No abstract

Clostridioides difficile infection (CDI) is the leading cause of hospital-acquired infections (HAI) in the United States. 1 Although multiple interventions have been shown to reduce CDI, the adoption of these evidence-based practices remains suboptimal, and the burden of CDI remains high. 2 There is a pressing need to develop strategies that bridge the gap between the available evidence and clinical practice to reduce harm from CDI. The 'Agile Implementation' (AI) framework was used to reduce central-line-associated bloodstream infections (CLABSIs) at our institution. 3 In study described here, we used the AI model to achieve reductions in CDI. Methods Setting The study was conducted in 2 large academic hospitals in the

We report electronic medical record interventions to reduce Clostridioides difficile testing risk ‘alert fatigue.’ We used a behavioral approach to diagnostic stewardship and observed a decrease in the number of tests ordered of ~4.5 per month (P < .0001). Although the number of inappropriate tests decreased during the study period, delayed testing increased.