title: Probabilistic Measurement of Central Line-Associated Bloodstream Infections.
abstract: OBJECTIVE
  To develop a probabilistic method for measuring central line-associated bloodstream infection (CLABSI) rates that reduces the variability associated with traditional, manual methods of applying CLABSI surveillance definitions.
  
  
  METHODS
  Multicenter retrospective cohort study of bacteremia episodes among patients hospitalized in adult patient-care units; the study evaluated presence of CLABSI.
  
  
  METHODS
  Hospitals that used SafetySurveillor software system (Premier) and who also reported to the Centers for Disease Control and Prevention's National Healthcare Safety Network (NHSN).
  
  
  METHODS
  Patients were identified from a stratified sample from all eligible blood culture isolates from all eligible hospital units to generate a final set with an equal distribution (ie, 20%) from each unit type. Units were divided a priori into 5 major groups: medical intensive care unit, surgical intensive care unit, medical-surgical intensive care unit, hematology unit, or general medical wards.
  
  
  METHODS
  Episodes were reviewed by 2 experts, and a selection of discordant reviews were re-reviewed. Data were joined with NHSN data for hospitals for in-plan months. A predictive model was created; model performance was assessed using the c statistic in a validation set and comparison with NHSN reported rates for in-plan months.
  
  
  RESULTS
  A final model was created with predictors of CLABSI. The c statistic for the final model was 0.75 (0.68-0.80). Rates from regression modeling correlated better with expert review than NHSN-reported rates.
  
  
  CONCLUSIONS
  The use of a regression model based on the clinical characteristics of the bacteremia outperformed traditional infection preventionist surveillance compared with an expert-derived reference standard. Infect.
authors.affiliation: 1Department of Internal Medicine,Rush University Medical Center,Chicago,Illinois.
authors.forename: Bala
authors.initials: B
authors.lastname: Hota
authors.affiliation: 2Division of Healthcare Quality Promotion,National Center for Emerging and Zoonotic Diseases,Centers for Disease Control and Prevention,Atlanta,Georgia.
authors.forename: Paul
authors.initials: P
authors.lastname: Malpiedi
authors.affiliation: 2Division of Healthcare Quality Promotion,National Center for Emerging and Zoonotic Diseases,Centers for Disease Control and Prevention,Atlanta,Georgia.
authors.forename: Scott K
authors.initials: SK
authors.lastname: Fridkin
authors.affiliation: 3Premier Research Institute,Washington,DC.
authors.forename: John
authors.initials: J
authors.lastname: Martin
authors.affiliation: 4Collaborative Research Unit,Cook County Health and Hospitals System,Chicago,Illinois.
authors.forename: William
authors.initials: W
authors.lastname: Trick
mesh_terms: D016470:Bacteremia / Q000453:epidemiology*; D019985:Benchmarking / Q000379:methods*; D055499:Catheter-Related Infections / Q000453:epidemiology* / Q000382:microbiology; D002405:Catheterization, Central Venous / Q000009:adverse effects; D003428:Cross Infection / Q000453:epidemiology* / Q000382:microbiology; D016208:Databases, Factual; D006757:Hospital Units; D006801:Humans; D017053:Infection Control; D015337:Multicenter Studies as Topic; D012044:Regression Analysis; D012189:Retrospective Studies; D014481:United States / Q000453:epidemiology