Bayesian Hierarchical Model Assessment of Maternal Care Facilities in Ghana: Evaluating Clinical Outcomes in a Nationally Representative Sample,

Maternal care facilities in Ghana face challenges in ensuring optimal clinical outcomes for pregnant women and their newborns. A Bayesian hierarchical model was employed to analyse data from nationally representative samples collected between and . The model accounted for variability in facility quality and patient demographics. The analysis revealed significant variations in clinical outcomes across different facilities, with a notable proportion (45%) of patients experiencing adverse postnatal complications. This study highlights the importance of standardised care protocols and continuous improvement initiatives to enhance maternal health outcomes. Health authorities are encouraged to implement quality assurance measures and support programmes to improve facility performance and patient safety. Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.