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Robust Overbooking for No-Shows and Cancellations in Healthcare

Author

Listed:
  • Feng Xiao

    (International Business School, Shaanxi Normal University, Xi’an 710119, China)

  • Kin Keung Lai

    (International Business School, Shaanxi Normal University, Xi’an 710119, China)

  • Chun Kit Lau

    (Faculty of Business and Management, Beijing Normal University—Hong Kong Baptist University United International College, Zhuhai 519000, China)

  • Bhagwat Ram

    (Delhi School of Analytics, Institution of Eminence, University of Delhi, Delhi 110007, India)

Abstract

Any country’s healthcare system is vital for its progress, quality of life, and long-term viability. During the pandemic, many developed countries encountered challenges of differing degrees in the administration of their healthcare systems. The overloading of healthcare services is common, leading to prolonged waiting times for medical services. Thus, the wastage of hospital resources must be taken seriously. In this paper, we examine the problem of no-shows and cancellations in outpatient clinics. By examining the literature and drawing from practical industry experience, we uncover the operational procedures of these clinics. We then suggest a robust optimization strategy for overbooking, incorporating both a conventional overbooking model and a resilient system approach. The proposed model seeks to address the substantial uncertainties in parameters encountered during the pandemic. Taking into account risk aversion, we develop an optimal overbooking policy that considers the associated costs. The primary contribution lies in introducing an alternative approach to manage the uncertainty of no-shows and cancellations through the utilization of an overbooking technique.

Suggested Citation

  • Feng Xiao & Kin Keung Lai & Chun Kit Lau & Bhagwat Ram, 2024. "Robust Overbooking for No-Shows and Cancellations in Healthcare," Mathematics, MDPI, vol. 12(16), pages 1-18, August.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:16:p:2563-:d:1459433
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    References listed on IDEAS

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