Use of clinical decision support for antibiotic stewardship in the emergency department and outpatient clinics: An interrupted time-series analysis

James S Ford; Brittany L Morgan Bustamante; Mehr Kaur Virk; Nancy Ramirez; Cynthia G Matsumoto; Daniel Jin Lee; Scott MacDonald; Larissa May

doi:10.1017/ash.2023.140

Use of clinical decision support for antibiotic stewardship in the emergency department and outpatient clinics: An interrupted time-series analysis

Antimicrob Steward Healthc Epidemiol. 2023 Apr 26;3(1):e80. doi: 10.1017/ash.2023.140. eCollection 2023.

Authors

James S Ford^#¹, Brittany L Morgan Bustamante^#², Mehr Kaur Virk³, Nancy Ramirez³, Cynthia G Matsumoto⁴, Daniel Jin Lee³, Scott MacDonald⁵, Larissa May³

Affiliations

¹ Department of Emergency Medicine, University of California-San Francisco, San Francisco, California.
² Department of Public Health Sciences, University of California-Davis School of Medicine, Davis, California.
³ Department of Emergency Medicine, University of California Davis, School of Medicine. Sacramento, California.
⁴ Office of Population Health and Accountable Care, University of California Davis, Sacramento, California.
⁵ Department of Clinical Informatics, University of California Davis Health, Sacramento, California.

^# Contributed equally.

Abstract

Objective: To evaluate the impact of implementing clinical decision support (CDS) tools for outpatient antibiotic prescribing in the emergency department (ED) and clinic settings.

Design: We performed a before-and-after, quasi-experimental study that employed an interrupted time-series analysis.

Setting: The study institution was a quaternary, academic referral center in Northern California.

Participants: We included prescriptions for patients in the ED and 21 primary-care clinics within the same health system.

Intervention: We implemented a CDS tool for azithromycin on March 1, 2020, and a CDS tool for fluoroquinolones (FQs; ie, ciprofloxacin, levofloxacin, and moxifloxacin) on November 1, 2020. The CDS added friction to inappropriate ordering workflows while adding health information technology (HIT) features to easily perform recommended actions. The primary outcome was the number of monthly prescriptions for each antibiotic type, by implementation period (before vs after).

Results: Immediately after azithromycin-CDS implementation, monthly rates of azithromycin prescribing decreased significantly in both the ED (-24%; 95% CI, -37% to -10%; P < .001) and outpatient clinics (-47%; 95% CI, -56% to -37%; P < .001). In the first month after FQ-CDS implementation in the clinics, there was no significant drop in ciprofloxacin prescriptions; however, there was a significant decrease in ciprofloxacin prescriptions over time (-5% per month; 95% CI, -6% to -3%; P < .001), suggesting a delayed effect of the CDS.

Conclusion: Implementing CDS tools was associated with an immediate decrease in azithromycin prescriptions, in both the ED and clinics. CDS may serve as a valuable adjunct to existing antimicrobial stewardship programs.