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Sampling for Collection of Central Line–Day Denominators in Surveillance of Healthcare-Associated Bloodstream Infections

  • R. M. Klevens (a1), J. I. Tokars (a1), J. Edwards (a1), T. Horan (a1) and National Nosocomial Infections Surveillance (NNIS) System...

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.

Copyright

Corresponding author

Centers for Disease Control and Prevention, 1600 Clifton Road, MS A-24, Atlanta, GA30333 (rmk2@cdc.gov)

References

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