year: 2002
• Tongue: English
• Weight: 208 KB
• Volume: 11
• Category: Article
• ISSN: 1057-9230
• DOI: 10.1002/hec.659

✦ Synopsis

Abstract

Statistical methods are given for producing a cost‐effectiveness frontier for an arbitrary number of programs. In the deterministic case, the net health benefit (NHB) decision rule is optimal; the rule funds the program with the largest positive NHB at each λ, the amount a decision‐maker is willing to pay for an additional unit of effectiveness. For bivariate normally distributed cost and effectiveness variables and a specified λ, a statistical procedure is presented, based on the method of constrained multiple comparisons with the best (CMCB), for determining the program with the largest NHB. A one‐tailed t test is used to determine if the NHB is positive. To obtain a statistical frontier in the λ‐NHB plane, we develop a method to produce the region in which each program has the largest NHB, by pivoting a CMCB confidence interval. A one‐sided version of Fieller's theorem is used to determine the region where the NHB of each program is positive. At each λ, the pointwise error rate is bounded by a prespecified α. Upper bounds on the familywise error rate, the probability of an error at any value of λ, are given. The methods are applied to a hypothetical clinical trial of antipsychotic agents. Copyright © 2002 John Wiley & Sons, Ltd.