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Background Inappropriate testing for Clostridioides difficile leads to overdiagnosis of C difficile infection (CDI). We determined the effect of a computerized clinical decision support (CCDS) order set on C difficile polymerase chain reaction (PCR) test utilization and clinical outcomes. Methods This study is an interrupted time series analysis comparing C difficile PCR test utilization, hospital-onset CDI (HO-CDI) rates, and clinical outcomes before and after implementation of a CCDS order set at 2 academic medical centers: University of Washington Medical Center (UWMC) and Harborview Medical Center (HMC). Results Compared with the 20-month preintervention period, during the 12-month postimplementation of the CCDS order set, there was an immediate and sustained reduction in C difficile PCR test utilization rates at both hospitals (HMC, −28.2% [95% confidence interval {CI}, −43.0% to −9.4%], P = .005; UWMC, −27.4%, [95% CI, −37.5% to −15.6%], P &amp;lt; .001). There was a significant reduction in rates of C difficile tests ordered in the setting of laxatives (HMC, −60.8% [95% CI, −74.3% to −40.1%], P &amp;lt; .001; UWMC, −37.3%, [95% CI, −58.2% to −5.9%], P = .02). The intervention was associated with an increase in the C difficile test positivity rate at HMC (P = .01). There were no significant differences in HO-CDI rates or in the proportion of patients with HO-CDI who developed severe CDI or CDI-associated complications including intensive care unit transfer, extended length of stay, 30-day mortality, and toxic megacolon. Conclusions Computerized clinical decision support tools can improve C difficile diagnostic test stewardship without causing harm. Additional studies are needed to identify key elements of CCDS tools to further optimize C difficile testing and assess their effect on adverse clinical outcomes.

open forum infectious diseases

Improving Appropriate Diagnosis of Clostridioides difficile Infection Through an Enteric Pathogen Order Set With Computerized Clinical Decision Support: An Interrupted Time Series Analysis