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Infect Control Hosp Epidemiol. 2006 Apr;27(4):338-42. Epub 2006 Mar 28.

Sampling for collection of central line-day denominators in surveillance of healthcare-associated bloodstream infections.

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  • 1Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA 30333, USA. rmk2@cdc.gov

Abstract

OBJECTIVE:

To determine the feasibility of estimating the number of central line-days at a hospital from a sample of months or individual days in a year, for surveillance of healthcare-associated bloodstream infections.

DESIGN:

We used data reported to the National Nosocomial Infections Surveillance system in the adult and pediatric intensive care unit component for 1995-2003 and data from a sample of hospitals' daily counts of device use for 12 consecutive months. We calculated the percentile error as the central line-associated bloodstream infection percentile based on rates per line-days minus the percentile based on rates per estimated line-days.

SETTING AND PARTICIPANTS:

A total of 247 hospitals were used for sampling whole months and 12 hospitals were used for sampling individual days.

RESULTS:

For a 1-month sample of central line-days data, the median percentile error was 3.3 (75th percentile, 7.9; 90th percentile, 15.4). The percentile error decreased with an increase in the number of months sampled. For a 3-month sample, the median percentile error was 1.4 (75th percentile, 4.3; 95th percentile, 8.3). Sampling individual days throughout the year yielded lower percentile errors than sampling an equivalent fraction of whole months. With 1 weekday sampled per week, the median percentile error ranged from 0.65 to 1.40, and the 90th percentile ranged from 2.8 to 5.0. Thus, for 90% of units, collecting data on line-days once a week provides an estimate within +/-5 percentile points of the true line-day rate.

CONCLUSION:

Sample-based estimates of central line-days can yield results that are acceptable for surveillance of healthcare-associated bloodstream infections.

[PubMed - indexed for MEDLINE]
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