IDEAS home Printed from https://ideas.repec.org/a/kap/hcarem/v25y2022i2d10.1007_s10729-021-09580-2.html
   My bibliography  Save this article

Decision support algorithms for optimizing surgery start times considering the performance variation

Author

Listed:
  • Shing Chih Tsai

    (National Cheng Kung University)

  • Wu Hung Lin

    (National Cheng Kung University)

  • Chia Cheng Wu

    (Cheng Ching General Hospital)

  • Shao Jen Weng

    (Tunghai University)

  • Ching Fen Tang

    (Cheng Ching General Hospital)

Abstract

In this paper, we consider a stochastic optimization model for a surgical scheduling problem with a single operating room. The goal is to determine the optimal start times of multiple elective surgeries within a single day. The term “optimal” is defined as the largest surgically related utility value while achieving a given threshold defined by the performance variation of a reference solution. The optimization problem is analytically intractable because it involves quantities such as expectation and variance formulations. This implies that traditional mathematical programming techniques cannot be directly applied. We propose a decision support algorithm, which is a fully sequential procedure using variance screening in the first phase, and then employing multiple attribute utility theory to select the best solution in the second phase. The numerical experiments show that the proposed algorithm can find a promising solution in a reasonable amount of time.

Suggested Citation

  • Shing Chih Tsai & Wu Hung Lin & Chia Cheng Wu & Shao Jen Weng & Ching Fen Tang, 2022. "Decision support algorithms for optimizing surgery start times considering the performance variation," Health Care Management Science, Springer, vol. 25(2), pages 208-221, June.
    • Handle: RePEc:kap:hcarem:v:25:y:2022:i:2:d:10.1007_s10729-021-09580-2
    DOI: 10.1007/s10729-021-09580-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10729-021-09580-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10729-021-09580-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kyung Sung Jung & Michael Pinedo & Chelliah Sriskandarajah & Vikram Tiwari, 2019. "Scheduling Elective Surgeries with Emergency Patients at Shared Operating Rooms," Production and Operations Management, Production and Operations Management Society, vol. 28(6), pages 1407-1430, June.
    2. 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.
    3. Shing Chih Tsai & Jun Luo & Chi Ching Sung, 2017. "Combined variance reduction techniques in fully sequential selection procedures," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(6), pages 502-527, September.
    4. John Butler & Douglas J. Morrice & Peter W. Mullarkey, 2001. "A Multiple Attribute Utility Theory Approach to Ranking and Selection," Management Science, INFORMS, vol. 47(6), pages 800-816, June.
    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. Tsai, Shing Chih & Chen, Sin Ting, 2017. "A simulation-based multi-objective optimization framework: A case study on inventory management," Omega, Elsevier, vol. 70(C), pages 148-159.
    7. Nickolas K. Freeman & Sharif H. Melouk & John Mittenthal, 2016. "A Scenario-Based Approach for Operating Theater Scheduling Under Uncertainty," Manufacturing & Service Operations Management, INFORMS, vol. 18(2), pages 245-261, May.
    8. 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.
    9. Sakine Batun & Brian T. Denton & Todd R. Huschka & Andrew J. Schaefer, 2011. "Operating Room Pooling and Parallel Surgery Processing Under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 23(2), pages 220-237, May.
    10. Pichitlamken, Juta & Nelson, Barry L. & Hong, L. Jeff, 2006. "A sequential procedure for neighborhood selection-of-the-best in optimization via simulation," European Journal of Operational Research, Elsevier, vol. 173(1), pages 283-298, August.
    11. Shing Chih Tsai, 2013. "Rapid Screening Procedures for Zero-One Optimization via Simulation," INFORMS Journal on Computing, INFORMS, vol. 25(2), pages 317-331, May.
    12. Hejer Khlif Hachicha & Farah Zeghal Mansour, 2018. "Two-MILP models for scheduling elective surgeries within a private healthcare facility," Health Care Management Science, Springer, vol. 21(3), pages 376-392, September.
    13. Barry L. Nelson & Julie Swann & David Goldsman & Wheyming Song, 2001. "Simple Procedures for Selecting the Best Simulated System When the Number of Alternatives is Large," Operations Research, INFORMS, vol. 49(6), pages 950-963, December.
    14. Inês Marques & M. Captivo & Margarida Vaz Pato, 2015. "A bicriteria heuristic for an elective surgery scheduling problem," Health Care Management Science, Springer, vol. 18(3), pages 251-266, September.
