title: The influence of the composition of the nursing staff on primary bloodstream infection rates in a surgical intensive care unit.
abstract: OBJECTIVE
  To determine the risk factors for acquisition of nosocomial primary bloodstream infections (BSIs), including the effect of nursing-staff levels, in surgical intensive care unit (SICU) patients.
  
  
  METHODS
  A nested case-control study.
  
  
  METHODS
  A 20-bed SICU in a 1,000-bed inner-city public hospital.
  
  
  METHODS
  28 patients with BSI (case-patients) were compared to 99 randomly selected patients (controls) hospitalized > or =3 days in the same unit.
  
  
  RESULTS
  Case- and control-patients were similar in age, severity of illness, and type of central venous catheter (CVC) used. Case-patients were significantly more likely than controls to be hospitalized during a 5-month period that had lower regular-nurse-to-patient and higher pool-nurse-to-patient ratios than during an 8-month reference period; to be in the SICU for a longer period of time; to be mechanically ventilated longer; to receive more antimicrobials and total parenteral nutrition; to have more CVC days; or to die. Case-patients had significantly lower regular-nurse-to-patient and higher pool-nurse-to-patient ratios for the 3 days before BSI than controls. In multivariate analyses, admission during a period of higher pool-nurse-to-patient ratio (odds ratio [OR]=3.8), total parenteral nutrition (OR=1.3), and CVC days (OR=1.1) remained independent BSI risk factors.
  
  
  CONCLUSIONS
  Our data suggest that, in addition to other factors, nurse staffing composition (ie, pool-nurse-to-patient ratio) may be related to primary BSI risk. Patterns in intensive care unit nurse staffing should be monitored to assess their impact on nosocomial infection rates. This may be particularly important in an era of cost containment and healthcare reform.
authors.affiliation: Laboratoire de Bactériologie et Hygiène, Hôpital Pitié-Salpêtrière, Paris, France.
authors.forename: J
authors.initials: J
authors.lastname: Robert
authors.forename: S K
authors.initials: SK
authors.lastname: Fridkin
authors.forename: H M
authors.initials: HM
authors.lastname: Blumberg
authors.forename: B
authors.initials: B
authors.lastname: Anderson
authors.forename: N
authors.initials: N
authors.lastname: White
authors.forename: S M
authors.initials: SM
authors.lastname: Ray
authors.forename: J
authors.initials: J
authors.lastname: Chan
authors.forename: W R
authors.initials: WR
authors.lastname: Jarvis
mesh_terms: D016022:Case-Control Studies; D003428:Cross Infection / Q000517:prevention & control*; D006779:Hospitals, Public; D006784:Hospitals, Teaching; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration*; D016015:Logistic Models; D008875:Middle Aged; D015999:Multivariate Analysis; D009741:Nursing Staff, Hospital / Q000458:organization & administration*; D016017:Odds Ratio; D010561:Personnel Staffing and Scheduling; D011182:Postoperative Care; D011446:Prospective Studies; D012307:Risk Factors; D018805:Sepsis / Q000453:epidemiology / Q000382:microbiology / Q000517:prevention & control*; D014481:United States / Q000453:epidemiology