SEE the DIFFerence: Reducing unnecessary C. difficile orders through clinical decision support in a large, urban safety-net system

Background: Clostridioides difficile (C. difficile) is a hospital-acquired infection. Overtesting for C. difficile leads to false positive results due to a high rate of asymptomatic colonization, resulting in unnecessary and harmful treatment for patients. Methods: This was a quality improvement initiative to decrease the rate of inappropriate C. difficile testing across 11 hospitals in an urban, safety-net setting. Three best practice advisories were created, alerting providers of recent laxative administration within 48 hours, a recent positive test within 14 days, and a recent negative test within 7 days. The outcome measures were the number of C. difficile tests per 1,000 patient days, as well as the rate of hospital onset C. difficile infection was compared pre- and post-intervention. The process measures included the rate of removal of the C. difficile test from the best practice advisory, as well as the subsequent 24-hour re-order rate. Results: The number of C. difficile tests decreased by 27.3% from 1.1 per 1,000 patient days preintervention (May 25, 2020-May 24, 2021) to 0.8 per 1,000 patient days postintervention, (May 25, 2021-March 25, 2022), P <.001. When stratified by hospital, changes in testing ranged from an increase of 12.5% to a decrease of 60%. Analysis among provider type showed higher behavior change among attendings than compared to trainees or advanced practice providers. There was a 12.1%, nonsignificant decrease in C. difficile rates from preintervention, 0.33 per 1,000 patient days compared to postintervention, 0.29 per 1,000 patient days, P= .32. Conclusions: Using only an electronic health record intervention, we successfully decreased C. difficile orders after 72 hours of admission in a large, safety-net system. Variation existed among hospitals and by provider type. (c) 2022 Published by Elsevier Inc. on behalf of Association for Professionals in Infection Control and Epidemiology, Inc.