IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v302y2022i1p337-347.html
   My bibliography  Save this article

A framework for developing generalisable discrete event simulation models of hospital emergency departments

Author

Listed:
  • Boyle, Laura M.
  • Marshall, Adele H.
  • Mackay, Mark

Abstract

Discrete event simulation (DES) is routinely used to model hospital emergency departments (EDs), primarily due to its ability to represent complex patient flow processes and investigate improvement strategies. Despite this, it is clear from published studies that many DES models are not subsequently implemented in hospitals or reused for other sites. This research addresses a gap in the literature by presenting a new data-driven modelling framework ‘GE-DES’, which outlines an approach to the design and development of generalisable ED models. The nature of the framework means that it is sufficiently flexible (i) for use across multiple EDs, and (ii) for investigating hospital-specific problems through data-driven customisation. The primary aim of GE-DES is to support model reuse and implementation. The framework is demonstrated through application to a case study ED in Australia.

Suggested Citation

  • Boyle, Laura M. & Marshall, Adele H. & Mackay, Mark, 2022. "A framework for developing generalisable discrete event simulation models of hospital emergency departments," European Journal of Operational Research, Elsevier, vol. 302(1), pages 337-347.
  • Handle: RePEc:eee:ejores:v:302:y:2022:i:1:p:337-347
    DOI: 10.1016/j.ejor.2021.12.033
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721010894
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.12.033?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mielczarek, Bożena, 2014. "Simulation modelling for contracting hospital emergency services at the regional level," European Journal of Operational Research, Elsevier, vol. 235(1), pages 287-299.
    2. R Ceglowski & L Churilov & J Wasserthiel, 2007. "Combining Data Mining and Discrete Event Simulation for a value-added view of a hospital emergency department," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 246-254, February.
    3. Adrian Fletcher & Dave Worthington, 2009. "What is a ‘generic’ hospital model?—a comparison of ‘generic’ and ‘specific’ hospital models of emergency patient flows," Health Care Management Science, Springer, vol. 12(4), pages 374-391, December.
    4. S Robinson, 2008. "Conceptual modelling for simulation Part II: a framework for conceptual modelling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 291-304, March.
    5. A Fletcher & D Halsall & S Huxham & D Worthington, 2007. "The DH Accident and Emergency Department model: a national generic model used locally," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(12), pages 1554-1562, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Demir, Eren & Yakutcan, Usame & Page, Stephen, 2024. "Using simulation modelling to transform hospital planning and management to address health inequalities," Social Science & Medicine, Elsevier, vol. 347(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Monks, Thomas & Robinson, Stewart & Kotiadis, Kathy, 2014. "Learning from discrete-event simulation: Exploring the high involvement hypothesis," European Journal of Operational Research, Elsevier, vol. 235(1), pages 195-205.
    2. H Pilgrim & P Tappenden & J Chilcott & M Bending & P Trueman & A Shorthouse & J Tappenden, 2009. "The costs and benefits of bowel cancer service developments using discrete event simulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(10), pages 1305-1314, October.
    3. Brailsford, Sally & Vissers, Jan, 2011. "OR in healthcare: A European perspective," European Journal of Operational Research, Elsevier, vol. 212(2), pages 223-234, July.
    4. Niyirora, Jerome & Zhuang, Jun, 2017. "Fluid approximations and control of queues in emergency departments," European Journal of Operational Research, Elsevier, vol. 261(3), pages 1110-1124.
    5. Ormerod, R.J., 2014. "Critical rationalism in practice: Strategies to manage subjectivity in OR investigations," European Journal of Operational Research, Elsevier, vol. 235(3), pages 784-797.
    6. Nguyen, Le Khanh Ngan & Howick, Susan & Megiddo, Itamar, 2024. "A framework for conceptualising hybrid system dynamics and agent-based simulation models," European Journal of Operational Research, Elsevier, vol. 315(3), pages 1153-1166.
    7. Jason Madan & Meghan Bruce Kumar & Miriam Taegtmeyer & Edwine Barasa & Swaran Preet Singh, 2020. "SEEP-CI: A Structured Economic Evaluation Process for Complex Health System Interventions," IJERPH, MDPI, vol. 17(18), pages 1-12, September.
    8. Eric Innocenti & Claudio Detotto & Corinne Idda & Dawn Cassandra Parker & Dominique Prunetti, 2023. "Spécification conceptuelle MR POTATOHEAD -Property Market Edition du système complexe d'un territoire touristique à deux marchés : application au territoire corse," Post-Print hal-04121402, HAL.
    9. Gogi, Anastasia & Tako, Antuela A. & Robinson, Stewart, 2016. "An experimental investigation into the role of simulation models in generating insights," European Journal of Operational Research, Elsevier, vol. 249(3), pages 931-944.
    10. P R Harper & N H Powell & J E Williams, 2010. "Modelling the size and skill-mix of hospital nursing teams," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(5), pages 768-779, May.
    11. Willoughby, Keith A. & Chan, Benjamin T.B. & Marques, Shauna, 2016. "Using simulation to test ideas for improving speech language pathology services," European Journal of Operational Research, Elsevier, vol. 252(2), pages 657-664.
    12. Mahdavi, Mahdi & Malmström, Tomi & van de Klundert, Joris & Elkhuizen, Sylvia & Vissers, Jan, 2013. "Generic operational models in health service operations management: A systematic review," Socio-Economic Planning Sciences, Elsevier, vol. 47(4), pages 271-280.
    13. Amir Elalouf & Guy Wachtel, 2022. "Queueing Problems in Emergency Departments: A Review of Practical Approaches and Research Methodologies," SN Operations Research Forum, Springer, vol. 3(1), pages 1-46, March.
    14. M Pidd, 2010. "Why modelling and model use matter," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 14-24, January.
    15. Robert Saltzman & Theresa Roeder & Judith Lambton & Lila Param & Brian Frost & Roxanne Fernandes, 2017. "The Impact of a Discharge Holding Area on the Throughput of a Pediatric Unit," Service Science, INFORMS, vol. 9(2), pages 121-135, June.
    16. Robert, Marion & Thomas, Alban & Sekhar, Muddu & Badiger, Shrinivas & Ruiz, Laurent & Raynal, Hélène & Bergez, Jacques-Eric, 2017. "Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms," Agricultural Systems, Elsevier, vol. 157(C), pages 279-291.
    17. Lehner, Roland, 2023. "Cross-Supply Chain Collaboration Platform for Pallet Management," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 138753, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    18. Graeme J. Doole & David J. Pannell, 2013. "A process for the development and application of simulation models in applied economics," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(1), pages 79-103, January.
    19. Martin Comis & Catherine Cleophas & Christina Büsing, 2021. "Patients, primary care, and policy: Agent-based simulation modeling for health care decision support," Health Care Management Science, Springer, vol. 24(4), pages 799-826, December.
    20. Glasgow, Simon M. & Perkins, Zane B. & Tai, Nigel R.M. & Brohi, Karim & Vasilakis, Christos, 2018. "Development of a discrete event simulation model for evaluating strategies of red blood cell provision following mass casualty events," European Journal of Operational Research, Elsevier, vol. 270(1), pages 362-374.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:302:y:2022:i:1:p:337-347. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.