Electronic surveillance for healthcare-associated central line-associated bloodstream infections outside the intensive care unit.
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.
Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri 63110, USA. kwoeltje@dom.wustl.edu
Keith F
KF
Woeltje
Kathleen M
KM
McMullen
Anne M
AM
Butler
Ashleigh J
AJ
Goris
Joshua A
JA
Doherty
D000465:Algorithms; D055499:Catheter-Related Infections / Q000453:epidemiology* / Q000382:microbiology*; D002405:Catheterization, Central Venous / Q000009:adverse effects*; D002408:Catheters, Indwelling / Q000009:adverse effects / Q000382:microbiology; D003198:Computer Simulation; D003428:Cross Infection / Q000453:epidemiology / Q000382:microbiology; D057286:Electronic Health Records; D006786:Hospitals, Urban; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D018805:Sepsis