title: Associations of hospital characteristics with nosocomial pneumonia after cardiac surgery can impact on standardized infection rates.
abstract: To identify hospital-level factors associated with post-cardiac surgical pneumonia for assessing their impact on standardized infection rates (SIRs), we studied 43 691 patients in a cardiac surgery registry (2001-2011) in 16 hospitals. In a logistic regression model for pneumonia following cardiac surgery, associations with hospital characteristics were quantified with adjustment for patient characteristics while allowing for clustering of patients by hospital. Pneumonia rates varied from 0·7% to 12·4% across hospitals. Seventy percent of variability in the pneumonia rate was attributable to differences in hospitals in their long-term rates with the remainder attributable to within-hospital differences in rates over time. After adjusting for patient characteristics, the pneumonia rate was found to be higher in hospitals with more registered nurses (RNs)/100 intensive-care unit (ICU) admissions [adjusted odds ratio (aOR) 1·2, P = 0·006] and more RNs/available ICU beds (aOR 1·4, P < 0·001). Other hospital characteristics had no significant association with pneumonia. SIRs calculated on the basis of patient characteristics alone differed substantially from the same rates calculated on the basis of patient characteristics and the hospital characteristic of RNs/100 ICU admissions. Since SIRs using patient case-mix information are important for comparing rates between hospitals, the additional allowance for hospital characteristics can impact significantly on how hospitals compare.
authors.affiliation: Department of Epidemiology and Preventive Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne,VIC,Australia.
authors.forename: M
authors.initials: M
authors.lastname: Sanagou
authors.affiliation: Department of Epidemiology and Preventive Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne,VIC,Australia.
authors.forename: K
authors.initials: K
authors.lastname: Leder
authors.affiliation: Department of Epidemiology and Preventive Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne,VIC,Australia.
authors.forename: A C
authors.initials: AC
authors.lastname: Cheng
authors.affiliation: Department of Intensive Care Medicine,The Alfred Hospital,Melbourne,VIC,Australia.
authors.forename: D
authors.initials: D
authors.lastname: Pilcher
authors.affiliation: Department of Epidemiology and Preventive Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne,VIC,Australia.
authors.forename: C M
authors.initials: CM
authors.lastname: Reid
authors.affiliation: Department of Epidemiology and Preventive Medicine,Faculty of Medicine,Nursing and Health Sciences,Monash University,Melbourne,VIC,Australia.
authors.forename: R
authors.initials: R
authors.lastname: Wolfe
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001315:Australia / Q000453:epidemiology; D006348:Cardiac Surgical Procedures / Q000009:adverse effects*; D003428:Cross Infection / Q000453:epidemiology* / Q000382:microbiology / Q000821:virology; D006760:Hospitalization / Q000706:statistics & numerical data; D006761:Hospitals / Q000706:statistics & numerical data*; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D009520:New Zealand / Q000453:epidemiology; D011014:Pneumonia / Q000453:epidemiology* / Q000382:microbiology / Q000821:virology
keywords: Pneumonia