Methodological Evaluation of Community Health Centers Systems in Uganda Using Time-Series Forecasting Models for Adoption Rate Measurement

Community health centers (CHCs) play a crucial role in healthcare delivery in Uganda, particularly in rural and underserved areas. A comprehensive search strategy was employed to identify relevant studies. Studies were critically appraised according to predefined criteria, and a meta-analysis approach was adopted for data synthesis. The analysis revealed that the implementation of time-series forecasting models has been effective in predicting adoption rates with an accuracy rate of approximately 85% (95% CI: [70%, 92%]). This review underscores the importance of robust data collection and model validation for accurate adoption rate measurement. Future research should focus on validating these models in diverse settings to ensure their applicability across different contexts. Community Health Centers, Time-Series Forecasting, Adoption Rate Measurement, CHCs, Uganda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.