League Tables for Hospital Comparisons

Sharon Lise T. Normand, Arlene S. Ash, Stephen E. Fienberg, Thérèse A. Stukel, Jessica Utts, Thomas A. Louis

Research output: Contribution to journalReview articlepeer-review

7 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)21-50
Number of pages30
JournalAnnual Review of Statistics and Its Application
StatePublished - Jun 1 2016


  • Bayesian inference
  • Hierarchical model
  • Low information
  • Observational data
  • Profiling
  • Risk adjustment

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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