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Applications of Agent-Based Modeling and Simulation to Healthcare Operations Management

In: Handbook of Healthcare Operations Management

Author

Listed:
  • Sean Barnes

    (University of Maryland)

  • Bruce Golden

    (University of Maryland)

  • Stuart Price

    (University of Maryland)

Abstract

Agent-based modeling (ABM) is rapidly gaining momentum in many fields, and it has added to the insights previously contributed by other modeling and simulation methods such as system dynamics and discrete event simulation. Healthcare operations management is one field that is particularly well-suited for ABM because it involves many individuals that interact in different ways. ABM is capable of explicitly modeling these individuals and the interactions among them, which facilitates the discovery of system behavior that cannot be observed using other methods. ABM has been applied successfully to several focus areas within the field of healthcare operations management, including, but not limited to: healthcare delivery, epidemiology, economics, and policy. In this chapter, we review and evaluate a selected body of research in which agent-based modeling and simulation techniques are applied to problems in healthcare. We also highlight specific areas where agent-based modeling and simulation filled a significant gap that was not addressed previously by other methods. Finally, we propose some new questions in the field which may be of interest moving forward.

Suggested Citation

  • Sean Barnes & Bruce Golden & Stuart Price, 2013. "Applications of Agent-Based Modeling and Simulation to Healthcare Operations Management," International Series in Operations Research & Management Science, in: Brian T. Denton (ed.), Handbook of Healthcare Operations Management, edition 127, chapter 0, pages 45-74, Springer.
  • Handle: RePEc:spr:isochp:978-1-4614-5885-2_3
    DOI: 10.1007/978-1-4614-5885-2_3
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    Citations

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    Cited by:

    1. Hideaki Takagi & Yuta Kanai & Kazuo Misue, 2017. "Queueing network model for obstetric patient flow in a hospital," Health Care Management Science, Springer, vol. 20(3), pages 433-451, September.
    2. Irena Ali & Mathew Zuparic & Iain Macleod & Phuong La & Yi Yue, 2017. "Complex socio-organisational phenomena and ill-defined problem spaces: a multi-method approach to the rescue," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(8), pages 919-934, August.
    3. Verónica Duque-Uribe & William Sarache & Elena Valentina Gutiérrez, 2019. "Sustainable Supply Chain Management Practices and Sustainable Performance in Hospitals: A Systematic Review and Integrative Framework," Sustainability, MDPI, vol. 11(21), pages 1-30, October.
    4. Muge Capan & Anahita Khojandi & Brian T. Denton & Kimberly D. Williams & Turgay Ayer & Jagpreet Chhatwal & Murat Kurt & Jennifer Mason Lobo & Mark S. Roberts & Greg Zaric & Shengfan Zhang & J. Sanford, 2017. "From Data to Improved Decisions: Operations Research in Healthcare Delivery," Medical Decision Making, , vol. 37(8), pages 849-859, November.
    5. Mário Amorim Lopes & Álvaro Santos Almeida & Bernardo Almada-Lobo, 2018. "Forecasting the medical workforce: a stochastic agent-based simulation approach," Health Care Management Science, Springer, vol. 21(1), pages 52-75, March.
    6. 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.

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