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A BPMN extension to support discrete-event simulation for healthcare applications: an explicit representation of queues, attributes and data-driven decision points

Author

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  • B. S. S. Onggo
  • N. C. Proudlove
  • S. A. D’Ambrogio
  • A. Calabrese
  • Stefania Bisogno
  • N. Levialdi Ghiron

Abstract

Stakeholder engagement in simulation projects is important, especially in healthcare where there is a plurality of stakeholder opinions, objectives and power. One promising approach for increasing engagement is facilitated modelling. Currently, the complexity of producing a simulation model means that the “model coding” stage is performed without the involvement of stakeholders, interrupting the possibility of a fully facilitated project. Early work demonstrated that with currently available software tools we can represent a simple healthcare process using Business Process Model and Notation (BPMN) and generate a simulation model automatically. However, for more complex processes, BPMN currently has a number of limitations, namely the ability to represent queues and data-driven decision points. To address these limitations, we propose a conceptual design for an extension to BPMN (BPMN4SIM) using model-driven architecture. Application to an elderly emergency care pathway in a UK hospital shows that BPMN4SIM is able to represent a more complex business process.

Suggested Citation

  • B. S. S. Onggo & N. C. Proudlove & S. A. D’Ambrogio & A. Calabrese & Stefania Bisogno & N. Levialdi Ghiron, 2018. "A BPMN extension to support discrete-event simulation for healthcare applications: an explicit representation of queues, attributes and data-driven decision points," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(5), pages 788-802, May.
    • Handle: RePEc:taf:tjorxx:v:69:y:2018:i:5:p:788-802
    DOI: 10.1057/s41274-017-0267-7
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    Cited by:

    1. Jesús Isaac Vázquez-Serrano & Rodrigo E. Peimbert-García & Leopoldo Eduardo Cárdenas-Barrón, 2021. "Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    2. Ali Ala & Morteza Yazdani & Mohsen Ahmadi & Aida Poorianasab & Mahdi Yousefi Nejad Attari, 2023. "An efficient healthcare chain design for resolving the patient scheduling problem: queuing theory and MILP-ASA optimization approach," Annals of Operations Research, Springer, vol. 328(1), pages 3-33, September.
    3. Beata Skowron-Grabowska & Marta Wincewicz-Bosy & Małgorzata Dymyt & Adam Sadowski & Tomasz Dymyt & Katarzyna Wąsowska, 2022. "Healthcare Supply Chain Reliability: The Case of Medical Air Transport," IJERPH, MDPI, vol. 19(7), pages 1-18, April.
    4. Ahmed Zainul Abideen & Jaafar Pyeman & Veera Pandiyan Kaliani Sundram & Ming-Lang Tseng & Shahryar Sorooshian, 2021. "Leveraging Capabilities of Technology into a Circular Supply Chain to Build Circular Business Models: A State-of-the-Art Systematic Review," Sustainability, MDPI, vol. 13(16), pages 1-26, August.
    5. Hana Tomaskova & Martin Kopecky, 2020. "Specialization of Business Process Model and Notation Applications in Medicine—A Review," Data, MDPI, vol. 5(4), pages 1-42, October.

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