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Optimal multiple-period scheduling and sequencing of operating room and intensive care unit

Author

Listed:
  • Abbas Al-Refaie

    (University of Jordan)

  • Mays Judeh

    (University of Jordan)

  • Toly Chen

    (National Chiao Tung University)

Abstract

Operating rooms (ORs), one of the most crucial hospital resources that generate among the highest costs, are prone to bottlenecking. This paper, therefore, proposes optimization models for multiple-period scheduling of patients in ORs and intensive care units (ICUs) as well as for sequencing of patients in the operating theatre. The first model considers scheduling at a minimal total cost, comprising hospitalization, undertime, overtime, and cancelation costs. The second model involves ICU scheduling and patient sequencing in the operating theatre at a minimal total overtime cost. The scheduling and sequencing models were implemented at a hospital that offers comprehensive surgical procedures for all surgical specialties. The research results are expected to improve patient satisfaction and resource efficiency as well as reduce hospital expenses by minimizing overtime, undertime, hospitalization costs, and cancelation costs. These optimization models may provide substantial assistance to decision makers and planners in facilitating coordination among available hospital resources, including ORs, surgeons, and patients, thereby increasing the productivity and efficiency of ORs and ICUs in providing high-quality care. Future research should consider OR scheduling for unexpected events.

Suggested Citation

  • Abbas Al-Refaie & Mays Judeh & Toly Chen, 2018. "Optimal multiple-period scheduling and sequencing of operating room and intensive care unit," Operational Research, Springer, vol. 18(3), pages 645-670, October.
    • Handle: RePEc:spr:operea:v:18:y:2018:i:3:d:10.1007_s12351-016-0287-0
    DOI: 10.1007/s12351-016-0287-0
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    References listed on IDEAS

    as
    1. Lamiri, Mehdi & Xie, Xiaolan & Dolgui, Alexandre & Grimaud, Frederic, 2008. "A stochastic model for operating room planning with elective and emergency demand for surgery," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1026-1037, March.
    2. Guinet, Alain & Chaabane, Sondes, 2003. "Operating theatre planning," International Journal of Production Economics, Elsevier, vol. 85(1), pages 69-81, July.
    3. Elena Tànfani & Angela Testi, 2010. "A pre-assignment heuristic algorithm for the Master Surgical Schedule Problem (MSSP)," Annals of Operations Research, Springer, vol. 178(1), pages 105-119, July.
    4. Angela Testi & Elena Tanfani & Giancarlo Torre, 2007. "A three-phase approach for operating theatre schedules," Health Care Management Science, Springer, vol. 10(2), pages 163-172, June.
    5. Ahmed, Mohamed A. & Alkhamis, Talal M., 2009. "Simulation optimization for an emergency department healthcare unit in Kuwait," European Journal of Operational Research, Elsevier, vol. 198(3), pages 936-942, November.
    6. Jebali, AIda & Hadj Alouane, Atidel B. & Ladet, Pierre, 2006. "Operating rooms scheduling," International Journal of Production Economics, Elsevier, vol. 99(1-2), pages 52-62, February.
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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. 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.
    3. 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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