Digital Antibiotic stewardship and training for Wahudumu wa Afya (DAWA) Project
Background
Inappropriate antibiotic prescribing is widespread in primary care settings and contributes to bacterial antimicrobial resistance (AMR), high morbidity and mortality. Sustainable antibiotic stewardship must address the clinical uncertainty experienced by clinicians, tackle entrenched prescribing habits, and address patient expectations.
Building on prior studies and feedback from healthcare providers, this study aims to develop and evaluate a digital clinical support tool integrated within an electronic medical record system, and strengthened mentorship approaches to promote rational antibiotic use in routine primary care settings.
Primary objective
To evaluate the effectiveness of two antibiotic stewardship interventions in reducing antibiotic prescribing for acute infectious illness in patients of all ages, compared to usual care at primary care health facilities in Zanzibar, Tanzania
Interventions:
- Clinical decision support integrated into the Zanzibar electronic medical record system (ZanEMR-AS) with antibiotic audit and feedback benchmarking dashboards
- Monthly antibiotic stewardship club meetings aimed at strengthening provider’s knowledge, attitudes, and peer learning around appropriate antibiotic use
Study design:
A three-arm, parallel-group, cluster randomized controlled trial (RCT) will evaluate the effectiveness of two intervention packages to reduce antibiotic prescribing compared to usual care. Primary healthcare facilities will serve as the unit of randomization, with all patients with an acute infectious illness attending participating facilities during the study period eligible for inclusion. Patient
enrollment will occur between months 3-5 after intervention initiation (month 0), once the interventions have been fully implemented and providers are familiar with their use.
Sample size: 13 clusters and 1,950 patients per arm, for a total of 5,850 patients (including 1,560 patients aged less than 5 years old) within 39 clusters.