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Solving the operating room scheduling problem with prioritized lists of patients

Author

Listed:
  • Guillermo Durán

    (Universidad de Chile
    Universidad de Buenos Aires
    CONICET)

  • Pablo A. Rey

    (Universidad de Chile)

  • Patricio Wolff

    (Universidad de Chile)

Abstract

The scheduling of surgical interventions directly impacts the number of patients that can be treated with given operating room resources. Medical centres often do not respond satisfactorily to the demand for interventions, and the shortcomings of traditional manual scheduling approaches contribute to the growth of waiting lists. In addition to the timetabling aspect, operating room scheduling methods must determine the order in which patients should be treated as a function of their relative priorities. This paper develops and compares two optimization models and two algorithms for scheduling interventions over a defined period that satisfy patient priority criteria. The four mathematical methods were studied under a range of different scenarios using real data from a public hospital in Chile. Improvements in operating room utilization rates using the proposed formulations ranged from 10 to 15 % over the current manual techniques, but the choice of method in any given real application will depend on the scenarios likely to be encountered.

Suggested Citation

  • Guillermo Durán & Pablo A. Rey & Patricio Wolff, 2017. "Solving the operating room scheduling problem with prioritized lists of patients," Annals of Operations Research, Springer, vol. 258(2), pages 395-414, November.
    • Handle: RePEc:spr:annopr:v:258:y:2017:i:2:d:10.1007_s10479-016-2172-x
    DOI: 10.1007/s10479-016-2172-x
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    References listed on IDEAS

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    Cited by:

    1. Sean Harris & David Claudio, 2022. "Current Trends in Operating Room Scheduling 2015 to 2020: a Literature Review," SN Operations Research Forum, Springer, vol. 3(1), pages 1-42, March.
    2. Shuwan Zhu & Wenjuan Fan & Shanlin Yang & Jun Pei & Panos M. Pardalos, 2019. "Operating room planning and surgical case scheduling: a review of literature," Journal of Combinatorial Optimization, Springer, vol. 37(3), pages 757-805, April.
    3. Jian-Jun Wang & Zongli Dai & Ai-Chih Chang & Jim Junmin Shi, 2022. "Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations," Annals of Operations Research, Springer, vol. 315(1), pages 463-505, August.
    4. Rachuba, Sebastian & Imhoff, Lisa & Werners, Brigitte, 2022. "Tactical blueprints for surgical weeks – An integrated approach for operating rooms and intensive care units," European Journal of Operational Research, Elsevier, vol. 298(1), pages 243-260.
    5. Ana Batista & Jorge Vera & David Pozo, 2020. "Multi-objective admission planning problem: a two-stage stochastic approach," Health Care Management Science, Springer, vol. 23(1), pages 51-65, March.
    6. Omolbanin Mashkani & Andreas T. Ernst & Dhananjay Thiruvady & Hanyu Gu, 2023. "Minimizing patients total clinical condition deterioration in operating theatre departments," Annals of Operations Research, Springer, vol. 328(1), pages 821-857, September.
    7. F. Davarian & J. Behnamian, 2022. "Robust finite-horizon scheduling/rescheduling of operating rooms with elective and emergency surgeries under resource constraints," Journal of Scheduling, Springer, vol. 25(6), pages 625-641, December.

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