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Setting staffing requirements for time dependent queueing networks: The case of accident and emergency departments.

Izady, N. and Worthington, D. J. (2012). Setting staffing requirements for time dependent queueing networks: The case of accident and emergency departments.. European Journal of Operational Research, 219(3), pp. 531-540. doi: 10.1016/j.ejor.2011.10.040

Abstract

An incentive scheme aimed at reducing patients’ waiting times in accident and emergency departments was introduced by the UK government in 2000. It requires 98% of patients to be discharged, transferred, or admitted to inpatient care within 4 hours of arrival. Setting the minimal hour by hour medical staffing levels for achieving the government target, in the presence of complexities like time-varying demand, multiple types of patients, and resource sharing, is the subject of this paper. Building on extensive body of research on time dependent queues, we propose an iterative scheme which uses infinite server networks, the square root staffing law, and simulation to come up with a good solution. The implementation of this algorithm in a typical A&E department suggests that significant improvement on the target can be gained, even without increase in total staff hours.
Highlights

► We considered the staffing problem in English emergency departments. ► We combined queueing and simulation models to search for minimal staffing profiles. ► Applying the method to a generic ED shows that improvements can be made even without increase in total staff-hours. ► Improvements arise as the result of matching staffing levels closely with demand.

Publication Type: Article
Additional Information: © 2012 Elsevier B. V. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Publisher Keywords: Staffing emergency departments, 98% Target, Time-dependent queues, Simulation
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
R Medicine
Departments: Business School > Management
Date Deposited: 20 Dec 2019 09:55
URI: https://openaccess.city.ac.uk/id/eprint/23377
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