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...
| Publicado en: | JAMA: Journal of the American Medical Association Vol. 304; no. 18; pp. 2035 - 2042 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
American Medical Association
11/10/2010
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104945621&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104945621 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00987484 AMA jtl: JAMA: Journal of the American Medical Association issn: 00987484 maglogo: N pubinfo: dt: 11/10/2010 vid: 304 iid: 18 pid: 30 pub: American Medical Association place: Chicago, Illinois artinfo: ui: 104945621 NLM21063013 2010861152 10.1001/jama.2010.1637 NLM21063013 104945621 ppf: 2035 ppct: 7 formats: tig: 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 refInfo: holdings: @attributes: islocal: N |
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