League Tables for Hospital Comparisons

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.

[1]  D. Nerenz,et al.  Quality measures and sociodemographic risk factors: to adjust or not to adjust. , 2014, JAMA.

[2]  A. Zaslavsky,et al.  Quality reporting that addresses disparities in health care. , 2014, JAMA.

[3]  John D. Kalbfleisch,et al.  On Monitoring Outcomes of Medical Providers , 2013 .

[4]  Brian S. Caffo,et al.  Multilevel functional data analysis , 2013 .

[5]  David J. Spiegelhalter,et al.  Statistical methods for healthcare regulation: rating, screening and surveillance , 2012 .

[6]  Stephen E. Fienberg,et al.  Discussion on the paper by Spiegelhalter, Sherlaw-Johnson, Bardsley, Blunt, Wood and Grigg , 2012 .

[7]  Thomas A. Louis,et al.  Statistical Issues in Assessing Hospital Performance , 2012 .

[8]  L. Goldman,et al.  The accuracy of present-on-admission reporting in administrative data. , 2011, Health services research.

[9]  Logistic versus hierarchical modeling: an analysis of a statewide inpatient sample. , 2011, Journal of the American College of Surgeons.

[10]  David J. Spiegelhalter,et al.  The Identification of “Unusual” Health-Care Providers From a Hierarchical Model , 2011 .

[11]  Thomas A Louis,et al.  Percentile‐based empirical distribution function estimates for performance evaluation of healthcare providers , 2011, Journal of the Royal Statistical Society. Series C, Applied statistics.

[12]  K. Coombes,et al.  What information should be required to support clinical "omics" publications? , 2011, Clinical chemistry.

[13]  S. Fienberg.  Bayesian Models and Methods in Public Policy and Government Settings , 2011, 1108.2177.

[14]  P. Rosenbaum,et al.  The Hospital Compare mortality model and the volume-outcome relationship. , 2010, Health services research.

[15]  Gabriel J. Escobar,et al.  Effect of Choice of Estimation Method on Inter-Hospital Mortality Rate Comparisons , 2010, Medical care.

[16]  S. Normand,et al.  Hospital volume and 30-day mortality for three common medical conditions. , 2010, The New England journal of medicine.

[17]  Hao Helen Zhang,et al.  Variable Selection for Semiparametric Mixed Models in Longitudinal Studies , 2010, Biometrics.

[18]  Jill P Mesirov,et al.  Accessible Reproducible Research , 2010, Science.

[19]  The Safety of Anesthetics: The National Halothane Study , 2010 .

[20]  Thomas A Louis,et al.  Effective communication of standard errors and confidence intervals. , 2008, Biostatistics.

[21]  Thomas A. Louis,et al.  Ranking USRDS provider specific SMRs from 1998–2001 , 2008, Health Services and Outcomes Research Methodology.

[22]  D. Greiner.  Causal Inference in Civil Rights Litigation , 2008 .

[23]  Sharon-Lise T Normand,et al.  Comparison of “Risk-Adjusted” Hospital Outcomes , 2008, Circulation.

[24]  Yingye Zheng,et al.  Integrating the predictiveness of a marker with its performance as a classifier. , 2007, American journal of epidemiology.

[25]  Xihong Lin.  Estimation using penalized quasilikelihood and quasi-pseudo-likelihood in Poisson mixed models , 2007, Lifetime data analysis.

[26]  Peter J. Diggle,et al.  Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty. , 2007 .

[27]  D. Ruppert,et al.  Spatially Adaptive Bayesian Penalized Splines With Heteroscedastic Errors , 2007 .

[28]  Sharon-Lise T. Normand,et al.  Statistical and Clinical Aspects of Hospital Outcomes Profiling , 2007, 0710.4622.

[29]  Andrew Gelman.  Bayesian Checking of the Second Levels of Hierarchical Models. Comment.. , 2007 .

[30]  Thomas A. Louis,et al.  Flexible distributions for triple-goal estimates in two-stage hierarchical models , 2006, Comput. Stat. Data Anal..

[31]  Jeffrey S. Morris,et al.  Wavelet‐based functional mixed models , 2006, Journal of the Royal Statistical Society. Series B, Statistical methodology.

[32]  Thomas A Louis,et al.  Loss Function Based Ranking in Two-Stage, Hierarchical Models. , 2006, Bayesian analysis.

[33]  Geert Verbeke,et al.  Multiple Imputation for Model Checking: Completed‐Data Plots with Missing and Latent Data , 2005, Biometrics.

[34]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[35]  Sharon-Lise T. Normand,et al.  Analytic Methods for Constructing Cross-Sectional Profiles of Health Care Providers , 2000, Health Services and Outcomes Research Methodology.

[36]  D. McCaffrey,et al.  Propensity score estimation with boosted regression for evaluating causal effects in observational studies. , 2004, Psychological methods.

[37]  Sharon-Lise T. Normand,et al.  Selection of Related Multivariate Means , 2003 .

[38]  S. Normand,et al.  The volume-outcome relationship: from Luft to Leapfrog. , 2003, The Annals of thoracic surgery.

[39]  Bradley P. Carlin,et al.  Bayesian measures of model complexity and fit , 2002 .

[40]  Thomas A Louis,et al.  Uncertainty in Rank Estimation: Implications for Value-Added Modeling Accountability Systems , 2002, Journal of educational and behavioral statistics : a quarterly publication sponsored by the American Educational Research Association and the American Statistical Association.

[41]  J. Birkmeyer,et al.  Hospital Volume and Surgical Mortality in the United States , 2002 .

[42]  A Milstein,et al.  Selective referral to high-volume hospitals: estimating potentially avoidable deaths. , 2000, JAMA.

[43]  A. Ash,et al.  R2: a useful measure of model performance when predicting a dichotomous outcome. , 1999, Statistics in medicine.

[44]  T. Louis,et al.  Triple‐goal estimates in two‐stage hierarchical models , 1998 .

[45]  L. Iezzoni.  Assessing Quality Using Administrative Data , 1997, Annals of Internal Medicine.

[46]  S. Zeger,et al.  A Smooth Nonparametric Estimate of a Mixing Distribution Using Mixtures of Gaussians , 1996 .

[47]  Harvey Goldstein,et al.  League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance , 1996 .

[48]  L. Iezzoni.  Risk Adjustment for Measuring Healthcare Outcomes , 1994 .

[49]  Thomas J. Tomberlin,et al.  PREDICTING ACCIDENT FREQUENCIES FOR DRIVERS CLASSIFIED BY TWO FACTORS , 1988 .

[50]  Arthur P. Dempster,et al.  Employment Discrimination and Statistical Science , 1988 .

[51]  Blumberg Ms.  Comments on HCFA hospital death rate statistical outliers. Health Care Financing Administration. , 1987 .

[52]  D. Freedman,et al.  Regression Models for Adjusting the 1980 Census , 1986 .

[53]  Joseph B. Kadane,et al.  Estimating the Population in a Census Year 1980 and beyond , 1985 .

[54]  B. Efron.  Regression and ANOVA with Zero-One Data: Measures of Residual Variation , 1978 .