Improving Antibiotic Stewardship for Diarrheal Disease With Probability-Based Electronic Clinical Decision Support: A Randomized Crossover Trial

Abstract

Importance: Inappropriate use of antibiotics for diarrheal illness can result in adverse effects and increase in antimicrobial resistance.

Objective: To determine whether the diarrheal etiology prediction (DEP) algorithm, which uses patient-specific and location-specific features to estimate the probability that diarrhea etiology is exclusively viral, impacts antibiotic prescriptions in patients with acute diarrhea.

Design, setting, and participants: A randomized crossover study was conducted to evaluate the DEP incorporated into a smartphone-based electronic clinical decision-support (eCDS) tool. The DEP calculated the probability of viral etiology of diarrhea, based on dynamic patient-specific and location-specific features. Physicians were randomized in the first 4-week study period to the intervention arm (eCDS with the DEP) or control arm (eCDS without the DEP), followed by a 1-week washout period before a subsequent 4-week crossover period. The study was conducted at 3 sites in Bangladesh from November 17, 2021, to January 21, 2021, and at 4 sites in Mali from January 6, 2021, to March 5, 2021. Eligible physicians were those who treated children with diarrhea. Eligible patients were children between ages 2 and 59 months with acute diarrhea and household access to a cell phone for follow-up.

Interventions: Use of the eCDS with the DEP (intervention arm) vs use of the eCDS without the DEP (control arm).

Main outcomes and measures: The primary outcome was the proportion of children prescribed an antibiotic.

Results: A total of 30 physician participants and 941 patient participants (57.1% male; median [IQR] age, 12 [8-18] months) were enrolled. There was no evidence of a difference in the proportion of children prescribed antibiotics by physicians using the DEP (risk difference [RD], -4.2%; 95% CI, -10.7% to 1.0%). In a post hoc analysis that accounted for the predicted probability of a viral-only etiology, there was a statistically significant difference in risk of antibiotic prescription between the DEP and control arms (RD, -0.056; 95% CI, -0.128 to -0.01). No known adverse effects of the DEP were detected at 10-day postdischarge.

Conclusions and relevance: Use of a tool that provides an estimate of etiological likelihood did not result in a significant change in overall antibiotic prescriptions. Post hoc analysis suggests that a higher predicted probability of viral etiology was linked to reductions in antibiotic use.

Trial registration: Clinicaltrials.gov Identifier: NCT04602676.

Conflict of interest statement

Conflict of Interest Disclosures: Dr Brintz reported grants from Bill & Melinda Gates Foundation during the conduct of the study. Dr Y. Keita reported grants from University of Utah. Dr Ahmed reported grants from National Institutes of Health during the conduct of the study. Dr Haaland reported grants from Bill & Melinda Gates Foundation and grants from National Institutes of Health during the conduct of the study; and consulting fees from Astra Zeneca, Prometic Life Sciences, National Kidney Foundation, and Value Analytics Labs, outside the submitted work. Dr Levine reported personal fees from University of Utah and grants from National Institutes of Health For, outside the submitted work. Dr Kotloff reported grants from Bill & Melinda Gates Foundation and grants from the National Institutes of Health during the conduct of the study. Dr Leung reported grants from the National Institutes of Health and grants from Bill & Melinda Gates Foundation during the conduct of the study. No other disclosures were reported.

Figures

Figure 1.. Enrollment Flow Diagram

Figure 2.. Fitted Probability of Antibiotic Prescription by the Diarrheal Etiology Prediction (DEP) Probability of Viral-only Etiology, by Period

The dashed lines are the overall estimate for patients in each arm and does not account for site and physician random effects. The shaded portions indicate a 95% CI for each estimate.