Effectiveness of a digital clinical decision support algorithm for guiding antibiotic prescribing in pediatric outpatient care in Rwanda: A pragmatic cluster non-randomized controlled trial

BACKGROUND: Poor adherence to clinical guidelines and diagnostic uncertainty are key contributors to antibiotic overprescription, accelerating antimicrobial resistance. We developed ePOCT+, a digital clinical decision support algorithm (previously published) that integrated oxygen saturation, hemoglobin measurements, and C-reactive protein testing to assist primary care clinicians in managing acutely ill children aged 14 years or below. The goal was to reduce antibiotic prescriptions without compromising clinical recovery. METHODS AND FINDINGS: We conducted a pragmatic, open-label cluster non-randomized controlled trial in 32 Rwandan health centers allocated to two groups by geography, balancing patient volume and infrastructure. Sixteen sites used ePOCT+ throughout; the other 16 provided standard care for five months before crossing over. This design supported three comparisons: intervention-control (months 1-5), before-after (control sites pre- versus post-crossover), and longitudinal assessment (intervention sites over 10 months). ePOCT+ was deployed in a digital application; the same application (without the algorithm) served as an electronic case report form in the control arm. Outcomes were analyzed using mixed-effects logistic regression, adjusted for age, sex, district, and presenting complaints. Superiority in antibiotic prescription (primary outcome) was defined as ≥25% reduction versus routine care. Non-inferiority for clinical failure (main secondary outcome) was defined as adjusted risk ratio upper 95% CI