title: The impact of adjusting for reliability on hospital quality rankings in vascular surgery.
abstract: BACKGROUND
  Hospital quality in vascular surgery is often measured using mortality. We sought to determine whether adjusting mortality for statistical reliability changes hospital quality rankings for vascular surgery.
  
  
  METHODS
  Patients undergoing five common vascular surgery procedures (open and endovascular abdominal aortic aneurysm repair, carotid endarterectomy, lower extremity bypass, and aorto-femoral bypass) in the National Surgical Quality Improvement Project (NSQIP) in 2007 were identified (n = 14,559). For each hospital, we first calculated a ratio of observed to expected mortality (O-E ratio) using standard NSQIP techniques. We then adjusted these estimates for statistical noise using empirical Bayes methods, a technique known as reliability adjustment. We then compared rankings based on the standard O-E ratio to the rankings after reliability adjustment.
  
  
  RESULTS
  A total of 172 hospitals reported an average adjusted mortality rate of 2.4% for the five procedures, varying from 0% to 17%. After adjusting for statistical noise using reliability adjustment, hospital mortality was greatly diminished, varying only from 1.7% to 4.1%. This adjustment for reliability had a dramatic effect on hospital rankings. Overall, 43% of hospitals were reclassified into either a higher or lower quartile of performance using traditional methods of risk-adjustment. Fifty-one percent all hospitals in the "best" quartile of performance according to traditional O-E ratios are not classified in the "best" quartile after adjusting for statistical noise. Twenty-six percent of hospitals in the "worst" quartile were no longer classified as such after adjusting for noise.
  
  
  CONCLUSIONS
  Adjusting mortality for reliability reduces statistical noise and provides more stable estimates of hospital quality. Reliability adjustment should be standard for comparing hospital quality.
authors.affiliation: Department of Surgery, University of Michigan, Ann Arbor, MI, USA. nichosbo@umich.edu
authors.forename: Nicholas H
authors.initials: NH
authors.lastname: Osborne
authors.forename: Clifford Y
authors.initials: CY
authors.lastname: Ko
authors.forename: Gilbert R
authors.initials: GR
authors.lastname: Upchurch
authors.forename: Justin B
authors.initials: JB
authors.lastname: Dimick
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017544:Aortic Aneurysm, Abdominal / Q000401:mortality / Q000601:surgery; D001499:Bayes Theorem; D016894:Endarterectomy, Carotid / Q000401:mortality / Q000592:standards; D005260:Female; D017052:Hospital Mortality; D006761:Hospitals / Q000592:standards*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D058996:Quality Improvement; D011787:Quality of Health Care / Q000592:standards*; D012042:Registries; D015203:Reproducibility of Results; D016019:Survival Analysis; D014481:United States; D014656:Vascular Surgical Procedures / Q000401:mortality* / Q000592:standards*