Effectiveness of Pharmacist-Led Interventions to Improve Adherence to Self-Administered Antibiotics in Community and Ambulatory Care: a Systematic Review and Meta-Analysis

BACKGROUND:Poor adherence to self-administered antibiotics in community and ambulatory care may compromise outcomes and contribute to inappropriate antibiotic use. Pharmacist-led adherence interventions are plausible, but evidence is heterogeneous and adherence is difficult to measure consistently. OBJECTIVE:To evaluate the published literature on whether pharmacist-led interventions in community and ambulatory care improve adherence to self-administered antibiotic therapy compared with usual care or less intensive support. METHODS:This PRISMA 2020 systematic review and meta-analysis was registered in PROSPERO (CRD420261329577). PubMed, Embase, Web of Science Core Collection, Scopus, and CENTRAL were searched from inception to 22 January 2026, with backward citation tracking. Eligible studies enrolled outpatients or ambulatory patients prescribed self-administered antibiotics. Randomized and cluster-randomized studies were pooled using random-effects models with Hartung-Knapp adjustment. Certainty was assessed with GRADE. RESULTS:Eighteen studies met the inclusion criteria; 10 randomized or cluster-randomized studies contributed to the primary meta-analysis. Certainty was very low because of risk of bias, inconsistency, and possible small-study effects. The pooled estimate favored pharmacist-led interventions (RR 1.42, 95% CI 1.04-1.93), but heterogeneity was considerable (I2 = 83.4%). Egger regression suggested possible small-study effects (p = 0.009) but not definitive publication bias. CONCLUSIONS:It remains uncertain whether pharmacist-led interventions improve adherence to self-administered antibiotics in community and ambulatory care. The pooled estimate suggests a possible benefit, but confidence in the magnitude and consistency of this effect is very limited. Future studies should use standardized adherence outcomes, transparent cluster-design methods, and downstream stewardship-relevant outcomes.