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Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network

Author

Listed:
  • Dongyang Wang

    (McCombs School of Business, University of Texas, Austin, Texas 78712)

  • Kumar Muthuraman

    (McCombs School of Business, University of Texas, Austin, Texas 78712)

  • Douglas Morrice

    (McCombs School of Business, University of Texas, Austin, Texas 78712)

Abstract

Outpatient services account for more than four-fifths of patient care in the United States, and most patients access these services via appointment scheduling. Because of the possibility of patient no-shows, healthcare providers usually rely on overbooking. If very few patients show up, it will leave hospital resources underutilized, whereas too many showing up will increase patient wait times and increase staff overtime costs. In a hospital or a network of clinics, where patients could enter and exit at various stations and have complex flow patterns, scheduling becomes even more of a challenge. In “Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network,” D. Wang, K. Muthuraman, and D. Morrice propose a multistation network model that carefully strikes a balance between assumptions that allow tractability and assumptions that disallow real-world adoption. Given the complexity involved in solving the model, they explore a sequence of approximations and find one that offers a significant computational advantage.

Suggested Citation

  • Dongyang Wang & Kumar Muthuraman & Douglas Morrice, 2019. "Coordinated Patient Appointment Scheduling for a Multistation Healthcare Network," Operations Research, INFORMS, vol. 67(3), pages 599-618, May.
    • Handle: RePEc:inm:oropre:v:67:y:2019:i:3:p:599-618
    DOI: 10.1287/opre.2018.1816
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    References listed on IDEAS

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    6. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    7. Minglong Zhou & Melvyn Sim & Shao‐Wei Lam, 2022. "Advance admission scheduling via resource satisficing," Production and Operations Management, Production and Operations Management Society, vol. 31(11), pages 4002-4020, November.

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