title: Health care-associated infections after major cancer surgery: temporal trends, patterns of care, and effect on mortality.
abstract: BACKGROUND
  Approximately 1.7 million individuals per year are affected with health care-associated infections (HAIs) in the United States. The authors examined trends in the incidence of HAI after major cancer surgery (MCS) and risk factors for HAI to describe the effects of HAI on mortality after MCS.
  
  
  METHODS
  Patients undergoing 1 of 8 MCS procedures within the Nationwide Inpatient Sample between 1999 and 2009 were identified (n = 2,502,686). Generalized linear regression models were used to estimate the impact of the primary predictors (procedure type, age, sex, race, insurance status, Charlson comorbidity index, hospital volume, and hospital bed size) on the odds of HAI and in-hospital mortality. Trends in incidence were evaluated with linear regression.
  
  
  RESULTS
  Overall, MCS-associated HAI incidence increased 2.7% per year (P < .001), whereas mortality decreased 1.3% per year (P < .001). Male gender (odds ratio [OR], 1.12, 95% confidence interval [CI], 1.10-1.14), advancing age (OR, 1.02; 95% CI, 1.02-1.02), black race (OR, 1.26; 95% CI, 1.21-1.31), ≥1 comorbidities (OR, from 1.08 [95% CI, 1.04-1.13] to 1.31 [95% CI, 1.27-1.35]), and nonprivate insurance (OR, from 1.18 [95% CI, 1.15-1.22] to 1.67 [95% CI, 1.59-1.76]) were associated with an increased odds of HAI on multivariable analysis. Conversely, increasing hospital volume was associated with lower odds of HAI (OR, 0.999; 95% CI, 0.99-0.99). Patients with MCS-associated HAI had increased odds of mortality (OR, 8.66; 95% CI, 8.51-8.82).
  
  
  CONCLUSIONS
  Between 1999 and 2009, the incidence of MCS-associated HAI events increased; however, HAI-associated mortality decreased. That said, significant disparities exist in the hospital and demographic attributes associated with MCS-associated HAI, with attendant health policy implications. Moreover, HAI remains detrimentally linked to mortality during hospitalization.
authors.affiliation: Vattikuti Urology Institute, Henry Ford Health System, Detroit, Michigan 48202, USA. jsammon79@gmail.com
authors.forename: Jesse
authors.initials: J
authors.lastname: Sammon
authors.forename: Vincent Q
authors.initials: VQ
authors.lastname: Trinh
authors.forename: Praful
authors.initials: P
authors.lastname: Ravi
authors.forename: Shyam
authors.initials: S
authors.lastname: Sukumar
authors.forename: Mai-Kim
authors.initials: MK
authors.lastname: Gervais
authors.forename: Shahrokh F
authors.initials: SF
authors.lastname: Shariat
authors.forename: Alexandre
authors.initials: A
authors.lastname: Larouche
authors.forename: Zhe
authors.initials: Z
authors.lastname: Tian
authors.forename: Simon P
authors.initials: SP
authors.lastname: Kim
authors.forename: Keith J
authors.initials: KJ
authors.lastname: Kowalczyk
authors.forename: Jim C
authors.initials: JC
authors.lastname: Hu
authors.forename: Mani
authors.initials: M
authors.lastname: Menon
authors.forename: Pierre I
authors.initials: PI
authors.lastname: Karakiewicz
authors.forename: Quoc-Dien
authors.initials: QD
authors.lastname: Trinh
authors.forename: Maxine
authors.initials: M
authors.lastname: Sun
mesh_terms: D000368:Aged; D015897:Comorbidity; D016001:Confidence Intervals; D003428:Cross Infection / Q000453:epidemiology* / Q000209:etiology / Q000401:mortality; D005260:Female; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000601:surgery*; D011183:Postoperative Complications / Q000453:epidemiology* / Q000209:etiology / Q000401:mortality; D012044:Regression Analysis; D014481:United States / Q000453:epidemiology