Effectiveness of a clinical decision support algorithm (CDSA) on reducing unnecessary antibiotic prescriptions for upper respiratory tract infections among ambulatory HIV-infected adults in Mozambique: a cluster randomized controlled trial

Abstract

Antibiotics are widely overprescribed to treat upper respiratory tract infections (URTIs), even though viruses cause most URTIs. We aimed to evaluate the effectiveness of a clinical decision support algorithm (CDSA)- based intervention in reducing antibiotic prescriptions among ambulatory HIV-infected adult patients with acute URTI symptoms. Methods Between June and September 2024, we conducted a multicenter, two-arm parallel, cluster-randomized controlled trial in six primary healthcare facilities in Mozambique. The intervention included applying the CDSA, educating and supervising clinicians, and conducting prescription audits. We used Pearson’s chi-square test and relative risk to assess the effectiveness of the intervention in reducing antibiotic prescribing. Results Three hundred seventy-nine (97.9%) HIV-infected adult patients with URTI symptoms were recruited, 182 (48%) in the intervention arm and 197 (52%) in the control. Most were females (75.5%) and single (57%). Most appeared with common cold and flu-like symptoms. Participants in the intervention arm were less likely to receive an antibiotic prescription (RR 0.41, 95% CI: 0.31–0.55) and develop a complication (RR 0.44, 95% CI: 0.16–1.20) than those not exposed. The antibiotic prescribing rate was 23.1% for the intervention and 56.3% for the control. The intervention was associated with a significant reduction in antibiotic prescribing by 33.2% (p < 0.001) and a non- significant decrease in frequency of complications by 3.7% (p = 0.096). In both arms, most patients (78%) recovered completely within five days. Amoxicillin (47.8%), azithromycin (21.9%), and phenoxymethylpenicillin (14.1%) were the most prescribed antibiotics.