Hostname: page-component-8448b6f56d-wq2xx Total loading time: 0 Render date: 2024-04-19T09:42:32.070Z Has data issue: false hasContentIssue false

Surveillance for central-line–associated bloodstream infections: Accuracy of different sampling strategies

Published online by Cambridge University Press:  29 August 2018

Elani Kourkouni*
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Georgia Kourlaba
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Evangelia Chorianopoulou
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Grammatiki-Christina Tsopela
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Ioannis Kopsidas
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Irene Spyridaki
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
Sotirios Tsiodras
Affiliation:
4th Department of Medicine National and Kapodistrian University of Athens Medical School, Athens, Greece
Emmanuel Roilides
Affiliation:
3rd Department of Pediatrics, Aristotle University, Hippokration Hospital, Thessaloniki, Greece
Susan Coffin
Affiliation:
Division of Infectious Diseases, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
Theoklis E. Zaoutis
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece
for the PHIG investigators
Affiliation:
Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece 4th Department of Medicine National and Kapodistrian University of Athens Medical School, Athens, Greece 3rd Department of Pediatrics, Aristotle University, Hippokration Hospital, Thessaloniki, Greece Division of Infectious Diseases, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
*
Author for correspondence: Elani Kourkouni MSc, Center for Clinical Epidemiology and Outcomes Research (CLEO), Nonprofit Civil Partnership, Athens, Greece. E-mail: elenkourkouni@hotmail.com

Abstract

Background

Active daily surveillance of central-line days (CLDs) in the assessment of rates of central-line–associated bloodstream infections (CLABSIs) is time-consuming and burdensome for healthcare workers. Sampling of denominator data is a method that could reduce the time necessary to conduct active surveillance.

Objective

To evaluate the accuracy of various sampling strategies in the estimation of CLABSI rates in adult and pediatric units in Greece.

Methods

Daily denominator data were collected across Greece for 6 consecutive months in 33 units: 11 adult units, 4 pediatric intensive care units (PICUs), 12 neonatal intensive care units (NICUs), and 6 pediatric oncology units. Overall, 32 samples were evaluated using the following strategies: (1) 1 fixed day per week, (2) 2 fixed days per week, and (3) 1 fixed week per month. The CLDs for each month were estimated as follows: (number of sample CLDs/number of sampled days) × 30. The estimated CLDs were used to calculate CLABSI rates. The accuracy of the estimated CLABSI rates was assessed by calculating the percentage error (PE): [(observed CLABSI rates − estimated CLABSI rates)/observed CLABSI rates].

Results

Compared to other strategies, sampling over 2 fixed days per week provided the most accurate estimates of CLABSI rates for all types of units. Percentage of estimated CLABSI rates with PE ≤±5% using the strategy of 2 fixed days per week ranged between 74.6% and 88.7% in NICUs. This range was 79.4%–94.1% in pediatric onology units, 62.5%–91.7% in PICUs, and 80.3%–92.4% in adult units. Further evaluation with intraclass correlation coefficients and Bland-Altman plots indicated that the estimated CLABSI rates were reliable.

Conclusion

Sampling over 2 fixed days per week provides a valid alternative to daily collection of CLABSI denominator data. Adoption of such a monitoring method could be an important step toward better and less burdensome infection control and prevention.

Type
Original Article
Copyright
© 2018 by The Society for Healthcare Epidemiology of America. All rights reserved 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Burke, JP. Infection control—a problem for patient safety. N Engl J Med 2003;348:651656.Google Scholar
2. O’Grady, NP, Alexander, M, Burns, LA, et al. Guidelines for the prevention of intravascular catheter-related infections. Am J Infect Control 2011;39:S1S34.Google Scholar
3. Fridkin, SK, Olmsted, RN. Meaningful measure of performance: a foundation built on valid, reproducible findings from surveillance of health care-associated infections. Am J Infect Control 2011;39:8790.Google Scholar
4. Gikas, A, Pediaditis, J, Papadakis, JA, et al. Prevalence study of hospital-acquired infections in 14 Greek hospitals: planning from the local to the national surveillance level. J Hosp Infect 2002;50:269275.Google Scholar
5. Siempos, II, Kopterides, P, Tsangaris, I, Dimopoulou, I, Armaganidis, AE. Impact of catheter-related bloodstream infections on the mortality of critically ill patients: a meta-analysis. Crit Care Med 2009;37:22832289.Google Scholar
6. Goudie, A, Dynan, L, Brady, PW, Rettiganti, M. Attributable cost and length of stay for central line-associated bloodstream infections. Pediatrics 2014;133:e1525e1532.Google Scholar
7. Dudeck, MA, Edwards, JR, Allen-Bridson, K, et al. National Healthcare Safety Network report, data summary for 2013, device-associated module. Am J Infect Control 2015;43:206221.Google Scholar
8. Hammami, N, Mertens, K, Overholser, R, Goetghebeur, E, Catry, B, Lambert, ML. Validation of a sampling method to collect exposure data for central-line-associated bloodstream infections. Infect Control Hosp Epidemiol 2016;37:549554.Google Scholar
9. Klevens, RM, Tokars, JI, Edwards, J, Horan, T, National Nosocomial Infections Surveillance Study Group. Sampling for collection of central line-day denominators in surveillance of healthcare-associated bloodstream infections. Infect Control Hosp Epidemiol 2006;27:338342.Google Scholar
10. Thompson, ND, Edwards, JR, Bamberg, W, et al. Evaluating the accuracy of sampling to estimate central line-days: simplification of the National Healthcare Safety Network surveillance methods. Infect Control Hosp Epidemiol 2013;34:221228.Google Scholar
11. Thompson, ND, Edwards, JR, Bamberg, W, et al. Estimating central line-associated bloodstream infection incidence rates by sampling of denominator data: A prospective, multicenter evaluation. Am J Infect Control 2015;43:853856.Google Scholar
12. Shelly, MA, Concannon, C, Dumyati, G. Device use ratio measured weekly can reliably estimate central-line days for central line-associated bloodstream infection rates. Infect Control Hosp Epidemiol 2011;32:727730.Google Scholar
13. O’Leary, EN, van Santen, KL, Webb, AK, Pollock, DA, Edwards, JR, Srinivasan, A. Uptake of Antibiotic stewardship programs in US acute care hospitals: findings from the 2015 National Healthcare Safety Network annual hospital survey. Clin Infect Dis 2017;65:17481750.Google Scholar
14. O’Riordan, M, Fitzpatrick, F. The impact of economic recession on infection prevention and control. J Hosp Infect 2015;89:340345.Google Scholar
15. Vandijck, D, Cleemput, I, Hellings, J, Vogelaers, D. Infection prevention and control strategies in the era of limited resources and quality improvement: a perspective paper. Austral Crit Care 2013;26:154157.Google Scholar
16. CDC. National Healthcare Safety Network (NHSN) Overview. 2016.Google Scholar