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Stochastic online appointment scheduling of multi-step sequential procedures in nuclear medicine

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  • Eduardo Pérez
  • Lewis Ntaimo
  • César Malavé
  • Carla Bailey
  • Peter McCormack

Abstract

The increased demand for medical diagnosis procedures has been recognized as one of the contributors to the rise of health care costs in the U.S. in the last few years. Nuclear medicine is a subspecialty of radiology that uses advanced technology and radiopharmaceuticals for the diagnosis and treatment of medical conditions. Procedures in nuclear medicine require the use of radiopharmaceuticals, are multi-step, and have to be performed under strict time window constraints. These characteristics make the scheduling of patients and resources in nuclear medicine challenging. In this work, we derive a stochastic online scheduling algorithm for patient and resource scheduling in nuclear medicine departments which take into account the time constraints imposed by the decay of the radiopharmaceuticals and the stochastic nature of the system when scheduling patients. We report on a computational study of the new methodology applied to a real clinic. We use both patient and clinic performance measures in our study. The results show that the new method schedules about 600 more patients per year on average than a scheduling policy that was used in practice by improving the way limited resources are managed at the clinic. The new methodology finds the best start time and resources to be used for each appointment. Furthermore, the new method decreases patient waiting time for an appointment by about two days on average. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • 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.
    • Handle: RePEc:kap:hcarem:v:16:y:2013:i:4:p:281-299
    DOI: 10.1007/s10729-013-9224-4
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    References listed on IDEAS

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    Cited by:

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    4. 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.
    5. 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.
    6. Marynissen, Joren & Demeulemeester, Erik, 2019. "Literature review on multi-appointment scheduling problems in hospitals," European Journal of Operational Research, Elsevier, vol. 272(2), pages 407-419.
    7. 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.
    8. Dogru, Ali K. & Melouk, Sharif H., 2019. "Adaptive appointment scheduling for patient-centered medical homes," Omega, Elsevier, vol. 85(C), pages 166-181.
    9. Sharan Srinivas & A. Ravi Ravindran, 2020. "Designing schedule configuration of a hybrid appointment system for a two-stage outpatient clinic with multiple servers," Health Care Management Science, Springer, vol. 23(3), pages 360-386, September.
    10. Mostafa Khatami & Amir Salehipour, 2021. "Coupled task scheduling with time-dependent processing times," Journal of Scheduling, Springer, vol. 24(2), pages 223-236, April.
    11. William P. Millhiser & Emre A. Veral, 2019. "A decision support system for real-time scheduling of multiple patient classes in outpatient services," Health Care Management Science, Springer, vol. 22(1), pages 180-195, March.
    12. Dina Bentayeb & Nadia Lahrichi & Louis-Martin Rousseau, 2023. "On integrating patient appointment grids and technologist schedules in a radiology center," Health Care Management Science, Springer, vol. 26(1), pages 62-78, March.
    13. Xuanzhu Fan & Jiafu Tang & Chongjun Yan, 2020. "Appointment scheduling optimization with two stages diagnosis for clinic outpatient," Computational Statistics, Springer, vol. 35(2), pages 469-490, June.
    14. Hyun-Jung Alvarez-Oh & Hari Balasubramanian & Ekin Koker & Ana Muriel, 2018. "Stochastic Appointment Scheduling in a Team Primary Care Practice with Two Flexible Nurses and Two Dedicated Providers," Service Science, INFORMS, vol. 10(3), pages 241-260, September.
    15. Andrés Miniguano-Trujillo & Fernanda Salazar & Ramiro Torres & Patricio Arias & Koraima Sotomayor, 2021. "An integer programming model to assign patients based on mental health impact for tele-psychotherapy intervention during the Covid–19 emergency," Health Care Management Science, Springer, vol. 24(2), pages 286-304, June.
    16. Ahmadi-Javid, Amir & Jalali, Zahra & Klassen, Kenneth J, 2017. "Outpatient appointment systems in healthcare: A review of optimization studies," European Journal of Operational Research, Elsevier, vol. 258(1), pages 3-34.
    17. Mostafa Khatami & Amir Salehipour, 2021. "A binary search algorithm for the general coupled task scheduling problem," 4OR, Springer, vol. 19(4), pages 593-611, December.

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