title: Improving the statistical approach to health care provider profiling.
abstract: 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.
authors.affiliation: Harvard Medical School, Boston, MA, USA.
authors.forename: C L
authors.initials: CL
authors.lastname: Christiansen
authors.forename: C N
authors.initials: CN
authors.lastname: Morris
mesh_terms: D001499:Bayes Theorem; D006302:Health Services Research / Q000379:methods*; D017052:Hospital Mortality; D006761:Hospitals / Q000145:classification / Q000592:standards*; D006801:Humans; D015233:Models, Statistical; D009518:New York; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D014481:United States