title: Improving Medicare's Hospital Compare Mortality Model.
abstract: To improve the predictions provided by Medicare's Hospital Compare (HC) to facilitate better informed decisions regarding hospital choice by the public.
  
  
  
  Medicare claims on all patients admitted for Acute Myocardial Infarction between 2009 through 2011.
  
  
  
  Cohort analysis using a Bayesian approach, comparing the present assumptions of HC (using a constant mean and constant variance for all hospital random effects), versus an expanded model that allows for the inclusion of hospital characteristics to permit the data to determine whether they vary with attributes of hospitals, such as volume, capabilities, and staffing. Hospital predictions are then created using directly standardized estimates to facilitate comparisons between hospitals.
  
  
  
  Medicare fee-for-service claims.
  
  
  
  Our model that included hospital characteristics produces very different predictions from the current HC model, with higher predicted mortality rates at hospitals with lower volume and worse characteristics. Using Chicago as an example, the expanded model would advise patients against seeking treatment at the smallest hospitals with worse technology and staffing.
  
  
  
  To aid patients when selecting between hospitals, the Centers for Medicare and Medicaid Services (CMS) should improve the HC model by permitting its predictions to vary systematically with hospital attributes such as volume, capabilities, and staffing.
authors.affiliation: Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA.|The Department of Pediatrics, The University of Pennsylvania School of Medicine, Philadelphia, PA.|Department of Anesthesiology and Critical Care, The University of Pennsylvania School of Medicine, Philadelphia, PA.|Department of Health Care Management, The Wharton School, The University of Pennsylvania, Philadelphia, PA.|The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Jeffrey H
authors.initials: JH
authors.lastname: Silber
authors.affiliation: Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Ville A
authors.initials: VA
authors.lastname: Satopää
authors.affiliation: Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA.
authors.forename: Nabanita
authors.initials: N
authors.lastname: Mukherjee
authors.affiliation: Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Veronika
authors.initials: V
authors.lastname: Rockova
authors.affiliation: Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA.
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
authors.affiliation: Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA.
authors.forename: Alexander S
authors.initials: AS
authors.lastname: Hill
authors.affiliation: Center for Outcomes Research, The Children's Hospital of Philadelphia, Philadelphia, PA.|The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Orit
authors.initials: O
authors.lastname: Even-Shoshan
authors.affiliation: The Leonard Davis Institute of Health Economics, The University of Pennsylvania, Philadelphia, PA.|Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Paul R
authors.initials: PR
authors.lastname: Rosenbaum
authors.affiliation: Department of Statistics, The Wharton School, The University of Pennsylvania, Philadelphia, PA.
authors.forename: Edward I
authors.initials: EI
authors.lastname: George
mesh_terms: D000368:Aged; D001499:Bayes Theorem; D015331:Cohort Studies; D018588:Fee-for-Service Plans; D006302:Health Services Research; D017052:Hospital Mortality; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D006278:Medicare / Q000706:statistics & numerical data*; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000453:epidemiology / Q000401:mortality*; D014481:United States / Q000453:epidemiology
keywords: Bayesian statistics; Medicare quality of care; acute myocardial infarction; hospital compare