Proactive Service Recovery in Emergency Departments: A Hybrid Modelling Approach using Forecasting and Real-Time Simulation

Abstract

This work in progress is an application of a hybrid modelling (HM) approach for short-term decision support in urgent and emergency healthcare. It uses seasonal ARIMA time-series forecasting to predict emergency department (ED) overcrowding in a near-future moving window (1-4 hours) using data downloaded from a digital platform (NHSquicker). NHSquicker delivers near real-time wait times from multiple centres of urgent care in the South-West of England. Alongside historical distributions, this near real-time data is used to populate an ED discrete event simulation model. The ARIMA forecasts trigger real-time simulation experimentation of ED scenarios including proactive diversion of low-acuity patients to alternative facilities in the urgent care network.