{ "background": "Maternal healthcare facility performance in Nigeria is critical yet difficult to assess due to heterogeneous data and complex, multi-level confounding factors. Traditional evaluation methods often fail to account for this hierarchy and inherent uncertainty, limiting actionable insights for system improvement.", "purpose and objectives": "This case study demonstrates the application of a Bayesian hierarchical model to evaluate maternal care facility performance and its association with clinical outcomes. The objective is to provide a robust methodological framework for facility-level assessment that quantifies uncertainty and identifies performance drivers.", "methodology": "We employed a Bayesian hierarchical logistic regression model. The core structure is $y{ij} \\sim \\text{Bernoulli}(p{ij}), \\; \\text{logit}(p{ij}) = \\alpha + \\alpha{j[i]} + \\beta X{ij}$, where $y{ij}$ is the binary outcome for mother $i$ in facility $j$, $\\alpha{j[i]} \\sim N(0, \\sigma{\\alpha}^2)$ represents the facility-specific random intercept, and $X_{ij}$ are covariates. Facility performance was measured via posterior distributions of the random effects.", "findings": "The model identified significant variation in facility-level performance, with the posterior probability that a facility in the lowest decile underperformed the national average exceeding 0.95. A key finding was that facilities with integrated referral systems and routine clinical audits had a 1.4 times higher probability (95% credible interval: 1.1 to 1.8) of favourable composite maternal outcomes.", "conclusion": "The Bayesian hierarchical approach provides a statistically rigorous and interpretable framework for benchmarking maternal care facilities, effectively separating signal from noise in complex health systems data.", "recommendations": "Health policymakers should adopt hierarchical modelling for facility performance assessment to enable targeted interventions. Investment should prioritise strengthening referral system integration and mandating clinical audit cycles to improve outcomes.", "key words": "Bayesian hierarchical model, maternal health, health systems evaluation