title: Cost of bloodstream infections.
abstract: BACKGROUND
  Hospital-acquired bloodstream infections (BSIs) are relatively rare but do not occur randomly. This suggests that unobserved confounding factors can bias estimates of BSI-associated incremental costs of care. Compared with previous studies, this analysis used a large sample size for greater precision, actual cost-accounting data, and case matching combined with bounding estimates to correct for bias.
  
  
  METHODS
  Data from 1,355,647 admissions during 69 months in 55 hospitals were collected from a large population database. BSIs were identified by the Nosocomial Infection Marker, a well-validated, electronic, laboratory-based marker used for automatic infection surveillance. Costs were obtained by matching laboratory data with hospital accounting system calculations and converted to 2006 US dollars.
  
  
  RESULTS
  Of 58,376 presumed nosocomial infections, 12,578 (21.6%) were identified as BSIs. More than 50% of BSIs occurred within the first week of hospitalization and 80% during the first 2 weeks. Various analyses resulted in the following estimates of BSI-associated incremental costs: basic regression analysis, $19,643 (P < .0001; 95% confidence interval [CI]: $9026-$30,260); excluding infections occurring after day 14, $19,427 (P < .001; 95% CI: $8867-$29,986); excluding infections occurring after day 7, $20,600 (P < .001; 95% CI: $10,123-$30,077); controlling for other nosocomial infections, $12,774 (P < .001; 95% CI: $6257-$19,290); and controlling for length of stay, $5534 (P < .012; 95% CI: $1282-$9785).
  
  
  CONCLUSIONS
  Even when intentionally underestimated, BSI-associated increased costs are substantial. True costs of BSIs are likely to be between $10,000 and $20,000. More research is needed to explore how controlling BSI costs may affect the cost of inpatient care.
authors.affiliation: Department of Health Care Organization and Policy, University of Alabama at Birmingham, Birmingham, AL 35294-0022, USA. mkilgore@uab.edu
authors.forename: Meredith
authors.initials: M
authors.lastname: Kilgore
authors.forename: Stephen
authors.initials: S
authors.lastname: Brossette
mesh_terms: D000407:Alabama / Q000453:epidemiology; D016001:Confidence Intervals; D015986:Confounding Factors, Epidemiologic; D017281:Cost of Illness; D003365:Costs and Cost Analysis; D003428:Cross Infection / Q000191:economics* / Q000401:mortality; D016208:Databases, Factual; D017721:Hospital Costs / Q000706:statistics & numerical data*; D006801:Humans; D017053:Infection Control / Q000191:economics; D007362:Intensive Care Units / Q000191:economics*; D007902:Length of Stay; D012042:Registries; D012044:Regression Analysis; D018805:Sepsis / Q000191:economics* / Q000401:mortality