Time-Series Forecasting Model for Evaluating Community Health Centre Systems in Uganda,

Community health centres in Uganda have faced challenges in meeting service demands over time. A comprehensive time-series analysis was conducted using statistical software, incorporating historical data from -. The study employed an ARIMA (AutoRegressive Integrated Moving Average) model for forecasting future trends in service utilization and system performance. The ARIMA model indicated a significant increase of 5% in patient consultations per month, suggesting improved service capacity over the year. The time-series forecasting approach demonstrated promising results in evaluating community health centre systems' reliability, with substantial improvements observed in patient consultation rates. Further research should focus on scalability and cost-effectiveness of the model to ensure widespread application across Ugandan healthcare settings. Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.