LAUSR

BACKGROUND Ordering Clostridioides difficile diagnostics without appropriate clinical indications can result in inappropriate antibiotic prescribing and misdiagnosis of hospital onset C. difficile infection. Manual processes such as provider review of order appropriateness may detract from other infection control or antibiotic stewardship activities. METHODS We developed an evidence-based clinical algorithm that defined appropriateness criteria for testing for C. difficile infection. We then implemented an electronic medical record-based order-entry tool that utilized discrete branches within the clinical algorithm including history of prior C. difficile test results, laxative or stool-softener administration, and documentation of unformed bowel movements. Testing guidance was then dynamically displayed with supporting patient data. We compared the rate of completed C. difficile tests after implementation of this intervention at 5 hospitals to a historic baseline in which a best-practice advisory was used. RESULTS Using mixed-effects Poisson regression, we found that the intervention was associated with a reduction in the incidence rate of both C. difficile ordering (incidence rate ratio [IRR], 0.74; 95% confidence interval [CI], 0.63-0.88; P = .001) and C. difficile-positive tests (IRR, 0.83; 95% CI, 0.76-0.91; P < .001). On segmented regression analysis, we identified a sustained reduction in orders over time among academic hospitals and a new reduction in orders over time among community hospitals. CONCLUSIONS An evidence-based dynamic order panel, integrated within the electronic medical record, was associated with a reduction in both C. difficile ordering and positive tests in comparison to a best practice advisory, although the impact varied between academic and community facilities.