Heather E Hsu1, Erica S Shenoy2, Douglas Kelbaugh3, Winston Ware4, Hang Lee5, Pearl Zakroysky6, David C Hooper7, Rochelle P Walensky8. 1. Harvard Medical School, Boston, MA; Boston Combined Residency Program in Pediatrics, Boston Children's Hospital and Boston Medical Center, Boston, MA. 2. Harvard Medical School, Boston, MA; Division of Infectious Disease, Department of Medicine, Massachusetts General Hospital, Boston, MA; Infection Control Unit, Massachusetts General Hospital, Boston, MA; Medical Practices Evaluation Center, Massachusetts General Hospital, Boston, MA. Electronic address: eshenoy@mgh.harvard.edu. 3. Partners Information Systems, Massachusetts General Hospital and Massachusetts General Physicians Organization, Boston, MA. 4. Clinical Care Management Unit, Massachusetts General Hospital, Boston, MA. 5. Harvard Medical School, Boston, MA; Department of Biostatistics, Massachusetts General Hospital, Boston, MA. 6. Department of Biostatistics, Massachusetts General Hospital, Boston, MA. 7. Harvard Medical School, Boston, MA; Division of Infectious Disease, Department of Medicine, Massachusetts General Hospital, Boston, MA; Infection Control Unit, Massachusetts General Hospital, Boston, MA. 8. Harvard Medical School, Boston, MA; Division of Infectious Disease, Department of Medicine, Massachusetts General Hospital, Boston, MA; Medical Practices Evaluation Center, Massachusetts General Hospital, Boston, MA.
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.
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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