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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
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    References listed on IDEAS

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