Predicting ambulance demand using singular spectrum analysis

Vile, Julie Leanne, Gillard, Jonathan William ORCID: https://orcid.org/0000-0001-9166-298X, Harper, Paul Robert ORCID: https://orcid.org/0000-0001-7894-4907 and Knight, Vincent Anthony ORCID: https://orcid.org/0000-0002-4245-0638 2012. Predicting ambulance demand using singular spectrum analysis. Journal of the Operational Research Society 63 , pp. 1556-1565. 10.1057/jors.2011.160

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Abstract

This paper demonstrates techniques to generate accurate predictions of demand exerted upon the Emergency Medical Services (EMS) using data provided by the Welsh Ambulance Service Trust (WAST). The aim is to explore new methods to produce accurate forecasts that can be subsequently embedded into current OR methodologies to optimise resource allocation of vehicles and staff, and allow rapid response to potentially life-threatening emergencies. Our analysis explores a relatively new non-parametric technique for time series analysis known as Singular Spectrum Analysis (SSA). We explain the theory of SSA and evaluate the performance of this approach by comparing the results with those produced by conventional time series methods. We show that in addition to being more flexible in approach, SSA produces superior longer-term forecasts (which are especially helpful for EMS planning), and comparable shorter-term forecasts to well established methods.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics
Uncontrolled Keywords:	Health service; Emergency medical services; Forecasting; Singular spectrum analysis
Publisher:	Palgrave Macmillan
ISSN:	0160-5682
Last Modified:	19 Oct 2022 09:50
URI:	https://orca.cardiff.ac.uk/id/eprint/22381

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