Time-Series Forecasting Model for Evaluating Emergency Care Units in Uganda,

Uganda's emergency care units (ECUs) face challenges in managing patient flow efficiently, leading to delays and suboptimal clinical outcomes. A time-series forecasting model was applied to historical data from Ugandan ECUs, incorporating robust standard errors for uncertainty quantification. The forecasted patient flow patterns indicated seasonal variations with peaks during the rainy season, suggesting a need for additional resources in that period. This study provides insights into ECU performance variability and highlights the importance of seasonal planning to improve service delivery. ECUs should prepare for increased demand during the rainy season by enhancing staffing levels and allocating more resources accordingly. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.