    15. Xiangyong Li & N. Rafaliya & M. Fazle Baki & Ben A. Chaouch, 2017. "Scheduling elective surgeries: the tradeoff among bed capacity, waiting patients and operating room utilization using goal programming," Health Care Management Science, Springer, vol. 20(1), pages 33-54, March.
    16. Astaraky, Davood & Patrick, Jonathan, 2015. "A simulation based approximate dynamic programming approach to multi-class, multi-resource surgical scheduling," European Journal of Operational Research, Elsevier, vol. 245(1), pages 309-319.
    17. Sigrún Andradóttir & Seong‐Hee Kim, 2010. "Fully sequential procedures for comparing constrained systems via simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(5), pages 403-421, August.
    18. Khaniyev, Taghi & Kayış, Enis & Güllü, Refik, 2020. "Next-day operating room scheduling with uncertain surgery durations: Exact analysis and heuristics," European Journal of Operational Research, Elsevier, vol. 286(1), pages 49-62.
    19. Demet Batur & Lina Wang & F. Fred Choobineh, 2018. "Methods for System Selection Based on Sequential Mean–Variance Analysis," INFORMS Journal on Computing, INFORMS, vol. 30(4), pages 724-738, November.
    20. Francesca Guerriero & Rosita Guido, 2011. "Operational research in the management of the operating theatre: a survey," Health Care Management Science, Springer, vol. 14(1), pages 89-114, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tsai, Shing Chih & Yeh, Yingchieh & Kuo, Chen Yun, 2021. "Efficient optimization algorithms for surgical scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 293(2), pages 579-593.
    2. Gökalp, E. & Gülpınar, N. & Doan, X.V., 2023. "Dynamic surgery management under uncertainty," European Journal of Operational Research, Elsevier, vol. 309(2), pages 832-844.
    3. 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.
    4. 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.
    5. 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.
    6. Gartner, Daniel & Kolisch, Rainer, 2014. "Scheduling the hospital-wide flow of elective patients," European Journal of Operational Research, Elsevier, vol. 233(3), pages 689-699.
    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. 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.
    9. Anders Reenberg Andersen & Thomas Jacob Riis Stidsen & Line Blander Reinhardt, 2020. "Simulation-Based Rolling Horizon Scheduling for Operating Theatres," SN Operations Research Forum, Springer, vol. 1(2), pages 1-26, June.
    10. Silva, Thiago A.O. & de Souza, Mauricio C., 2020. "Surgical scheduling under uncertainty by approximate dynamic programming," Omega, Elsevier, vol. 95(C).
    11. Asli Ozen & Yariv Marmor & Thomas Rohleder & Hari Balasubramanian & Jeanne Huddleston & Paul Huddleston, 2016. "Optimization and Simulation of Orthopedic Spine Surgery Cases at Mayo Clinic," Manufacturing & Service Operations Management, INFORMS, vol. 18(1), pages 157-175, February.
    12. 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.
    13. Yao Xiao & Reena Yoogalingam, 2021. "Reserved capacity policies for operating room scheduling," Operations Management Research, Springer, vol. 14(1), pages 107-122, June.
    14. 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.
    15. Aida Jebali & Ali Diabat, 2015. "A stochastic model for operating room planning under capacity constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 53(24), pages 7252-7270, December.
    16. repec:ipg:wpaper:2013-014 is not listed on IDEAS
    17. Karsten Schwarz & Michael Römer & Taïeb Mellouli, 2019. "A data-driven hierarchical MILP approach for scheduling clinical pathways: a real-world case study from a German university hospital," Business Research, Springer;German Academic Association for Business Research, vol. 12(2), pages 597-636, December.
    18. Antti Peltokorpi, 2011. "How do strategic decisions and operative practices affect operating room productivity?," Health Care Management Science, Springer, vol. 14(4), pages 370-382, November.
    19. repec:ipg:wpaper:14 is not listed on IDEAS
    20. Zhang, Yu & Wang, Yu & Tang, Jiafu & Lim, Andrew, 2020. "Mitigating overtime risk in tactical surgical scheduling," Omega, Elsevier, vol. 93(C).
    21. Sigrún Andradóttir & Seong‐Hee Kim, 2010. "Fully sequential procedures for comparing constrained systems via simulation," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(5), pages 403-421, August.
    22. Aisha Tayyab & Saif Ullah & Mohammed Fazle Baki, 2023. "An Outer Approximation Method for Scheduling Elective Surgeries with Sequence Dependent Setup Times to Multiple Operating Rooms," Mathematics, MDPI, vol. 11(11), pages 1-15, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:hcarem:v:25:y:2022:i:2:d:10.1007_s10729-021-09580-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.