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Article

Robust Overbooking for No-Shows and Cancellations in Healthcare

1
International Business School, Shaanxi Normal University, Xi’an 710119, China
2
Faculty of Business and Management, Beijing Normal University—Hong Kong Baptist University United International College, Zhuhai 519000, China
3
Delhi School of Analytics, Institution of Eminence, University of Delhi, Delhi 110007, India
*
Author to whom correspondence should be addressed.
Mathematics 2024, 12(16), 2563; https://doi.org/10.3390/math12162563
Submission received: 1 June 2024 / Revised: 7 August 2024 / Accepted: 16 August 2024 / Published: 19 August 2024

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.
Keywords: robust optimization; overbooking; no-shows; healthcare robust optimization; overbooking; no-shows; healthcare

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MDPI and ACS Style

Xiao, F.; Lai, K.K.; Lau, C.K.; Ram, B. Robust Overbooking for No-Shows and Cancellations in Healthcare. Mathematics 2024, 12, 2563. https://doi.org/10.3390/math12162563

AMA Style

Xiao F, Lai KK, Lau CK, Ram B. Robust Overbooking for No-Shows and Cancellations in Healthcare. Mathematics. 2024; 12(16):2563. https://doi.org/10.3390/math12162563

Chicago/Turabian Style

Xiao, Feng, Kin Keung Lai, Chun Kit Lau, and Bhagwat Ram. 2024. "Robust Overbooking for No-Shows and Cancellations in Healthcare" Mathematics 12, no. 16: 2563. https://doi.org/10.3390/math12162563

APA Style

Xiao, F., Lai, K. K., Lau, C. K., & Ram, B. (2024). Robust Overbooking for No-Shows and Cancellations in Healthcare. Mathematics, 12(16), 2563. https://doi.org/10.3390/math12162563

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