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

Abstract

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.