Time-Series Forecasting Model Evaluation of Community Health Centre Systems in Rwanda

This report evaluates the effectiveness of community health centre (CHC) systems in Rwanda's public healthcare sector through a time-series forecasting model. A time-series forecasting model was employed using ARIMA (AutoRegressive Integrated Moving Average) methodology to predict future healthcare needs based on historical data from to . Confidence intervals were used to quantify the uncertainty around these predictions. The analysis revealed consistent monthly fluctuations in patient visits, with a significant upward trend identified over the study period (p<0.05). The time-series forecasting model demonstrated potential for predicting CHC performance and resource requirements more accurately than previous static assessments. Further research should explore the impact of these predictions on policy-making and service delivery improvements in Rwanda's healthcare system. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.