{ "background": "District hospitals are critical nodes in Ghana's healthcare system, yet synthesising evidence on their cost-effectiveness is hampered by heterogeneous study designs and outcome measures. Existing systematic reviews often fail to quantify uncertainty and integrate disparate data sources effectively.", "purpose and objectives": "This study aimed to develop and apply a Bayesian hierarchical meta-analytic model to synthesise cost-effectiveness evidence for district-level hospital services, evaluating the model's methodological performance and deriving optimised estimates to inform resource allocation.", "methodology": "A meta-analysis was conducted of studies reporting cost and health outcome data for district hospital interventions. A Bayesian hierarchical model was fitted, formalised as $y{ij} \\sim \\text{Normal}(\\thetaj, \\sigma^2{ij}), \\; \\thetaj \\sim \\text{Normal}(\\mu, \\tau^2)$, where $y{ij}$ is the $i$th cost-effectiveness ratio in hospital group $j$, $\\thetaj$ are group-level means, and $\\mu$ is the overall mean. Posterior distributions were estimated using Markov chain Monte Carlo sampling.", "findings": "The model successfully integrated heterogeneous data, revealing substantial hospital variability in cost-effectiveness, with a posterior probability of 0.87 that the group standard deviation ($\\tau$) exceeded 0.5. Maternal and child health interventions consistently demonstrated the highest probability of being cost-effective, with a median incremental cost-effectiveness ratio of GHS 1,200 per disability-adjusted life year averted (95% credible interval: GHS 800 to 1,700).", "conclusion": "The Bayesian hierarchical approach provides a robust methodological framework for evidence synthesis in this context, quantifying uncertainty more comprehensively than frequentist models. The results indicate significant efficiency gains are possible through targeted investment in specific service areas.", "recommendations": "Health system planners should adopt probabilistic modelling to guide district hospital funding. Future research should prioritise standardised cost-reporting and utilise hierarchical models to account for institutional and regional heterogeneity