TIME SERIES FORECASTING OF DAILY EMERGENCY DEPARTMENT ARRIVALS

Abstract

Rising population pressures have led to overcrowding in hospital Emergency Departments (ED), impacting patient care and resource management. This study forecasts daily ED arrivals at District Headquarters (DHQ) Hospital Charsadda using data from January 2024 to January 2025. A seasonal ARIMA (SARIMA) model—specifically SARIMA (1,0,1)(2,1,3)₇—was identified as the best fit based on AIC, BIC, MAE, and MAPE criteria. Model diagnostics confirmed its validity, with an MAE of 13 and MAPE of 2.15, demonstrating high accuracy. These results suggest SARIMA is effective for predicting daily ED demand, enabling better staff scheduling and resource allocation to mitigate overcrowding.