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. 2013 Mar;34(3):221-8.
doi: 10.1086/669515. Epub 2013 Jan 24.

Evaluating the accuracy of sampling to estimate central line-days: simplification of the National Healthcare Safety Network surveillance methods

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Evaluating the accuracy of sampling to estimate central line-days: simplification of the National Healthcare Safety Network surveillance methods

Nicola D Thompson et al. Infect Control Hosp Epidemiol. 2013 Mar.

Abstract

Objective: To evaluate the accuracy of weekly sampling of central line-associated bloodstream infection (CLABSI) denominator data to estimate central line-days (CLDs).

Design: Obtained CLABSI denominator logs showing daily counts of patient-days and CLD for 6-12 consecutive months from participants and CLABSI numerators and facility and location characteristics from the National Healthcare Safety Network (NHSN).

Setting and participants: Convenience sample of 119 inpatient locations in 63 acute care facilities within 9 states participating in the Emerging Infections Program.

Methods: Actual CLD and estimated CLD obtained from sampling denominator data on all single-day and 2-day (day-pair) samples were compared by assessing the distributions of the CLD percentage error. Facility and location characteristics associated with increased precision of estimated CLD were assessed. The impact of using estimated CLD to calculate CLABSI rates was evaluated by measuring the change in CLABSI decile ranking.

Results: The distribution of CLD percentage error varied by the day and number of days sampled. On average, day-pair samples provided more accurate estimates than did single-day samples. For several day-pair samples, approximately 90% of locations had CLD percentage error of less than or equal to ±5%. A lower number of CLD per month was most significantly associated with poor precision in estimated CLD. Most locations experienced no change in CLABSI decile ranking, and no location's CLABSI ranking changed by more than 2 deciles.

Conclusions: Sampling to obtain estimated CLD is a valid alternative to daily data collection for a large proportion of locations. Development of a sampling guideline for NHSN users is underway.

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