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Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming

Author

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  • Michelle Alvarado

    (Texas A&M University College Station College Station)

  • Lewis Ntaimo

    (Texas A&M University College Station College Station)

Abstract

Oncology clinics are often burdened with scheduling large volumes of cancer patients for chemotherapy treatments under limited resources such as the number of nurses and chairs. These cancer patients require a series of appointments over several weeks or months and the timing of these appointments is critical to the treatment’s effectiveness. Additionally, the appointment duration, the acuity levels of each appointment, and the availability of clinic nurses are uncertain. The timing constraints, stochastic parameters, rising treatment costs, and increased demand of outpatient oncology clinic services motivate the need for efficient appointment schedules and clinic operations. In this paper, we develop three mean-risk stochastic integer programming (SIP) models, referred to as SIP-CHEMO, for the problem of scheduling individual chemotherapy patient appointments and resources. These mean-risk models are presented and an algorithm is devised to improve computational speed. Computational results were conducted using a simulation model and results indicate that the risk-averse SIP-CHEMO model with the expected excess mean-risk measure can decrease patient waiting times and nurse overtime when compared to deterministic scheduling algorithms by 42 % and 27 %, respectively.

Suggested Citation

  • Michelle Alvarado & Lewis Ntaimo, 2018. "Chemotherapy appointment scheduling under uncertainty using mean-risk stochastic integer programming," Health Care Management Science, Springer, vol. 21(1), pages 87-104, March.
  • Handle: RePEc:kap:hcarem:v:21:y:2018:i:1:d:10.1007_s10729-016-9380-4
    DOI: 10.1007/s10729-016-9380-4
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    References listed on IDEAS

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    1. Trine Kristoffersen, 2005. "Deviation Measures in Linear Two-Stage Stochastic Programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 62(2), pages 255-274, November.
    2. Eduardo Pérez & Lewis Ntaimo & César Malavé & Carla Bailey & Peter McCormack, 2013. "Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine," Health Care Management Science, Springer, vol. 16(4), pages 281-299, December.
    3. Yasin Gocgun & Martin Puterman, 2014. "Dynamic scheduling with due dates and time windows: an application to chemotherapy patient appointment booking," Health Care Management Science, Springer, vol. 17(1), pages 60-76, March.
    4. Shoshana Hahn-Goldberg & Michael Carter & J. Beck & Maureen Trudeau & Philomena Sousa & Kathy Beattie, 2014. "Dynamic optimization of chemotherapy outpatient scheduling with uncertainty," Health Care Management Science, Springer, vol. 17(4), pages 379-392, December.
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    Citations

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    Cited by:

    1. Hadid, Majed & Elomri, Adel & Mekkawy, Tarek El & Jouini, Oualid & Kerbache, Laoucine & Hamad, Anas, 2022. "Operations management of outpatient chemotherapy process: An optimization-oriented comprehensive review," Operations Research Perspectives, Elsevier, vol. 9(C).
    2. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.
    3. Alireza F. Hesaraki & Nico P. Dellaert & Ton Kok, 2023. "Online scheduling using a fixed template: the case of outpatient chemotherapy drug administration," Health Care Management Science, Springer, vol. 26(1), pages 117-137, March.
    4. Nur Banu Demir & Serhat Gul & Melih Çelik, 2021. "A stochastic programming approach for chemotherapy appointment scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 112-133, February.
    5. Pilar I. Vidal-Carreras & Julio J. Garcia-Sabater & Juan A. Marin-Garcia, 2022. "Applying Value Stream Mapping to Improve the Delivery of Patient Care in the Oncology Day Hospital," IJERPH, MDPI, vol. 19(7), pages 1-18, April.
    6. Namakshenas, Mohammad & Mazdeh, Mohammad Mahdavi & Braaksma, Aleida & Heydari, Mehdi, 2023. "Appointment scheduling for medical diagnostic centers considering time-sensitive pharmaceuticals: A dynamic robust optimization approach," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1018-1031.
    7. Golmohammadi, Davood & Zhao, Lingyu & Dreyfus, David, 2023. "Using machine learning techniques to reduce uncertainty for outpatient appointment scheduling practices in outpatient clinics," Omega, Elsevier, vol. 120(C).
    8. Karakaya, Sırma & Gul, Serhat & Çelik, Melih, 2023. "Stochastic scheduling of chemotherapy appointments considering patient acuity levels," European Journal of Operational Research, Elsevier, vol. 305(2), pages 902-916.
    9. Mona Issabakhsh & Seokgi Lee & Hyojung Kang, 2021. "Scheduling patient appointment in an infusion center: a mixed integer robust optimization approach," Health Care Management Science, Springer, vol. 24(1), pages 117-139, March.

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