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Anticipating special events in emergency department forecasting

Rostami-Tabar, Bahman and Ziel, Florian 2020. Anticipating special events in emergency department forecasting. International Journal of Forecasting 10.1016/j.ijforecast.2020.01.001
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Abstract

Accurate daily forecast of Emergency Department (ED) attendance helps roster planners in allocating available resources more effectively and potentially influences staffing. Since special events affect human behaviours, they may increase or decrease the demand for ED services. Therefore, it is crucial to model their impact and use them to forecast future attendance to improve roster planning and avoid reactive strategies. In this paper, we propose, for the first time, a forecasting model to generate both point and probabilistic daily forecast of ED attendance. We model the impact of special events on ED attendance by considering real-life ED data. We benchmark the accuracy of our model against three time-series techniques and a regression model that does not consider special events. We show that the proposed model outperforms its benchmarks across all horizons for both point and probabilistic forecasts. Results also show that our model is more robust with an increasing forecasting horizon. Moreover, we provide evidence on how different types of special events may increase or decrease ED attendance. Our model can easily be adapted for use not only by EDs but also by other health services. It could also be generalised to include more types of special events.

Item Type: Article
Date Type: Published Online
Status: In Press
Schools: Business (Including Economics)
Publisher: Elsevier
ISSN: 0169-2070
Date of First Compliant Deposit: 6 February 2020
Date of Acceptance: 6 January 2020
Last Modified: 08 Jul 2020 09:15
URI: http://orca.cf.ac.uk/id/eprint/129358

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