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Developing an optimal appointment scheduling for systems with rigid standby time under pre-determined quality of service

Author

Listed:
  • Illana Bendavid

    (ORT Braude College of Engineering)

  • Yariv N. Marmor

    (ORT Braude College of Engineering)

  • Boris Shnits

    (ORT Braude College of Engineering)

Abstract

A critical step in patient care path is diagnosis. The demand for advanced imaging tests, such as computerized axial tomography, magnetic resonance imaging and positron emission tomography (PET), increased dramatically in the past 15 years. Since imaging equipment remains relatively expensive, in order to fit the demand, the imaging resources must be managed effectively while ensuring required quality of service. In PET, a radiopharmaceutical (radioactive substance) is injected to patients prior to their scans. The time between substance injection and scan (standby or uptake time) is rigid. This constraint makes the patient appointment scheduling more challenging, because if at the end of the expected uptake time the scanner is not available, the quality of the scan is jeopardized (due to short half-life duration of the substance). The availability of the scanner is a consequence of prior scans’ appointments and durations. The aim of this work is to develop an approach for appointment scheduling in a system with one scanner, given a sequence of patients and rigid uptake time, in order to minimize the length of day while satisfying a minimal pre-determined quality of service. In order to solve this stochastic problem, we formulate its equivalent deterministic problem, based on simulated data, as a mixed-integer linear programming. To overcome the dimensionality limitations, we develop a simulation-based sequential algorithm that solves the problem in a reasonable time. We found that a fixed slot per scan policy, as a benchmark, is inferior to our method, especially in achieving stable and fair quality of service for patients.

Suggested Citation

  • Illana Bendavid & Yariv N. Marmor & Boris Shnits, 2018. "Developing an optimal appointment scheduling for systems with rigid standby time under pre-determined quality of service," Flexible Services and Manufacturing Journal, Springer, vol. 30(1), pages 54-77, June.
    • Handle: RePEc:spr:flsman:v:30:y:2018:i:1:d:10.1007_s10696-016-9270-6
    DOI: 10.1007/s10696-016-9270-6
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    References listed on IDEAS

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    1. Illana Bendavid & Boaz Golany, 2009. "Setting gates for activities in the stochastic project scheduling problem through the cross entropy methodology," Annals of Operations Research, Springer, vol. 172(1), pages 259-276, November.
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    Cited by:

    1. Yong-Hong Kuo & Hari Balasubramanian & Yan Chen, 2020. "Medical appointment overbooking and optimal scheduling: tradeoffs between schedule efficiency and accessibility to service," Flexible Services and Manufacturing Journal, Springer, vol. 32(1), pages 72-101, March.
    2. Zhou, Shenghai & Li, Debiao & Yin, Yong, 2021. "Coordinated appointment scheduling with multiple providers and patient-and-physician matching cost in specialty care," Omega, Elsevier, vol. 101(C).
    3. Shnits, Boris & Bendavid, Illana & Marmor, Yariv N., 2020. "An appointment scheduling policy for healthcare systems with parallel servers and pre-determined quality of service," Omega, Elsevier, vol. 97(C).
    4. Carolin Bauerhenne & Rainer Kolisch & Andreas S. Schulz, 2024. "Robust Appointment Scheduling with Waiting Time Guarantees," Papers 2402.12561, arXiv.org.

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