Forecasting emergency department arrivals using INGARCH models.

Background: Forecasting patient arrivals to hospital emergency departments is critical to dealing with surges and to efficient planning, management and functioning of hospital emerency departments.

Objective: We explore whether past mean values and past observations are useful to forecast daily patient arrivals in an Emergency Department.

Material And Methods: We examine whether an integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) model can yield a better conditional distribution fit and forecast of patient arrivals by using past arrival information and taking into account the dynamics of the volatility of arrivals.