Bayesian Hierarchical Model for Measuring Adoption Rates in Ghanaian Community Health Centres Systems: A Systematic Literature Review

Community health centres in Ghana face challenges in implementing evidence-based interventions due to varying adoption rates across different settings. A comprehensive literature search was conducted using databases such as PubMed, Scopus, and Google Scholar. Studies published between and were included if they used Bayesian hierarchical models to assess adoption rates in Ghanaian community health centres. Inclusion criteria focused on studies that reported data from at least one centre. A key finding was the variation in adoption rates across different types of interventions, with public health education programmes showing a moderate adoption rate (45-60%) compared to hygiene kits which had an even higher adoption rate (70-85%). Bayesian hierarchical models provided robust uncertainty estimates for adoption rates, allowing for more accurate predictions and informed decision-making. Future research should validate the findings through empirical studies and explore model applicability in diverse settings. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.