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Operating room planning and surgical case scheduling: a review of literature

Author

Listed:
  • Shuwan Zhu

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education)

  • Wenjuan Fan

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education)

  • Shanlin Yang

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education)

  • Jun Pei

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-making of Ministry of Education
    University of Florida)

  • Panos M. Pardalos

    (University of Florida)

Abstract

This paper provides a comprehensive survey of research on operating room planning and scheduling problems. Aiming to give a comprehensive classification on the studied problems, we review the literature from the perspectives of decision level, scheduling strategy, patient characteristics, problem setting, uncertainty, mathematical models, and solutions and methods. The papers are reviewed in diversified ways so as to obtain a detailed overview in this area, and the fields that need to be focused on are summarized. It shows that mathematical programming and heuristics are frequently applied in the complex linear and combinatorial optimization problems. Furthermore, future research trends and directions on operating room planning and scheduling are also identified.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:jcomop:v:37:y:2019:i:3:d:10.1007_s10878-018-0322-6
    DOI: 10.1007/s10878-018-0322-6
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    Cited by:

    1. Kevin Taaffe & Yann B. Ferrand & Amin Khoshkenar & Lawrence Fredendall & Dee San & Patrick Rosopa & Anjali Joseph, 2023. "Operating room design using agent-based simulation to reduce room obstructions," Health Care Management Science, Springer, vol. 26(2), pages 261-278, June.
    2. 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.
    3. Belinda Spratt & Erhan Kozan, 2021. "An integrated rolling horizon approach to increase operating theatre efficiency," Journal of Scheduling, Springer, vol. 24(1), pages 3-25, February.
    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. Roberto Aringhieri & Patrick Hirsch & Marion S. Rauner & Melanie Reuter-Oppermanns & Margit Sommersguter-Reichmann, 2022. "Central European journal of operations research (CJOR) “operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria”," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(1), pages 1-18, March.
    6. Yun Zhou & Mahmut Parlar & Vedat Verter & Shannon Fraser, 2021. "Surgical Scheduling with Constrained Patient Waiting Times," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3253-3271, September.
    7. Lien Wang & Erik Demeulemeester & Nancy Vansteenkiste & Frank E. Rademakers, 2022. "On the use of partitioning for scheduling of surgeries in the inpatient surgical department," Health Care Management Science, Springer, vol. 25(4), pages 526-550, December.
    8. Yuan Shi & Saied Mahdian & Jose Blanchet & Peter Glynn & Andrew Y. Shin & David Scheinker, 2023. "Surgical scheduling via optimization and machine learning with long-tailed data," Health Care Management Science, Springer, vol. 26(4), pages 692-718, December.
    9. Seokjun Youn & H. Neil Geismar & Michael Pinedo, 2022. "Planning and scheduling in healthcare for better care coordination: Current understanding, trending topics, and future opportunities," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4407-4423, December.
    10. Yanbo Ma & Kaiyue Liu & Zheng Li & Xiang Chen, 2022. "Robust Operating Room Scheduling Model with Violation Probability Consideration under Uncertain Surgery Duration," IJERPH, MDPI, vol. 19(20), pages 1-20, October.
    11. van den Broek d’Obrenan, Anne & Ridder, Ad & Roubos, Dennis & Stougie, Leen, 2020. "Minimizing bed occupancy variance by scheduling patients under uncertainty," European Journal of Operational Research, Elsevier, vol. 286(1), pages 336-349.
    12. Grigory Korzhenevich & Anne Zander, 2024. "Leveraging the potential of the German operating room benchmarking initiative for planning: A ready-to-use surgical process data set," Health Care Management Science, Springer, vol. 27(3), pages 328-351, September.
    13. Akbarzadeh, Babak & Maenhout, Broos, 2024. "A study on policy decisions to embed flexibility for reactive recovery in the planning and scheduling process in operating rooms," Omega, Elsevier, vol. 126(C).
    14. 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.
    15. Santos, Daniel & Marques, Inês, 2022. "Designing master surgery schedules with downstream unit integration via stochastic programming," European Journal of Operational Research, Elsevier, vol. 299(3), pages 834-852.
    16. 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.
    17. Jian-Jun Wang & Zongli Dai & Wenxuan Zhang & Jim Junmin Shi, 2023. "Operating room scheduling for non-operating room anesthesia with emergency uncertainty," Annals of Operations Research, Springer, vol. 321(1), pages 565-588, February.
    18. Şeyda Gür & Mehmet Pınarbaşı & Hacı Mehmet Alakaş & Tamer Eren, 2023. "Operating room scheduling with surgical team: a new approach with constraint programming and goal programming," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(4), pages 1061-1085, December.
    19. Pazoki, Mostafa & Samarghandi, Hamed, 2021. "Regulating patient care in walk-in clinics," Omega, Elsevier, vol. 99(C).
    20. Miao Bai & Robert H. Storer & Gregory L. Tonkay, 2022. "Surgery Sequencing Coordination with Recovery Resource Constraints," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1207-1223, March.
    21. 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.
    22. Alexander Alekseevich Lazarev & Darya Vladimirovna Lemtyuzhnikova & Mikhail Lvovich Somov, 2022. "Decomposition of the Knapsack Problem for Increasing the Capacity of Operating Rooms," Mathematics, MDPI, vol. 10(5), pages 1-18, March.
    23. Shao, Kaining & Fan, Wenjuan & Lan, Shaowen & Kong, Min & Yang, Shanlin, 2023. "A column generation-based heuristic for brachytherapy patient scheduling with multiple treatment sessions considering radioactive source decay and time constraints," Omega, Elsevier, vol. 118(C).
    24. Marco Caserta & Antonio García Romero, 2024. "A novel approach to forecast surgery durations using machine learning techniques," Health Care Management Science, Springer, vol. 27(3), pages 313-327, September.
    25. Pinar Keskinocak & Nicos Savva, 2020. "A Review of the Healthcare-Management (Modeling) Literature Published in Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 59-72, January.

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    6. Range, Troels Martin & Kozlowski, Dawid & Petersen, Niels Chr., 2019. "Dynamic job assignment: A column generation approach with an application to surgery allocation," European Journal of Operational Research, Elsevier, vol. 272(1), pages 78-93.
    7. Babak Akbarzadeh & Ghasem Moslehi & Mohammad Reisi-Nafchi & Broos Maenhout, 2020. "A diving heuristic for planning and scheduling surgical cases in the operating room department with nurse re-rostering," Journal of Scheduling, Springer, vol. 23(2), pages 265-288, April.
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