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The Real Time Management of Operating Rooms

In: Operations Research Applications in Health Care Management

Author

Listed:
  • Davide Duma

    (Università degli Studi di Torino)

  • Roberto Aringhieri

    (Università degli Studi di Torino)

Abstract

At the operational decision level, the problem arising in the Operating Room (OR) planning is also called “surgery process scheduling”, which usually consists in selecting elective patients from a waiting list and assigning them to a specific operating room on a specific day, and determining the sequence of surgical procedures and the allocation of resources for each OR session. The Real Time Management (RTM) of operating rooms is the decision problem arising during the fulfillment of the surgery process scheduling, that is the problem of supervising the execution of such a schedule and, in case of delays, to take the more rational decision regarding the surgery cancellation or the overtime assignment. The RTM is characterized by the uncertainty of its main parameters, that is, for instance, the duration of a surgery and the arrivals of non-elective patients. In this chapter we propose online optimization approaches for the RTM capable to deal with (1) the elective and non-elective patient flows within a single surgical pathway (Non-Elective Worst Fit algorithm), and with (2) the resource sharing among different surgical pathways of elective patients (Flexible Overtime Allocation and Flexible Scheduling policies). We assess the effectiveness of the proposed solutions on simulated surgical clinical pathways under several scenarios. From a methodological point of view, our analysis suggested that online optimization can be a suitable methodology to deal with the inherent stochastic aspects arising in the majority of the health care problems.

Suggested Citation

  • Davide Duma & Roberto Aringhieri, 2018. "The Real Time Management of Operating Rooms," International Series in Operations Research & Management Science, in: Cengiz Kahraman & Y. Ilker Topcu (ed.), Operations Research Applications in Health Care Management, chapter 0, pages 55-79, Springer.
  • Handle: RePEc:spr:isochp:978-3-319-65455-3_3
    DOI: 10.1007/978-3-319-65455-3_3
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    Citations

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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. 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.
    3. Duma, Davide & Aringhieri, Roberto, 2019. "The management of non-elective patients: shared vs. dedicated policies," Omega, Elsevier, vol. 83(C), pages 199-212.
    4. 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.
    5. Belinda Spratt & Erhan Kozan, 2021. "A real-time reactive framework for the surgical case sequencing problem," Flexible Services and Manufacturing Journal, Springer, vol. 33(1), pages 183-211, March.
    6. 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.

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