R M Klevens1, J I Tokars, J Edwards, T Horan. 1. Division 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.
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.
Authors: Crystal H Son; Titus L Daniels; Janet A Eagan; Michael B Edmond; Neil O Fishman; Thomas G Fraser; Mini Kamboj; Lisa L Maragakis; Sapna A Mehta; Trish M Perl; Michael S Phillips; Connie S Price; Thomas R Talbot; Stephen J Wilson; Kent A Sepkowitz Journal: Infect Control Hosp Epidemiol Date: 2012-07-24 Impact factor: 3.254
Authors: José Francisco García-Rodríguez; Hortensia Álvarez-Díaz; Laura Vilariño-Maneiro; María Virginia Lorenzo-García; Ana Cantón-Blanco; Patricia Ordoñez-Barrosa; Ana Isabel Mariño-Callejo; Pascual Sesma-Sánchez Journal: BMC Infect Dis Date: 2013-09-24 Impact factor: 3.090