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Reducing patient-flow delays in surgical suites through determining start-times of surgical cases

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  • Lee, Sangbok
  • Yih, Yuehwern

Abstract

A scheduling strategy to determine starting times of surgeries in multiple operating rooms (OR) is presented. The constraints are resource limit of a downstream facility, post-anesthesia care unit (PACU), and the service time uncertainties. Given sets of surgeries that need to be done on a day, this problem is formulated as a flexible job shop model with fuzzy sets. Patient-waitings in the process flow, clinical resource idling, and total completion times are considered for evaluation. This multi-objective problem is solved by a two-stage decision process. A genetic algorithm is used for determining relative order of surgeries in the first stage and definite starting times for all the surgical cases are obtained by a decision-heuristic in the second stage. The resultant schedule is evaluated by a Monte-Carlo simulation. The performance is shown to be better than our previous approach, a simulation based scheduling which already outperforms simple scheduling rules in regional hospitals. Additionally, the ratio of PACU to OR is examined using the proposed scheduling strategy.

Suggested Citation

  • Lee, Sangbok & Yih, Yuehwern, 2014. "Reducing patient-flow delays in surgical suites through determining start-times of surgical cases," European Journal of Operational Research, Elsevier, vol. 238(2), pages 620-629.
  • Handle: RePEc:eee:ejores:v:238:y:2014:i:2:p:620-629
    DOI: 10.1016/j.ejor.2014.03.043
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    References listed on IDEAS

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    1. Pham, Dinh-Nguyen & Klinkert, Andreas, 2008. "Surgical case scheduling as a generalized job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1011-1025, March.
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    4. M. R. Garey & D. S. Johnson & Ravi Sethi, 1976. "The Complexity of Flowshop and Jobshop Scheduling," Mathematics of Operations Research, INFORMS, vol. 1(2), pages 117-129, May.
    5. Brian Denton & James Viapiano & Andrea Vogl, 2007. "Optimization of surgery sequencing and scheduling decisions under uncertainty," Health Care Management Science, Springer, vol. 10(1), pages 13-24, February.
    6. Cardoen, Brecht & Demeulemeester, Erik & Beliën, Jeroen, 2010. "Operating room planning and scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 201(3), pages 921-932, March.
    7. 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. Eun, Joonyup & Kim, Sang-Phil & Yih, Yuehwern & Tiwari, Vikram, 2019. "Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches," Omega, Elsevier, vol. 86(C), pages 137-153.
    2. Ker, Jun-Ing & Wang, Yichuan & Hajli, Nick, 2018. "Examining the impact of health information systems on healthcare service improvement: The case of reducing in patient-flow delays in a U.S. hospital," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 188-198.
    3. Michael Samudra & Carla Van Riet & Erik Demeulemeester & Brecht Cardoen & Nancy Vansteenkiste & Frank E. Rademakers, 2016. "Scheduling operating rooms: achievements, challenges and pitfalls," Journal of Scheduling, Springer, vol. 19(5), pages 493-525, October.
    4. 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.
    5. Bing Wang & Xingbao Han & Xianxia Zhang & Shaohua Zhang, 2015. "Predictive-reactive scheduling for single surgical suite subject to random emergency surgery," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 949-966, November.
    6. Serhat Gul, 2018. "A Stochastic Programming Approach for Appointment Scheduling Under Limited Availability of Surgery Turnover Teams," Service Science, INFORMS, vol. 10(3), pages 277-288, September.
    7. 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.
    8. 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.
    9. Shuwan Zhu & Wenjuan Fan & Tongzhu Liu & Shanlin Yang & Panos M. Pardalos, 2020. "Dynamic three-stage operating room scheduling considering patient waiting time and surgical overtime costs," Journal of Combinatorial Optimization, Springer, vol. 39(1), pages 185-215, January.
    10. T. Meersman & B. Maenhout, 2022. "Multi-objective optimisation for constructing cyclic appointment schedules for elective and urgent patients," Annals of Operations Research, Springer, vol. 312(2), pages 909-948, May.
    11. Çelik, Batuhan & Gul, Serhat & Çelik, Melih, 2023. "A stochastic programming approach to surgery scheduling under parallel processing principle," Omega, Elsevier, vol. 115(C).

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