title: Are mortality rates for different operations related?: implications for measuring the quality of noncardiac surgery.
abstract: BACKGROUND
  Except in cardiac surgery, measuring quality with procedure-specific mortality rates is unreliable because of small sample sizes at individual hospitals. Statistical power can be improved by combining mortality data from multiple operations. We sought to determine whether this approach would still be useful in understanding performance with individual procedures.
  
  
  METHODS
  We studied 11 high-risk operations performed in the national Medicare population (1996-1999). For each operation, we calculated 1) the risk-adjusted mortality rate for the procedure and 2) the mortality rate with up to 10 other operations combined ("other" mortality). To test for an association between these mortality rates, we calculated the correlation coefficient adjusting for random variation. We then collapsed hospitals into quintiles of other mortality and calculated procedure-specific mortality rates within each of these quintiles.
  
  
  RESULTS
  Mortality with specific operations was modestly correlated with other mortality: coefficients ranged from 0.14 for pneumonectomy to 0.35 for esophagectomy. Despite small to moderate correlations, other mortality was a good predictor of procedure-specific mortality for 10 of the 11 operations. Pancreatic resection had the strongest relationship, with procedure-specific mortality rates at hospitals in the worst quintile of other mortality 3-fold higher than those in the best quintile (15.2% vs. 6.3%, P < 0.001). Pneumonectomy had the weakest relationship with no significant relationship between other mortality and procedure-specific mortality.
  
  
  CONCLUSIONS
  Hospitals with low mortality rates for 1 operation tend to have lower mortality rates for other operations. These relationships suggest that different operations share important structures and processes of care related to performance. Future efforts aimed at predicting procedure-specific performance should consider incorporating data from other operations at that hospital.
authors.affiliation: Michigan Surgical Collaborative for Outcomes Research and Evaluation (M-SCORE), Department of Surgery, University of Michigan, Ann Arbor, Michigan, USA. Justin.B.Dimick@Dartmouth.edu
authors.forename: Justin B
authors.initials: JB
authors.lastname: Dimick
authors.forename: Douglas O
authors.initials: DO
authors.lastname: Staiger
authors.forename: John D
authors.initials: JD
authors.lastname: Birkmeyer
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D008297:Male; D020379:Risk Adjustment / Q000379:methods; D013503:Surgery Department, Hospital