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The Scheduling of Medical Students at Ghent University

Author

Listed:
  • Babak Akbarzadeh

    (Faculty of Economics and Business Administration, Ghent University, 9000 Ghent, Belgium)

  • Johan Wouters

    (Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium)

  • Carl Sys

    (Faculty of Medicine and Health Sciences, Ghent University, 9000 Ghent, Belgium)

  • Broos Maenhout

    (Faculty of Economics and Business Administration, Ghent University, 9000 Ghent, Belgium; FlandersMake@UGent – corelab CVAMO, 9000 Ghent, Belgium)

Abstract

Each year, the faculty of medicine and health sciences (Ghent University, Belgium) has to compose a medical student roster, assigning graduate students to different internships over the course of the academic year. An internship embodies a specific medical discipline and is carried out at a local hospital. This problem is complex because of conflicting requirements of different involved stakeholders, comprising educational requirements set by the university, limited capacity of local hospitals offering internships, and student preferences and requests. In this paper, we discuss a heuristic and required calibration to attain high-quality rosters, and it builds upon different decomposition-based heuristic solution steps and different control mechanisms to regulate the candidate assignments in each step. The proposed heuristic meets the software requirements of the university and is implemented as the scheduling module in the information system of the faculty to manage student internships. Computational experiments are carried out on real-life data related to the academic year 2020–2021 to validate the performance of the heuristic and the different improvement mechanisms. In addition, we demonstrate the use of the software as a simulation tool to devise different managerial insights relevant for the university with regard to curriculum design and student preferences.

Suggested Citation

  • Babak Akbarzadeh & Johan Wouters & Carl Sys & Broos Maenhout, 2022. "The Scheduling of Medical Students at Ghent University," Interfaces, INFORMS, vol. 52(4), pages 303-323, July.
  • Handle: RePEc:inm:orinte:v:52:y:2022:i:4:p:303-323
    DOI: 10.1287/inte.2022.1116
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    References listed on IDEAS

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    1. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
    2. Belien, Jeroen & Demeulemeester, Erik, 2006. "Scheduling trainees at a hospital department using a branch-and-price approach," European Journal of Operational Research, Elsevier, vol. 175(1), pages 258-278, November.
    3. Kraul, Sebastian & Fügener, Andreas & Brunner, Jens O. & Blobner, Manfred, 2019. "A robust framework for task-related resident scheduling," European Journal of Operational Research, Elsevier, vol. 276(2), pages 656-675.
    4. Lori S. Franz & Janis L. Miller, 1993. "Scheduling Medical Residents to Rotations: Solving the Large-Scale Multiperiod Staff Assignment Problem," Operations Research, INFORMS, vol. 41(2), pages 269-279, April.
    5. Mengyu Guo & Su Wu & Binfeng Li & Jie Song & Youping Rong, 2016. "Integrated scheduling of elective surgeries and surgical nurses for operating room suites," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 166-181, June.
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    Cited by:

    1. Kraul, Sebastian & Brunner, Jens O., 2023. "Stable annual scheduling of medical residents using prioritized multiple training schedules to combat operational uncertainty," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1263-1278.

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