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Different stakeholders’ perspectives for a surgical case assignment problem: Deterministic and robust approaches

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  • Marques, Inês
  • Captivo, M. Eugénia

Abstract

Adequate access to health care is one of the main strategic axes considered in the Portuguese National Health Plan. This plan seeks to ensure the best performance and adequacy of care maximizing the use of resources, quality, equity and access. This work results from a close collaboration with a large and publicly funded Portuguese hospital. The aim is to propose a systematic approach to help the surgical planner in the scheduling of elective surgeries, in order to optimize the use of the available surgical resources, and improve equity and access to operated and waiting patients. The decisions to be taken by this surgical case assignment problem are twofold: select patients to be scheduled in the planning horizon from a large waiting list for surgery; and assign a day, an operating room, and a time block to the selected patients. Three versions are modeled in (mixed) integer linear programming: from the administration’s intention up to the surgeons’ current practice, and a halfway reflecting a negotiation with the surgeons. A robust approach is proposed to tackle the uncertain surgeries’ duration without the need to assume a given distribution for these random parameters and allowing to control the level of conservatism in the solutions. Practical and real-sized problems from the hospital are solved providing very good optimization gaps within a short time limit, both for the deterministic and robust approaches. The schedules obtained are analyzed regarding quality and robustness, and are also compared with the surgical schedules performed by the hospital.

Suggested Citation

  • Marques, Inês & Captivo, M. Eugénia, 2017. "Different stakeholders’ perspectives for a surgical case assignment problem: Deterministic and robust approaches," European Journal of Operational Research, Elsevier, vol. 261(1), pages 260-278.
  • Handle: RePEc:eee:ejores:v:261:y:2017:i:1:p:260-278
    DOI: 10.1016/j.ejor.2017.01.036
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    References listed on IDEAS

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    2. Beaulieu, Martin & Bentahar, Omar, 2021. "Digitalization of the healthcare supply chain: A roadmap to generate benefits and effectively support healthcare delivery," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    3. Hossein Hashemi Doulabi & Soheyl Khalilpourazari, 2023. "Stochastic weekly operating room planning with an exponential number of scenarios," Annals of Operations Research, Springer, vol. 328(1), pages 643-664, September.
    4. Mariana Oliveira & Filippo Visintin & Daniel Santos & Inês Marques, 2022. "Flexible master surgery scheduling: combining optimization and simulation in a rolling horizon approach," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 824-858, December.
    5. A, Augustin & P, Jouvet & N, Lahrichi & A, Lodi & LM, Rousseau, 2022. "A data-driven approach to include availability of ICU beds in the planning of the operating room," Omega, Elsevier, vol. 109(C).
    6. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2020. "Column-generation-based heuristic approaches to stochastic surgery scheduling with downstream capacity constraints," International Journal of Production Economics, Elsevier, vol. 229(C).
    7. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    8. Zhang, Jian & Dridi, Mahjoub & El Moudni, Abdellah, 2019. "A two-level optimization model for elective surgery scheduling with downstream capacity constraints," European Journal of Operational Research, Elsevier, vol. 276(2), pages 602-613.
    9. Kamran Kianfar & Arezoo Atighehchian, 2023. "A hybrid heuristic approach to master surgery scheduling with downstream resource constraints and dividable operating room blocks," Annals of Operations Research, Springer, vol. 328(1), pages 727-754, September.
    10. Wang, Kai & Qin, Hu & Huang, Yun & Luo, Mengwen & Zhou, Lei, 2021. "Surgery scheduling in outpatient procedure centre with re-entrant patient flow and fuzzy service times," Omega, Elsevier, vol. 102(C).
    11. da Cunha, Joaquim J. & de Souza, Mauricio C., 2018. "A linearized model for academic staff assignment in a Brazilian university focusing on performance gain in quality indicators," International Journal of Production Economics, Elsevier, vol. 197(C), pages 43-51.
    12. Aringhieri, Roberto & Duma, Davide & Landa, Paolo & Mancini, Simona, 2022. "Combining workload balance and patient priority maximisation in operating room planning through hierarchical multi-objective optimisation," European Journal of Operational Research, Elsevier, vol. 298(2), pages 627-643.
    13. Rafael L. Patrão & Reinaldo C. Garcia & João M. da Silva, 2022. "An Integrated Two-Level Integer Linear Program (ILP) Model for Elective Surgery Scheduling: A Case Study in an Italian Hospital," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
    14. Wang, Yu & Zhang, Yu & Tang, Jiafu, 2019. "A distributionally robust optimization approach for surgery block allocation," European Journal of Operational Research, Elsevier, vol. 273(2), pages 740-753.
    15. Koppka, Lisa & Wiesche, Lara & Schacht, Matthias & Werners, Brigitte, 2018. "Optimal distribution of operating hours over operating rooms using probabilities," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1156-1171.

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