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

Published online by Cambridge University Press:  21 June 2016

R. M. Klevens ,
J. I. Tokars ,
J. Edwards ,
T. Horan  and
National Nosocomial Infections Surveillance (NNIS) System
R. M. Klevens*
Affiliation:
National Center for Infectious Diseases, Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
J. I. Tokars
Affiliation:
National Center for Infectious Diseases, Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
J. Edwards
Affiliation:
National Center for Infectious Diseases, Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
T. Horan
Affiliation:
National Center for Infectious Diseases, Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia
*
Centers for Disease Control and Prevention, 1600 Clifton Road, MS A-24, Atlanta, GA30333 (rmk2@cdc.gov)
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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.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 27 , Issue 4 , April 2006 , pp. 338 - 342
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2006

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