Computer Algorithms To Detect Bloodstream Infections

Trick, William E.; Zagorski, Brandon M.; Tokars, Jerome I.; Vernon, Michael O.; Welbel, Sharon F.; Wisniewski, Mary F.; Richards, Chesley; Weinstein, Robert A.

doi:10.3201/eid1009.030978

i

Computer Algorithms To Detect Bloodstream Infections

Supporting Files

Sep 2004
By Trick, William E. ; Zagorski, Brandon M. ; Tokars, Jerome I. ; ...

File Language:

English

Details

Alternative Title:

Emerg Infect Dis
Personal Author:

Trick, William E. ; Zagorski, Brandon M. ; Tokars, Jerome I. ; Vernon, Michael O. ; Welbel, Sharon F. ; Wisniewski, Mary F. ; Richards, Chesley ; Weinstein, Robert A.
Description:

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.
Subjects:

Algorithms Catheterization Catheterization, Central Venous Community-Acquired Infections Cross Infection Humans Infection Control Research Sepsis
Source:

Emerg Infect Dis. 10(9):1612-1620.
Document Type:

Journal Article
Funding:

U50/CCU515853/CC/ODCDC CDC HHS/United States
Volume:

10
Issue:

9
Collection(s):

Emerging Infectious Diseases
Main Document Checksum:

urn:sha256:c41e466f3e0bb86ff692ba74f4b82173bb25598fc53c25c5e74093d117d5c5e2
Download URL:

https://stacks.cdc.gov/view/cdc/7774/cdc_7774_DS1.pdf
File Type:

[PDF - 285.36 KB ]

File Language:

English

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