Author:
Lin Michael Y.,Woeltje Keith F.,Khan Yosef M.,Hota Bala,Doherty Joshua A.,Borlawsky Tara B.,Stevenson Kurt B.,Fridkin Scott K.,Weinstein Robert A.,Trick William E.
Abstract
Objective.Central line–associated bloodstream infection (BSI) rates are a key quality metric for comparing hospital quality and safety. Traditional BSI surveillance may be limited by interrater variability. We assessed whether a computer-automated method of central line–associated BSI detection can improve the validity of surveillance.Design.Retrospective cohort study.Setting.Eight medical and surgical intensive care units (ICUs) in 4 academic medical centers.Methods.Traditional surveillance (by hospital staff) and computer algorithm surveillance were each compared against a retrospective audit review using a random sample of blood culture episodes during the period 2004–2007 from which an organism was recovered. Episode-level agreement with audit review was measured with κ statistics, and differences were assessed using the test of equal κ coefficients. Linear regression was used to assess the relationship between surveillance performance (κ) and surveillance-reported BSI rates (BSIs per 1,000 central line–days).Results.We evaluated 664 blood culture episodes. Agreement with audit review was significantly lower for traditional surveillance (κ [95% confidence interval (CI)] = 0.44 [0.37–0.51]) than computer algorithm surveillance (κ [95% CI] [0.52–0.64]; P = .001). Agreement between traditional surveillance and audit review was heterogeneous across ICUs (P = .001); furthermore, traditional surveillance performed worse among ICUs reporting lower (better) BSI rates (P = .001). In contrast, computer algorithm performance was consistent across ICUs and across the range of computer-reported central line–associated BSI rates.Conclusions.Compared with traditional surveillance of bloodstream infections, computer automated surveillance improves accuracy and reliability, making interfacility performance comparisons more valid.Infect Control Hosp Epidemiol 2014;35(12):1483–1490
Publisher
Cambridge University Press (CUP)
Subject
Infectious Diseases,Microbiology (medical),Epidemiology
Cited by
18 articles.
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