Medical profiling: improving standards and risk adjustments using hierarchical models

被引:65
作者
Burgess, JF
Christiansen, CL
Michalak, SE
Morris, CN
机构
[1] Dept Vet Affairs, Management Sci Grp, Bedford, MA 01730 USA
[2] Harvard Univ, Sch Med, Cambridge, MA 02138 USA
[3] Harvard Univ, Pilgrim Hlth Care, Cambridge, MA 02138 USA
[4] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA
基金
美国国家科学基金会;
关键词
profiling standards; hierarchical models; regression-to-the-mean; risk adjustment;
D O I
10.1016/S0167-6296(99)00034-X
中图分类号
F [经济];
学科分类号
02 ;
摘要
The conclusions from a profile analysis to identify performance extremes can be affected substantially by the standards and statistical methods used and by the adequacy of risk adjustment. Medically meaningful standards are proposed to replace common statistical standards. Hierarchical regression methods can handle several levels of random variation, make risk adjustments for the providers' case-mix differences, and address the proposed standards. These methods determine probabilities needed to make meaningful profiles of medical units based on standards set by all appropriate parties. Published by Elsevier Science B.V. JEL classification: I18; C11; L15.
引用
收藏
页码:291 / 309
页数:19
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