title: Comparing methods to calculate hospital-specific rates of early death or urgent readmission.
abstract: BACKGROUND
  Hospital readmissions are important patient outcomes that can be accurately captured with routinely collected administrative data. Hospital-specific readmission rates have been reported as a quality-of-care indicator. However, the extent to which these measures vary with different calculation methods is uncertain.
  
  
  METHODS
  We identified all discharges from Ontario hospitals from 2005 to 2010 and determined whether patients died or were urgently readmitted within 30 days. For each hospital, we calculated 4 distinct observed-to-expected ratios, estimating the expected number of events using different adjustments for confounders (age and sex v. complete) and different units of analysis (all admissions v. single admission per patient).
  
  
  RESULTS
  We included 3 148 648 admissions to hospital for 1 802 704 patients in 162 hospitals. Ratios adjusted for age and sex alone had the greatest variation. Within hospitals, ranges of the 4 ratios averaged 31% of the overall estimate. Readmission ratios adjusted for age and sex showed the lowest correlation (Spearman correlation coefficient 0.48-0.68). Hospital rankings based on the different measures had an average range of 47.4 (standard deviation 32.2) out of 162.
  
  
  CONCLUSIONS
  We found notable variation in rates of death or urgent readmission within 30 days based on the extent of adjustment for confounders and the unit of analysis. Slight changes in the methods used to calculate hospital-specific readmission rates influence their values and the consequent rankings of hospitals. Our results highlight the caution required when comparing hospital performance using rates of death or urgent readmission within 30 days.
authors.affiliation: Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada. carlv@ohri.ca
authors.forename: Carl
authors.initials: C
authors.lastname: van Walraven
authors.forename: Jenna
authors.initials: J
authors.lastname: Wong
authors.forename: Steven
authors.initials: S
authors.lastname: Hawken
authors.forename: Alan J
authors.initials: AJ
authors.lastname: Forster
mesh_terms: D005260:Female; D006801:Humans; D008297:Male; D009026:Mortality; D009864:Ontario / Q000453:epidemiology; D017063:Outcome Assessment, Health Care; D010359:Patient Readmission / Q000706:statistics & numerical data*; D019984:Quality Indicators, Health Care