Time-dependent stochastic methods for managing and scheduling Emergency Medical Services

Authors : J.L. Vile, J.W. Gillard, P.R. Harper, V.A. Knight

Abstract

Emergency Medical Services (EMS) are facing increasing pressures in many nations given that demands on the service are rising. This article focuses in particular on the operations of the Welsh Ambulance Service Trust (WAST), which is the only organisation that provides urgent paramedical care services on a day-to-day basis across the whole of Wales. In response to WAST’s aspiration to improve the quality of care it provides, this research investigates several interrelated advanced statistical and operational research (OR) methods, culminating in a suite of decision support tools to aid WAST with capacity planning issues. The developed techniques are integrated in a master workforce capacity planning tool that may be independently operated by WAST planners. By means of incorporating methods that seek to simultaneously better predict future demands, recommend minimum staffing requirements and generate low-cost rosters, the tool ultimately provides planners with an analytical base to effectively deploy resources. Whilst the tool is primarily developed for WAST, the generic nature of the methods considered means they could equally be applied to any service subject to demand that is of an urgent nature, cannot be backlogged, is heavily time-dependent and highly variable.

Keywords

Health care modelling; Forecasting; Priority queueing theory; Time-dependent queueing theory; Ambulance allocation; Demand and capacity models.

Citation: J.L. Vile, J.W. Gillard, P.R. Harper, V.A. Knight Time-dependent stochastic methods for managing and scheduling Emergency Medical Services doi:10.1016/j.orhc.2015.07.002

Received: 31 October 2014 Accepted: 18 July 2015 Available online: 24 August 2015

Copyright: © 2015 The Authors.Published by Elsevier Ltd. This is an open access article under the CCBY license
(http://creativecommons.org/licenses/by/4.0/).

Acknowledgments

This research was funded by EPSRC grant EP/F033338/1 (part of the LANCS initiative) and the data underpinning the project was provided by the Welsh Ambulance Services NHS Trust (WAST). The authors would particularly like to thank WAST Research Development Manager Richard Whitfield for his profound support throughout the project and the EURO Summer Institute XXXI conference organisers for providing the opportunity to improve the paper in such a stimulating research environment.

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