Hsu HE, Shenoy ES, Kelbaugh D, Ware W, Lee H, Zakroysky P, Hooper DC, Walensky RP. An electronic surveillance tool for catheter-associated urinary tract infection in intensive care units.
Am J Infect Control 2015;
43:592-9. [PMID:
25840717 DOI:
10.1016/j.ajic.2015.02.019]
[Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Revised: 02/12/2015] [Accepted: 02/17/2015] [Indexed: 11/28/2022]
Abstract
BACKGROUND
Traditional methods of surveillance of catheter-associated urinary tract infections (CAUTIs) are error-prone and resource-intensive. To resolve these issues, we developed a highly sensitive electronic surveillance tool.
OBJECTIVE
To develop an electronic surveillance tool for CAUTIs and assess its performance.
METHODS
The study was conducted at a 947-bed tertiary care center. Patients included adults aged ≥18 years admitted to an intensive care unit between January 10 and June 30, 2012, with an indwelling urinary catheter during their admission. We identified CAUTIs using 4 methods: traditional surveillance (TS) (ie, manual chart review by ICPs), an electronic surveillance (ES) tool, augmented electronic surveillance (AES) (ie, ES with chart review on a subset of cases), and reference standard (RS) (ie, a subset of CAUTIs originally ascertained by TS or ES, confirmed by review). We assessed performance characteristics to RS for reviewed cases.
RESULTS
We identified 417 candidate CAUTIs in 308 patients; 175 (42.0%) of these candidate CAUTIs were selected for review, yielding 32 confirmed CAUTIs in 22 patients (RS). Compared with RS, the sensitivities of TS, ES, and AES were 43.8% (95% confidence interval [CI], 26.4%-62.3%), 100.0% (95% CI, 89.1%-100.0%), and 100.0% (95% CI, 89.1%-100.0%). Specificities were 82.5% (95% CI, 75.3%-88.4%), 2.8% (95% CI, 0.8%-7.0%), and 100.0% (95% CI, 97.5%-100.0%).
CONCLUSIONS
Electronic CAUTI surveillance offers a streamlined approach to improve reliability and resource burden of surveillance.
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