Computer Algorithms To Detect Bloodstream Infections

We compared manual and computer-assisted bloodstream infection surveillance for adult inpatients at two hospitals. We identified hospital-acquired, primary, central-venous catheter (CVC)-associated bloodstream infections by using five methods: retrospective, manual record review by investigators; pr...

Full description

Saved in:
Bibliographic Details
Published in:Emerging infectious diseases Vol. 10; no. 9; pp. 1612 - 1620
Main Authors: Trick, William E., Zagorski, Brandon M., Tokars, Jerome I., Vernon, Michael O., Welbel, Sharon F., Wisniewski, Mary F., Richards, Chesley, Weinstein, Robert A.
Format: Journal Article
Language:English
Published: United States U.S. National Center for Infectious Diseases 01.09.2004
Centers for Disease Control and Prevention
Subjects:
Algorithms
bloodstream infection
Catheterization - adverse effects
Catheterization, Central Venous - adverse effects
Community-Acquired Infections
computer data processing
Cross Infection - epidemiology
Humans
Infection
Infection Control
information system
Sepsis - diagnosis
Sepsis - epidemiology
Sepsis - etiology
surveillance
United States
ISSN:1080-6040, 1080-6059
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We compared manual and computer-assisted bloodstream infection surveillance for adult inpatients at two hospitals. We identified hospital-acquired, primary, central-venous catheter (CVC)-associated bloodstream infections by using five methods: retrospective, manual record review by investigators; prospective, manual review by infection control professionals; positive blood culture plus manual CVC determination; computer algorithms; and computer algorithms and manual CVC determination. We calculated sensitivity, specificity, predictive values, plus the kappa statistic (kappa) between investigator review and other methods, and we correlated infection rates for seven units. The kappa value was 0.37 for infection control review, 0.48 for positive blood culture plus manual CVC determination, 0.49 for computer algorithm, and 0.73 for computer algorithm plus manual CVC determination. Unit-specific infection rates, per 1,000 patient days, were 1.0-12.5 by investigator review and 1.4-10.2 by computer algorithm (correlation r = 0.91, p = 0.004). Automated bloodstream infection surveillance with electronic data is an accurate alternative to surveillance with manually collected data.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Undefined-3
ISSN:1080-6040
1080-6059
DOI:10.3201/eid1009.030978