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Modelling patient flow in an emergency department to better understand demand management strategies

  • Published:
Journal of Simulation

Abstract

This paper presents a simulation model of the emergency department (ED) at a major UK hospital, which like most other EDs, is struggling to meet the key ED performance target to admit or discharge 95% of patients within 4 h of arrival. Only marginal improvements have been evidenced from recent investigations piloted as attempts to improve cost, quality and throughput in the ED, leading to increased enthusiasm from management to explore the potential of simulation to expedite patient flow. The objective of this project was to create a discrete event simulation model of the ED to improve understanding of the current system, identify shortcomings of previously piloted interventions and assess the impact of alternative initiatives. The project has served as an excellent means to promote simulation as an effective tool to design ED services. Its success to generate outputs above those anticipated by management has accelerated the development of a multidisciplinary Flow Team, which meets regularly at the hospital to review improvements and explore further proposals to improve patient flow.

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Author information

Authors and Affiliations

  1. School of Mathematics, Cardiff University, Cardiff, UK

    J L Vile, E Allkins & J E Williams

  2. Delivery Unit, NHS Wales, Pencoed, UK

    J L Vile

  3. ABCi, Aneurin Bevan University Health Board, Caerleon, UK

    J Frankish

  4. Royal Gwent Hospital, Newport, UK

    S Garland & P Mizen

Authors
  1. J L Vile
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  2. E Allkins
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  3. J Frankish
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  4. S Garland
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  5. P Mizen
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  6. J E Williams
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Corresponding author

Correspondence to J L Vile.

Appendix A: List of software

Appendix A: List of software

  • SIMUL8 A simulation tool that allows the user to create a virtual model of any department that processes discrete entities at discrete times. Basic features of the model can be built via a simple graphical interface and more advanced features can be added using SIMUL8’s own simulation language, Visual Logic. It’s design allows communication with other software packages, so parameters and results can be simply imported/exported. Popular alternatives to SIMUL8 include AnyLogic, Witness, Simio, ARENA, ProModel, Flexsim and Scenario Generator (for strategic planning for health and social care). Further guidance on selecting the most appropriate package is provided in Azadeh et al (2010).

  • R Open-source data analysis software in which the analysis is performed via scripts and functions written in the R programming language. Not only can the software be downloaded for free, but the source code required to perform the data analysis can be recycled from other projects and directly modified by the user. In this study, R was used for distribution fitting but it can also be used for general statistical analysis, data visualisation and predictive modelling. Alternative proprietary software include SAS, IBM SPSS and Stata.

  • Microsoft Excel Excel is widely available within many organisations and most NHS staff have a basic understanding of the software. Excel does contain a limited number of add-ins that can be used to perform data analysis, but its functionality remains very basic in comparison to the packages listed above.

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Vile, J.L., Allkins, E., Frankish, J. et al. Modelling patient flow in an emergency department to better understand demand management strategies. J Simulation 11, 115–127 (2017). https://doi.org/10.1057/s41273-016-0004-2

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  • DOI: https://doi.org/10.1057/s41273-016-0004-2

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