Median-based incremental cost-effectiveness ratio (ICER)

被引:71
作者
Bang H. [1 ]
Zhao H. [2 ]
机构
[1] Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA
[2] Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A and M Health Science Center, College Station, TX
关键词
Cost-effectiveness analysis; Cost-effectiveness plane; Mean cost; Median cost;
D O I
10.1080/15598608.2012.695571
中图分类号
学科分类号
摘要
Cost-effectiveness analysis (CEA) is a type of economic evaluation that examines the costs and health outcomes of alternative strategies and has been extensively applied in health sciences. The incremental cost-effectiveness ratio (ICER), which represents the additional cost of one unit of outcome gained by one strategy compared with another, has become a popular methodology in CEA. Despite its popularity, limited attention has been paid to summary measures other than the mean for summarizing cost as well as effectiveness in the context of CEA. Although some apparent advantages of other central tendency measures, such as median for cost data that are often highly skewed, are well understood, thus far, the median has rarely been considered in the ICER. In this paper, we propose the median-based ICER, along with inferential procedures, and suggest that mean-and median-based ICERs be considered together as complementary tools in CEA for informed decision making, acknowledging the pros and cons of each. If the mean-and median-based CEAs are concordant, we may feel reasonably confident about the cost-effectiveness of an intervention, but if they provide different results, our confidence may need to be adjusted accordingly, pending further evidence. © 2012 Grace Scientific Publishing, LLC.
引用
收藏
页码:428 / 442
页数:14
相关论文
共 45 条
[1]  
Bang H., Tsiatis A.A., Median regression with censored cost data, Biometrics, 58, 3, pp. 643-649, (2002)
[2]  
Black W.C., The CE plane: A graphic representation of cost-effectiveness, Medical Decision Making, 10, 3, pp. 212-214, (1990)
[3]  
Bloomfield D.J., Krahn M.D., Neogi T., Panzarella T., Smith T.J., Warde P., Willan A.R., Ernst S., Moore M.J., Neville A., Tannock I.F., Economic evaluation of chemotherapy with mitoxantrone plus prednisone for symptomatic hormone-resistant prostate cancer: Based on a Canadian randomized tial with palliative end points, Journal of Clinical Oncology, 16, 6, pp. 2272-2279, (1998)
[4]  
Blumenschein K., Johannesson M., Yokoyama K.K., Freeman P.R., Hypothetical versus real willingness to pay in the health care sector: Results from a field experiment, Journal of Health Economics, 20, 3, pp. 441-457, (2001)
[5]  
Briggs A., Economic evaluation and clinical trials: Size matters: The need for greater power in cost analyses poses an ethical dilemma, Br. Med. J., 321, pp. 1362-1363, (2000)
[6]  
Brookmeyer R., Median survival time, Encyclopedia of Biostatistics, (2005)
[7]  
Chaudhary M.A., Stearns S.C., Estimating confidence intervals for cost-effectiveness ratios: An example from a randomized trial, Statistics in Medicine, 15, 13, pp. 1447-1458, (1996)
[8]  
Dinh P., Zhou X.-H., Nonparametric statistical methods for cost-effectiveness analyses, Biometrics, 62, 2, pp. 576-588, (2006)
[9]  
Drummond M.F., Sculpher M.J., Torrance G.W., O'Brien B.J., Stoddart G.L., Methods for the Economic Evaluation of Health Care Programmes, (2005)
[10]  
Duan N., Smearing estimate: A nonparametric retransformation method, JASA, 78, pp. 605-610, (1983)