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Electronic Surveillance for Healthcare-Associated Central Line—Associated Bloodstream Infections Outside the Intensive Care Unit

Published online by Cambridge University Press:  02 January 2015

Keith F. Woeltje ,
Kathleen M. McMullen ,
Anne M. Butler ,
Ashleigh J. Goris  and
Joshua A. Doherty
Keith F. Woeltje*
Affiliation:
Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri Center for Clinical Excellence, BJC HealthCare, St. Louis, Missouri
Kathleen M. McMullen
Affiliation:
Infection Prevention Department, Barnes-Jewish Hospital, St. Louis, Missouri
Anne M. Butler
Affiliation:
Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
Ashleigh J. Goris
Affiliation:
Progress West Health Center, O'Fallon, Missouri
Joshua A. Doherty
Affiliation:
Center for Clinical Excellence, BJC HealthCare, St. Louis, Missouri
*
Division of Infectious Diseases, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8051, St. Louis, MO 63110 (kwoeltje@dom.wustl.edu)
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Abstract

Background.

Manual surveillance for central line-associated bloodstream infections (CLABSIs) by infection prevention practitioners is time-consuming and often limited to intensive care units (ICUs). An automated surveillance system using existing databases with patient-level variables and microbiology data was investigated.

Methods.

Patients with a positive blood culture in 4 non-ICU wards at Barnes-Jewish Hospital between July 1, 2005, and December 31, 2006, were evaluated. CLABSI determination for these patients was made via 2 sources; a manual chart review and an automated review from electronically available data. Agreement between these 2 sources was used to develop the best-fit electronic algorithm that used a set of rules to identify a CLABSI. Sensitivity, specificity, predictive values, and Pearson's correlation were calculated for the various rule sets, using manual chart review as the reference standard.

Results.

During the study period, 391 positive blood cultures from 331 patients were evaluated. Eighty-five (22%) of these were confirmed to be CLABSI by manual chart review. The best-fit model included presence of a catheter, blood culture positive for known pathogen or blood culture with a common skin contaminant confirmed by a second positive culture and the presence of fever, and no positive cultures with the same organism from another sterile site. The best-performing rule set had an overall sensitivity of 95.2%, specificity of 97.5%, positive predictive value of 90%, and negative predictive value of 99.2% compared with intensive manual surveillance.

Conclusions.

Although CLABSIs were slightly overpredicted by electronic surveillance compared with manual chart review, the method offers the possibility of performing acceptably good surveillance in areas where resources do not allow for traditional manual surveillance.

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 32 , Issue 11 , November 2011 , pp. 1086 - 1090
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2011

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