title: Patterns of hospital performance in acute myocardial infarction and heart failure 30-day mortality and readmission.
abstract: BACKGROUND
  In 2009, the Centers for Medicare & Medicaid Services is publicly reporting hospital-level risk-standardized 30-day mortality and readmission rates after acute myocardial infarction (AMI) and heart failure (HF). We provide patterns of hospital performance, based on these measures.
  
  
  RESULTS
  We calculated the 30-day mortality and readmission rates for all Medicare fee-for-service beneficiaries ages 65 years or older with a primary diagnosis of AMI or HF, discharged between July 2005 and June 2008. We compared weighted risk-standardized mortality and readmission rates across Hospital Referral Regions and hospital structural characteristics. The median 30-day mortality rate was 16.6% for AMI (range, 10.9% to 24.9%; 25th to 75th percentile, 15.8% to 17.4%; 10th to 90th percentile, 14.7% to 18.4%) and 11.1% for HF (range, 6.6% to 19.8%; 25th to 75th percentile, 10.3% to 12.0%; 10th to 90th percentile, 9.4% to 13.1%). The median 30-day readmission rate was 19.9% for AMI (range, 15.3% to 29.4%; 25th to 75th percentile, 19.5% to 20.4%; 10th to 90th percentile, 18.8% to 21.1%) and 24.4% for HF (range, 15.9% to 34.4%; 25th to 75th percentile, 23.4% to 25.6%; 10th to 90th percentile, 22.3% to 27.0%). We observed geographic differences in performance across the country. Although there were some differences in average performance by hospital characteristics, there were high and low hospital performers among all types of hospitals.
  
  
  CONCLUSIONS
  In a recent 3-year period, 30-day risk-standardized mortality rates for AMI and HF varied among hospitals and across the country. The readmission rates were particularly high.
authors.affiliation: Section of Cardiovascular Medicine and the Robert Wood Johnson Clinical Scholars Program, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA. harlan.krumholz@yale.edu
authors.forename: Harlan M
authors.initials: HM
authors.lastname: Krumholz
authors.forename: Angela R
authors.initials: AR
authors.lastname: Merrill
authors.forename: Eric M
authors.initials: EM
authors.lastname: Schone
authors.forename: Geoffrey C
authors.initials: GC
authors.lastname: Schreiner
authors.forename: Jersey
authors.initials: J
authors.lastname: Chen
authors.forename: Elizabeth H
authors.initials: EH
authors.lastname: Bradley
authors.forename: Yun
authors.initials: Y
authors.lastname: Wang
authors.forename: Yongfei
authors.initials: Y
authors.lastname: Wang
authors.forename: Zhenqiu
authors.initials: Z
authors.lastname: Lin
authors.forename: Barry M
authors.initials: BM
authors.lastname: Straube
authors.forename: Michael T
authors.initials: MT
authors.lastname: Rapp
authors.forename: Sharon-Lise T
authors.initials: SL
authors.lastname: Normand
authors.forename: Elizabeth E
authors.initials: EE
authors.lastname: Drye
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D018588:Fee-for-Service Plans / Q000706:statistics & numerical data; D040362:Geographic Information Systems; D006291:Health Policy; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006333:Heart Failure / Q000401:mortality*; D017052:Hospital Mortality; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D006278:Medicare / Q000706:statistics & numerical data; D009203:Myocardial Infarction / Q000401:mortality*; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology