title: Variation in hospital mortality rates with inpatient cancer surgery.
abstract: OBJECTIVE
  To elucidate clinical mechanisms underlying variation in hospital mortality after cancer surgery
  
  
  BACKGROUND
  : Thousands of Americans die every year undergoing elective cancer surgery. Wide variation in hospital mortality rates suggest opportunities for improvement, but these efforts are limited by uncertainty about why some hospitals have poorer outcomes than others.
  
  
  METHODS
  Using data from the 2006-2007 National Cancer Data Base, we ranked 1279 hospitals according to a composite measure of perioperative mortality after operations for bladder, esophagus, colon, lung, pancreas, and stomach cancers. We then conducted detailed medical record review of 5632 patients at 1 of 19 hospitals with low mortality rates (2.1%) or 30 hospitals with high mortality rates (9.1%). Hierarchical logistic regression analyses were used to compare risk-adjusted complication incidence and case-fatality rates among patients experiencing serious complications.
  
  
  RESULTS
  The 7.0% absolute mortality difference between the 2 hospital groups could be attributed to higher mortality from surgical site, pulmonary, thromboembolic, and other complications. The overall incidence of complications was not different between hospital groups [21.2% vs 17.8%; adjusted odds ratio (OR) = 1.34, 95% confidence interval (CI): 0.93-1.94]. In contrast, case-fatality after complications was more than threefold higher at high mortality hospitals than at low mortality hospitals (25.9% vs 13.6%; adjusted OR = 3.23, 95% CI: 1.56-6.69).
  
  
  CONCLUSIONS
  Low mortality and high mortality hospitals are distinguished less by their complication rates than by how frequently patients die after a complication. Strategies for ensuring the timely recognition and effective management of postoperative complications will be essential in reducing mortality after cancer surgery.
authors.affiliation: *Center for Healthcare Outcomes and Policy and Department of Surgery, University of Michigan Medical School, Ann Arbor †Remedy Informatics, Chicago, IL; and ‡Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor.
authors.forename: Sandra L
authors.initials: SL
authors.lastname: Wong
authors.forename: ShaʼShonda L
authors.initials: SL
authors.lastname: Revels
authors.forename: Huiying
authors.initials: H
authors.lastname: Yin
authors.forename: Andrew K
authors.initials: AK
authors.lastname: Stewart
authors.forename: Andrea
authors.initials: A
authors.lastname: McVeigh
authors.forename: Mousumi
authors.initials: M
authors.lastname: Banerjee
authors.forename: John D
authors.initials: JD
authors.lastname: Birkmeyer
mesh_terms: D000368:Aged; D002423:Cause of Death; D003082:Colectomy / Q000401:mortality / Q000706:statistics & numerical data; D015897:Comorbidity; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006761:Hospitals / Q000145:classification / Q000706:statistics & numerical data; D006801:Humans; D015994:Incidence; D007297:Inpatients / Q000706:statistics & numerical data*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D009369:Neoplasms / Q000401:mortality* / Q000473:pathology / Q000601:surgery*; D016017:Odds Ratio; D011183:Postoperative Complications / Q000453:epidemiology / Q000401:mortality; D011647:Puerto Rico / Q000453:epidemiology; D013510:Pulmonary Surgical Procedures / Q000401:mortality / Q000706:statistics & numerical data; D058996:Quality Improvement / Q000639:trends; D011787:Quality of Health Care; D015996:Survival Rate; D014481:United States / Q000453:epidemiology
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