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A Simulation Optimization Approach to Long-Term Care Capacity Planning

Author

Listed:
  • Yue Zhang

    (College of Business and Innovation, University of Toledo, Toledo, Ohio 43606)

  • Martin L. Puterman

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

  • Matthew Nelson

    (Centre for Research in Healthcare Engineering, University of Toronto, Toronto, Ontario M5S 3G8, Canada)

  • Derek Atkins

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia V6T 1Z2, Canada)

Abstract

This paper describes a methodology for setting long-term care capacity levels over a multiyear planning horizon to achieve target wait time service levels. Our approach integrates demographic and survival analysis, discrete event simulation, and optimization. Based on this methodology, we developed a decision support system for use in practice. We illustrate this approach through two case studies: one for a regional health authority in British Columbia, Canada, and the other for a long-term care facility. We also compare our approach to the fixed ratio approach used in practice and the SIPP (stationary, independent, period by period) and MOL (modified offered load) approaches developed in the call center literature. Our results suggest that our approach is preferable. The fixed ratio approach lacks a rigorous foundation, and the SIPP and MOL approaches do not perform reliably mainly because of long service times. We conclude the paper with policy recommendations.

Suggested Citation

  • Yue Zhang & Martin L. Puterman & Matthew Nelson & Derek Atkins, 2012. "A Simulation Optimization Approach to Long-Term Care Capacity Planning," Operations Research, INFORMS, vol. 60(2), pages 249-261, April.
    • Handle: RePEc:inm:oropre:v:60:y:2012:i:2:p:249-261
    DOI: 10.1287/opre.1110.1026
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    References listed on IDEAS

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    4. Defraeye, Mieke & Van Nieuwenhuyse, Inneke, 2016. "Staffing and scheduling under nonstationary demand for service: A literature review," Omega, Elsevier, vol. 58(C), pages 4-25.
    5. Cardoso, Teresa & Oliveira, Mónica Duarte & Barbosa-Póvoa, Ana & Nickel, Stefan, 2016. "Moving towards an equitable long-term care network: A multi-objective and multi-period planning approach," Omega, Elsevier, vol. 58(C), pages 69-85.
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    9. Liping Zhou & Na Geng & Zhibin Jiang & Shan Jiang, 2022. "Integrated Multiresource Capacity Planning and Multitype Patient Scheduling," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 129-149, January.
    10. Cardoso, Teresa & Oliveira, Mónica Duarte & Barbosa-Póvoa, Ana & Nickel, Stefan, 2015. "An integrated approach for planning a long-term care network with uncertainty, strategic policy and equity considerations," European Journal of Operational Research, Elsevier, vol. 247(1), pages 321-334.
    11. Ya‐Tang Chuang & Manaf Zargoush & Somayeh Ghazalbash & Saied Samiedaluie & Kerry Kuluski & Sara Guilcher, 2023. "From prediction to decision: Optimizing long‐term care placements among older delayed discharge patients," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1041-1058, April.
    12. Noa Zychlinski & Avishai Mandelbaum & Petar Momčilović & Izack Cohen, 2020. "Bed Blocking in Hospitals Due to Scarce Capacity in Geriatric Institutions—Cost Minimization via Fluid Models," Manufacturing & Service Operations Management, INFORMS, vol. 22(2), pages 396-411, March.
    13. Paul Intrevado & Vedat Verter & Lucie Tremblay, 2019. "Patient-centric design of long-term care networks," Health Care Management Science, Springer, vol. 22(2), pages 376-390, June.
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    16. Yue Zhang & Martin Puterman, 2013. "Developing an adaptive policy for long-term care capacity planning," Health Care Management Science, Springer, vol. 16(3), pages 271-279, September.

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