League Tables for Hospital Comparisons

Author:

Normand Sharon-Lise T.1,Ash Arlene S.2,Fienberg Stephen E.3,Stukel Thérèse A.4,Utts Jessica5,Louis Thomas A.6

Affiliation:

1. Department of Health Care Policy, Harvard Medical School, and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115;

2. Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts 01605;

3. Department of Statistics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213;

4. Institute for Clinical Evaluative Sciences, Toronto, Ontario M4N 3M5, Canada, and the Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario M5T 3M6, Canada, and Dartmouth Institute for Health Policy and Clinical Practice, Hanover, New Hampshire 03766;

5. Department of Statistics, University of California, Irvine, California 92697;

6. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205;

Abstract

We review statistical methods for estimating and interpreting league tables used to infer hospital quality with a primary focus on methods for partitioning variation into two types: (a) that associated with within-hospital variation for a homogeneous group of patients and (b) that produced by between-hospital variation. We discuss the types of covariates included in the model, hierarchical and nonhierarchical logistic regression models for conducting inferences in a low-information context and their associated trade-offs, and the role of hospital volume. We use all-cause mortality rates for US hospitals to illustrate concepts and methods.

Publisher

Annual Reviews

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

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