Clinical Pharmacology & Biopharmaceutics
Open Access

Abstract

Background: Streamlining healthcare associated infection surveillance is essential for healthcare facilities due to the continued increase in reporting requirements. Methods : Stanford Hospital, a 583-bed adult tertiary care center, utilized their electronic medical record (EMR) to develop an electronic algorithm to reduce the time required to conduct Catheter Associated Urinary Tract Infections (CAUTI) surveillance for adults. The algorithm provided inclusion and exclusion criteria, utilizing the National Healthcare Safety Network (NHSN) definitions, for patients with a CAUTI. The algorithm was validated by trained infection preventionists utilizing complete chart review for a random sample of cultures collected during the study time period; September 1, 2012 to February 28, 2013. Results: During the study time period, there were 6,379 positive urine cultures identified. The Stanford Hospital Electronic CAUTI Algorithm (SHECA) determined that 6,101 (95.64%) positive urine cultures were ?Not a CAUTI?, 191 (2.99%) positive urine cultures were a ?Possible CAUTI? and needed further validation; and 87 (1.36%) positive urine cultures were a ?Definite CAUTI?. Overall, the SHECA reduced CAUTI surveillance requirements at Stanford Hospital by 97.01%. Conclusion: An electronic algorithm proved effective in increasing the efficiency of CAUTI surveillance. The data suggests that CAUTI surveillance, utilizing the NHSN definitions, can be fully automated.

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