Abstract
In this work, we address the elective surgery scheduling problem and the risk of last-minute cancellations. This risk is associated with the likelihood of operating rooms going into overtime and ward beds exceeding their limit. The risk of overtime is constrained by considering only feasible combinations of operating room days schedules. To account for the feasibility, we restrict the number of surgeries assigned to each combination and force it to maintain the correct ratio between in- and out-patients for each operator. Furthermore, the probability of running into overtime is bound and verified using Monte-Carlo simulation. The risk of exceeding the ward limit is solved by a mixed-integer programming model where the probability of going over the available ward beds downstream is bound. The approach is inspired by real challenges and tested on real-life hospital data.
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The authors would like to acknowledge the staff and the managers at Landspitali for giving insights and support to this project.
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Sigurpalsson, A.O., Runarsson, T.P., Saemundsson, R.J. (2020). Stochastic Master Surgical Scheduling Under Ward Uncertainty. In: Bélanger, V., Lahrichi, N., Lanzarone, E., Yalçındağ, S. (eds) Health Care Systems Engineering. ICHCSE 2019. Springer Proceedings in Mathematics & Statistics, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-030-39694-7_13
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DOI: https://doi.org/10.1007/978-3-030-39694-7_13
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