Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods

被引:173
作者
O'Brien, BJ
Briggs, AH
机构
[1] McMaster Univ, Dept Clin Epidemiol & Biostat, Hamilton, ON L8S 4L8, Canada
[2] St Josephs Hosp, Ctr Evaluat Med, Hamilton, ON, Canada
[3] Univ Oxford, Dept Publ Hlth, Hlth Econ Res Ctr, Oxford, England
关键词
D O I
10.1191/0962280202sm304ra
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Cost-effectiveness analysis is now an integral part of health technology assessment and addresses the question of whether a new treatment or other health care program offers good value for money. In this paper we introduce the basic framework for decision making with cost-effectiveness data and then review recent developments in statistical methods for analysis of uncertainty when cost-effectiveness estimates are based on observed data from a clinical trial. Although much research has focused on methods for calculating confidence intervals for cost-effectiveness ratios using bootstrapping or Fieller's method, these calculations can be problematic with a ratio-based statistic where numerator and/or denominator can be zero. We advocate plotting the joint density of cost and effect differences, together with cumulative density plots known as cost-effectiveness acceptability curves (CEACs) to summarize the overall value-for-money of interventions. We also outline the net-benefit formulation of the cost-effectiveness problem and show that it has particular advantages over the standard incremental cost-effectiveness ratio formulation.
引用
收藏
页码:455 / 468
页数:14
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