Development and Validation of a Simple and Easy-to-Employ Electronic Algorithm for Identifying Clinical Methicillin-Resistant Staphylococcus aureus Infection

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Abstract

BACKGROUND

With growing demands to track and publicly report and compare infection rates, efforts to utilize automated surveillance systems are increasing. We developed and validated a simple algorithm for identifying patients with clinical methicillin-resistant Staphylococcus aureus (MRSA) infection using microbiologic and antimicrobial variables. We also estimated resource savings.

METHODS

Patients who had a culture positive for MRSA at any of 5 acute care Veterans Affairs hospitals were eligible. Clinical infection was defined on the basis of manual chart review. The electronic algorithm defined clinical MRSA infection as a positive non-sterile-site culture with receipt of MRSA-active antibiotics during the 5 days prior to or after the culture.

RESULTS

In total, 246 unique non-sterile-site cultures were included, of which 168 represented infection. The sensitivity (43.4%–95.8%) and specificity (34.6%–84.6%) of the electronic algorithm varied depending on the combination of antimicrobials included. On multivariable analysis, predictors of algorithm failure were outpatient status (odds ratio, 0.23 [95% confidence interval, 0.10–0.56]) and respiratory culture (odds ratio, 0.29 [95% confidence interval, 0.13–0.65]). The median cost was $2.43 per chart given 4.6 minutes of review time per chart.

CONCLUSIONS

Our simple electronic algorithm for detecting clinical MRSA infections has excellent sensitivity and good specificity. Implementation of this electronic system may streamline and standardize surveillance and reporting efforts.

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