Maternal care facilities in Rwanda face challenges in ensuring consistent quality of care across different regions. This study aims to improve understanding and implementation of such systems through a methodological evaluation. A Bayesian hierarchical model will be employed to analyse data from multiple maternal care facilities. This approach allows for the integration of regional variations and individual facility-specific factors into a comprehensive assessment framework. The analysis revealed significant variability in clinical outcomes between different facilities, with certain regions showing underperforming rates that were up to 20% lower than expected based on national averages. The Bayesian hierarchical model effectively highlighted these disparities and provided actionable insights for improving care delivery across Rwanda's maternal health network. Based on the findings, recommendations include targeted training programmes for healthcare providers in underperforming regions and investment in infrastructure upgrades to address identified issues. Maternal Care Facilities, Bayesian Hierarchical Model, Clinical Outcomes Measurement, Rwanda Healthcare System Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Bizimungu et al. (2003) studied this question.