Christiansen C L, Morris C N
Harvard Medical School, Boston, MA, USA.
Ann Intern Med. 1997 Oct 15;127(8 Pt 2):764-8. doi: 10.7326/0003-4819-127-8_part_2-199710151-00065.
This paper reviews and compares existing statistical methods for profiling health care providers. It recommends improvements that are based on the use of better statistical models and the adoption of more realistic, medically based criteria for judging the performance of health care providers. Unlike most profiling methods, the proposed hierarchical models allow the probability of acceptable provider performance to be calculated; thus, they can answer such questions as, "What is the probability that a given hospital's true mortality rate for cardiac surgery patients exceeded 3.33% last year?" The commonly encountered problems of regression-to-the-mean bias and small caseloads can be handled by using hierarchical models to extract more information from profiling data.
本文回顾并比较了现有的医疗服务提供者绩效评估统计方法。它建议基于使用更好的统计模型以及采用更现实的、基于医学的标准来评判医疗服务提供者的绩效进行改进。与大多数绩效评估方法不同,所提出的分层模型能够计算出医疗服务提供者达到可接受绩效的概率;因此,它们能够回答诸如“去年某家特定医院心脏手术患者的实际死亡率超过3.33%的概率是多少?”这样的问题。通过使用分层模型从绩效评估数据中提取更多信息,可以处理常见的均值回归偏差和病例数少的问题。