Quality of traditional surveillance for public reporting of nosocomial bloodstream infection rates.

Context: Central line-associated bloodstream infection (BSI) rates, determined by infection preventionists using the Centers for Disease Control and Prevention (CDC) surveillance definitions, are increasingly published to compare the quality of patient care delivered by hospitals. However, such comp...

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Publicado en:JAMA: Journal of the American Medical Association Vol. 304; no. 18; pp. 2035 - 2042
Autores principales: Lin MY, Hota B, Khan YM, Woeltje KF, Borlawsky TB, Doherty JA, Stevenson KB, Weinstein RA, Trick WE, Lin, Michael Y, Hota, Bala, Khan, Yosef M, Woeltje, Keith F, Borlawsky, Tara B, Doherty, Joshua A, Stevenson, Kurt B, Weinstein, Robert A, Trick, William E
Formato: research Journal Article
Publicado: American Medical Association 11/10/2010
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 11/10/2010
      vid: 304
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      pub: American Medical Association
      place: Chicago, Illinois
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        104945621
        NLM21063013
        2010861152
        10.1001/jama.2010.1637
        NLM21063013
        104945621
      ppf: 2035
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        atl: Quality of traditional surveillance for public reporting of nosocomial bloodstream infection rates.
      aug:
        au:
          Lin MY
          Hota B
          Khan YM
          Woeltje KF
          Borlawsky TB
          Doherty JA
          Stevenson KB
          Weinstein RA
          Trick WE
          Lin, Michael Y
          Hota, Bala
          Khan, Yosef M
          Woeltje, Keith F
          Borlawsky, Tara B
          Doherty, Joshua A
          Stevenson, Kurt B
          Weinstein, Robert A
          Trick, William E
        affil: Section of Infectious Diseases, Department of Medicine, Rush University Medical Center, Chicago, Illinois 60612, USA
      sug:
        subj:
          Bacteremia Epidemiology
          Catheter-Related Infections Epidemiology
          Cross Infection Epidemiology
          Population Surveillance
          Quality Assurance
          Academic Medical Centers Statistics and Numerical Data
          Algorithms
          Bacteremia Classification
          Catheter-Related Infections Classification
          Centers for Disease Control and Prevention (U.S.)
          Prospective Studies
          Cross Infection Classification
          Human
          Infection Control
          Intensive Care Units Statistics and Numerical Data
          Reproducibility of Results
          Retrospective Design
          Single-Blind Studies
          Nomenclature
          United States
      ab: Context: Central line-associated bloodstream infection (BSI) rates, determined by infection preventionists using the Centers for Disease Control and Prevention (CDC) surveillance definitions, are increasingly published to compare the quality of patient care delivered by hospitals. However, such comparisons are valid only if surveillance is performed consistently across institutions.Objective: To assess institutional variation in performance of traditional central line-associated BSI surveillance.Design, Setting, and Participants: We performed a retrospective cohort study of 20 intensive care units among 4 medical centers (2004-2007). Unit-specific central line-associated BSI rates were calculated for 12-month periods. Infection preventionists, blinded to study participation, performed routine prospective surveillance using CDC definitions. A computer algorithm reference standard was applied retrospectively using criteria that adapted the same CDC surveillance definitions.Main Outcome Measures: Correlation of central line-associated BSI rates as determined by infection preventionist vs the computer algorithm reference standard. Variation in performance was assessed by testing for institution-dependent heterogeneity in a linear regression model.Results: Forty-one unit-periods among 20 intensive care units were analyzed, representing 241,518 patient-days and 165,963 central line-days. The median infection preventionist and computer algorithm central line-associated BSI rates were 3.3 (interquartile range [IQR], 2.0-4.5) and 9.0 (IQR, 6.3-11.3) infections per 1000 central line-days, respectively. Overall correlation between computer algorithm and infection preventionist rates was weak (ρ = 0.34), and when stratified by medical center, point estimates for institution-specific correlations ranged widely: medical center A: 0.83; 95% confidence interval (CI), 0.05 to 0.98; P = .04; medical center B: 0.76; 95% CI, 0.32 to 0.93; P = .003; medical center C: 0.50, 95% CI, -0.11 to 0.83; P = .10; and medical center D: 0.10; 95% CI -0.53 to 0.66; P = .77. Regression modeling demonstrated significant heterogeneity among medical centers in the relationship between computer algorithm and expected infection preventionist rates (P < .001). The medical center that had the lowest rate by traditional surveillance (2.4 infections per 1000 central line-days) had the highest rate by computer algorithm (12.6 infections per 1000 central line-days).Conclusions: Institutional variability of infection preventionist rates relative to a computer algorithm reference standard suggests that there is significant variation in the application of standard central line-associated BSI surveillance definitions across medical centers. Variation in central line-associated BSI surveillance practice may complicate interinstitutional comparisons of publicly reported central line-associated BSI rates.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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