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Use of a discrete-event simulation in a Kaizen event: A case study in healthcare

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  • Baril, Chantal
  • Gascon, Viviane
  • Miller, Jonathan
  • Côté, Nadine

Abstract

To improve service delivery, healthcare facilities look toward operations research techniques, discrete event simulation and continuous improvement approaches such as Lean manufacturing. Lean management often includes a Kaizen event to facilitate the acceptance of the project by the employees. Business game is also used as a tool to increase understanding of Lean management concepts. In this paper, we study how a business game can be used jointly with discrete event simulation to test scenarios defined by team members during a Kaizen event. The aim is to allow a rapid and successful implementation of the solutions developed during the Kaizen. Our approach has been used to improve patients’ trajectory in an outpatient hematology–oncology clinic. Patient delays before receiving their treatment were reduced by 74 percent after 19 weeks.

Suggested Citation

  • Baril, Chantal & Gascon, Viviane & Miller, Jonathan & Côté, Nadine, 2016. "Use of a discrete-event simulation in a Kaizen event: A case study in healthcare," European Journal of Operational Research, Elsevier, vol. 249(1), pages 327-339.
    • Handle: RePEc:eee:ejores:v:249:y:2016:i:1:p:327-339
    DOI: 10.1016/j.ejor.2015.08.036
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    2. Fabiane Letícia Lizarelli & Jiju Antony & José Carlos Toledo, 2020. "Statistical thinking and its impact on operational performance in manufacturing companies: an empirical study," Annals of Operations Research, Springer, vol. 295(2), pages 923-950, December.
    3. Agnetis, Alessandro & Bianciardi, Caterina & Iasparra, Nicola, 2019. "Integrating lean thinking and mathematical optimization: A case study in appointment scheduling of hematological treatments," Operations Research Perspectives, Elsevier, vol. 6(C).
    4. 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.
    5. Sharon J. Williams & Zoe Radnor, 2018. "Using bandwidths to visualize and improve patient pathways," Public Money & Management, Taylor & Francis Journals, vol. 38(1), pages 21-28, January.
    6. Kotiadis, K. & Tako, A.A., 2018. "Facilitated post-model coding in discrete event simulation (DES): A case study in healthcare," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1120-1133.
    7. Sinem Buyuksaatci Kiris & Enes Eryarsoy & Selim Zaim & Dursun Delen, 2023. "An integrated approach for lean production using simulation and data envelopment analysis," Annals of Operations Research, Springer, vol. 320(2), pages 863-886, January.
    8. Diego Tlapa & Guilherme Tortorella & Flavio Fogliatto & Maneesh Kumar & Alejandro Mac Cawley & Roberto Vassolo & Luis Enberg & Yolanda Baez-Lopez, 2022. "Effects of Lean Interventions Supported by Digital Technologies on Healthcare Services: A Systematic Review," IJERPH, MDPI, vol. 19(15), pages 1-23, July.
    9. Guillaume Lamé & Oualid Jouini & Julie Stal-Le Cardinal, 2016. "Outpatient Chemotherapy Planning: a Literature Review with Insights from a Case Study," Post-Print hal-01324488, HAL.
    10. Proudlove, N.C. & Bisogno, S. & Onggo, B.S.S. & Calabrese, A. & Levialdi Ghiron, N., 2017. "Towards fully-facilitated discrete event simulation modelling: Addressing the model coding stage," European Journal of Operational Research, Elsevier, vol. 263(2), pages 583-595.
    11. 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.
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