title: Judging hospitals by severity-adjusted mortality rates: the influence of the severity-adjustment method.
abstract: OBJECTIVE
  This research examined whether judgments about a hospital's risk-adjusted mortality performance are affected by the severity-adjustment method.
  
  
  METHODS
  Data came from 100 acute care hospitals nationwide and 11880 adults admitted in 1991 for acute myocardial infarction. Ten severity measures were used in separate multivariable logistic models predicting in-hospital death. Observed-to-expected death rates and z scores were calculated with each severity measure for each hospital.
  
  
  RESULTS
  Unadjusted mortality rates for the 100 hospitals ranged from 4.8% to 26.4%. For 32 hospitals, observed mortality rates differed significantly from expected rates for 1 or more, but not for all 10, severity measures. Agreement between pairs of severity measures on whether hospitals were flagged as statistical mortality outliers ranged from fair to good. Severity measures based on medical records frequently disagreed with measures based on discharge abstracts.
  
  
  CONCLUSIONS
  Although the 10 severity measures agreed about relative hospital performance more often than would be expected by chance, assessments of individual hospital mortality rates varied by different severity-adjustment methods.
authors.affiliation: Division of General Medicine and Primary Care, Harvard Medical School, Beth Israel Hospital, Boston, MA 02215, USA.
authors.forename: L I
authors.initials: LI
authors.lastname: Iezzoni
authors.forename: A S
authors.initials: AS
authors.lastname: Ash
authors.forename: M
authors.initials: M
authors.lastname: Shwartz
authors.forename: J
authors.initials: J
authors.lastname: Daley
authors.forename: J S
authors.initials: JS
authors.lastname: Hughes
authors.forename: Y D
authors.initials: YD
authors.lastname: Mackiernan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007256:Information Systems; D007902:Length of Stay; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009026:Mortality; D009203:Myocardial Infarction / Q000401:mortality*; D017063:Outcome Assessment, Health Care; D011237:Predictive Value of Tests; D011336:Probability; D011787:Quality of Health Care; D012720:Severity of Illness Index; D014481:United States