Impact of an electronic clinical decision support algorithm (eCDSA) on antibiotic prescribing in primary care in Cambodia: A cluster randomised controlled trial

OBJECTIVES: Poorly targeted antibiotic use in primary care is a driver of antimicrobial resistance. Electronic clinical decision support algorithms (eCDSAs) integrating point-of-care tests may improve prescribing. We evaluated the impact of an eCDSA on antibiotic prescriptions among febrile patients attending primary health centres in Cambodia. METHODS: In this cluster randomised controlled trial, 30 PHCs in Battambang Province were randomised (1:1) to either adopt the eCDSA or routine care. The eCDSA integrated clinical assessment with pulse oximetry and C-reactive protein tests. Patients aged ≥1 year with acute febrile illness were eligible. The primary outcome was the proportion of patients prescribed antibiotics, using an age- and sex-adjusted generalised linear mixed model, incorporating PHC as a random effect. Secondary outcomes included hospital referral rates and self-reported recovery at 7 and 14 days. RESULTS: Between May 2024 and January 2025, 4752 patients were enrolled (2324 intervention; 2428 control). Crude proportions of patients prescribed antibiotics were 56.1% and 60.5% in intervention and control arms, respectively. No difference in prescribing rates between the arms was detected (adjusted odds ratio [aOR] 0.64; 95% CI: 0.20-1.99; P = 0.44). Among patients for whom the eCDSA did not recommend antibiotics, almost half (45.6%) received a prescription. Hospital referral was rare (2.0%) and most patients reported full recovery within 7 days (94.3%). CONCLUSION: This eCDSA did not reduce antibiotic prescription in this setting. Relatively low adherence to the eCDSA's recommendations suggests that, to support a change in prescribing behaviour, future iterations of this intervention should incorporate enhanced training, greater adaptation to local health sector, and deeper engagement with frontline healthcare workers.