Development and validation of a simple and easy-to-employ electronic algorithm for identifying clinical methicillin-resistant Staphylococcus aureus infection.

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.