Central line-associated bloodstream infection surveillance outside the intensive care unit: a multicenter survey.

ABSTRACT

OBJECTIVE: The success of central line-associated bloodstream infection (CLABSI) prevention programs in intensive care units (ICUs) has led to the expansion of surveillance at many hospitals. We sought to compare non-ICU CLABSI (nCLABSI) rates with national reports and describe methods of surveillance at several participating US institutions. DESIGN AND SETTING: An electronic survey of several medical centers about infection surveillance practices and rate data for non-ICU patients. PARTICIPANTS: Ten tertiary care hospitals. METHODS: In March 2011, a survey was sent to 10 medical centers. The survey consisted of 12 questions regarding demographics and CLABSI surveillance methodology for non-ICU patients at each center. Participants were also asked to provide available rate and device utilization data. RESULTS: Hospitals ranged in size from 238 to 1,400 total beds (median, 815). All hospitals reported using Centers for Disease Control and Prevention (CDC) definitions. Denominators were collected by different means counting patients with central lines every day (5 hospitals), indirectly estimating on the basis of electronic orders ([Formula see text]), or another automated method ([Formula see text]). Rates of nCLABSI ranged from 0.2 to 4.2 infections per 1,000 catheter-days (median, 2.5). The national rate reported by the CDC using 2009 data from the National Healthcare Surveillance Network was 1.14 infections per 1,000 catheter-days. CONCLUSIONS: Only 2 hospitals were below the pooled CLABSI rate for inpatient wards; all others exceeded this rate. Possible explanations include differences in average central line utilization or hospital size in the impact of certain clinical risk factors notably absent from the definition and in interpretation and reporting practices. Further investigation is necessary to determine whether the national benchmarks are low or whether the hospitals surveyed here represent a selection of outliers.