Validation of a Sampling Method to Collect Exposure Data for Central-Line–Associated Bloodstream Infections

Author:

Hammami Naïma,Mertens Karl,Overholser Rosanna,Goetghebeur Els,Catry Boudewijn,Lambert Marie-Laurence

Abstract

OBJECTIVESurveillance of central-line–associated bloodstream infections requires the labor-intensive counting of central-line days (CLDs). This workload could be reduced by sampling. Our objective was to evaluate the accuracy of various sampling strategies in the estimation of CLDs in intensive care units (ICUs) and to establish a set of rules to identify optimal sampling strategies depending on ICU characteristics.DESIGNAnalyses of existing data collected according to the European protocol for patient-based surveillance of ICU-acquired infections in Belgium between 2004 and 2012.SETTING AND PARTICIPANTSCLD data were reported by 56 ICUs in 39 hospitals during 364 trimesters.METHODSWe compared estimated CLD data obtained from weekly and monthly sampling schemes with the observed exhaustive CLD data over the trimester by assessing the CLD percentage error (ie, observed CLDs – estimated CLDs/observed CLDs). We identified predictors of improved accuracy using linear mixed models.RESULTSWhen sampling once per week or 3 times per month, 80% of ICU trimesters had a CLD percentage error within 10%. When sampling twice per week, this was >90% of ICU trimesters. Sampling on Tuesdays provided the best estimations. In the linear mixed model, the observed CLD count was the best predictor for a smaller percentage error. The following sampling strategies provided an estimate within 10% of the actual CLD for 97% of the ICU trimesters with 90% confidence: 3 times per month in an ICU with >650 CLDs per trimester or each Tuesday in an ICU with >480 CLDs per trimester.CONCLUSIONSampling of CLDs provides an acceptable alternative to daily collection of CLD data.Infect Control Hosp Epidemiol 2016;37:549–554

Publisher

Cambridge University Press (CUP)

Subject

Infectious Diseases,Microbiology (medical),Epidemiology

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