Optimizing responsiveness to feedback about antibiotic prescribing in primary care: protocol for two interrelated...

Area of Science:

• Health Services Research
• Primary Care Medicine
• Health Informatics

Background:

• Audit and feedback (A&F) is effective in reducing unnecessary antibiotic prescribing among family physicians.
• The optimal design for A&F interventions to maximize impact remains uncertain.
• This study investigates three scalable A&F design modifications: case-mix adjustment, harm emphasis, and viral prescription pads.

Purpose of the Study:

• To test variations of theory-informed audit and feedback (A&F) components.
• To determine how to optimize A&F interventions for antibiotic prescribing in primary care.
• To evaluate the effectiveness of different A&F designs in reducing antibiotic prescribing rates.

Main Methods:

• Two interrelated pragmatic randomized trials involving Ontario family physicians.
• Cluster-randomization by practice (OH Trial) and individual randomization (PHO Trial).
• Interventions include case-mix adjusted vs. unadjusted comparators, emphasis on harms, and viral prescription pads; primary outcome is antibiotic prescribing rate per 1000 patient visits at 6 months.

Main Results:

• Primary outcome: antibiotic prescribing rate per 1000 patient visits at 6 months post-randomization.
• Analysis using Poisson regression with intention-to-treat principle.
• Mixed-methods process evaluation using surveys and interviews to explore intervention mechanisms.

Conclusions:

• This protocol outlines the methodology for optimizing A&F interventions for antibiotic prescribing.
• The findings will provide evidence on effective A&F design modifications for primary care settings.
• The study aims to improve antibiotic stewardship through evidence-based A&F strategies.