Use of the false discovery rate when comparing multiple health care providers

被引:74
作者
Jones, Hayley E. [1 ]
Ohlssen, David I. [1 ]
Spiegelhalter, David J. [1 ]
机构
[1] MRC Biostat Unit, Inst Publ Hlth, Cambridge CB2 2SR, England
基金
英国医学研究理事会;
关键词
provider profiling; multiple testing; false discovery rate (FDR); Bonferroni correction; funnel plot; mortality rates;
D O I
10.1016/j.jclinepi.2007.04.017
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
Objective: Comparisons of the performance of multiple health care providers are often based on hypothesis tests, those with resulting P-values below some critical threshold being identified as potentially extreme. Because of the multiple testing involved, the classical P-value threshold of, say, 0.05 may not be considered strict enough, as it will tend to lead to too many "false positives." However, we argue that the commonly used Bonferroni-corrected threshold is in general too strict for the problem in hand. The purpose of this article is to demonstrate a suitable alternative thresholding procedure that is already well established in other fields. Study Design and Setting: The suggested procedure involves control of an error measure called the "false discovery rate" (FDR). We present a worked example involving a comparison of risk-adjusted mortality rates following heart surgery in New York State hospitals during 2000-2002. It is shown that the FDR critical threshold lines can be drawn on a "funnel plot," providing a simple graphical presentation of the results. Results: The FDR procedure identified more providers as potentially extreme than the Bonferrom correction, while maintaining control of an intuitively sensible error measure. Conclusion: Control of the FDR offers a simple guideline to determining where to draw critical thresholds when comparing multiple health care providers. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:232 / 240
页数:9
相关论文
共 29 条
[1]  
AGUILAR O, 1998, CASE STUDIES BAYESIA, V4, P287
[2]   Adjusting for multiple testing - when and how? [J].
Bender, R ;
Lange, S .
JOURNAL OF CLINICAL EPIDEMIOLOGY, 2001, 54 (04) :343-349
[3]  
Benjamini Y, 2001, ANN STAT, V29, P1165
[4]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[5]   MULTIPLE SIGNIFICANCE TESTS - THE BONFERRONI METHOD .10. [J].
BLAND, JM ;
ALTMAN, DG .
BRITISH MEDICAL JOURNAL, 1995, 310 (6973) :170-170
[6]   Medical profiling: improving standards and risk adjustments using hierarchical models [J].
Burgess, JF ;
Christiansen, CL ;
Michalak, SE ;
Morris, CN .
JOURNAL OF HEALTH ECONOMICS, 2000, 19 (03) :291-309
[7]  
Campbell MJ., 1999, MED STAT COMMONSENSE, V3rd
[8]   Quantitative refinements for comparisons of institutional performance [J].
Deely, JJ ;
Smith, AFM .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 1998, 161 :5-12
[9]  
Feinstein AR, 2002, PRINCIPLES MED STAT
[10]   Thresholding of statistical maps in functional neuroimaging using the false discovery rate [J].
Genovese, CR ;
Lazar, NA ;
Nichols, T .
NEUROIMAGE, 2002, 15 (04) :870-878