Emergency Department Wait Time Modelling and Prediction at North York General Hospital

At North York General Hospital Yellow Zone (YZ), providers seek real-time forecasts of waiting times to improve communication and prescribe actions to relieve patient crowding. Time series of patient waits to physician assessment (PIA) and to discharge from the YZ (PTE) were collected. Multivariable regression with ARIMA errors was fit to determine the patient-based and systematic predictors of wait times for YZ patients at time of arrival. A regression on occupancy with ARIMA(1,0,0)(0,1,1)24 errors yielded the lowest error in forecasting PIA. Accuracy improved when grouping patients by acuity and complaint. ARIMA methods yielded low accuracy in forecasting PTE, and no correlations were found between PTE and acuity. 90% of patients waited up to 47.88 minutes more than predicted for PIA and up to 118 minutes more for PTE. The results suggest that ARIMA models have utility in forecasting PIA but that alternative models should be used to improve PTE prediction.M.A.S