When epidemics occur, such as is the case for bronchiolitis in the Pediatric Emergency Department (ED), the patient flow in the ED incontestably increases and can lead to crowding. We bypassed this difficulty of forecasting patient flow with aggregated weekly or monthly data by tackling the problem from a different point of view. We used daily data to build a multiperiod Serfling-based model. This model is hereinafter assimilated to normal ED flow. We then used the fourth-order moment of distribution of the time series, obtained from the difference between the estimated model and the real data, to provide an early index announcing abnormal ED patient flow. This index is parameter-dependent and we provide criterion to assist in selecting the optimal parameters. A simple program based on this methodology has been developed and has been given to the pediatric physicians for testing. Thanks to this index, the Pediatric ED was able to anticipate crowding almost three weeks before the height of the bronchiolitis epidemic.