A data-driven approach to include availability of ICU beds in the planning of the operating room

Augustin A, Jouvet P, Lahrichi N, Lodi A and Rousseau Lm

Omega, 2022, vol. 109, issue C

Abstract: In this paper, we propose a novel approach to deal with the integration of the cancellation probability due to congestion in the intensive care unit in the (long term) surgical case assignment problem. This problem consists of selecting patients from the wait list to be on the operating list of surgeons for a selected horizon, and assigning a day, an operating room, and a time block to each surgeon. We propose an approach that computes the probability of canceling cases on each day through the graph of possible states and actions derived from the schedule in the OR. This graph is then integrated into a Mixed Integer Programming model to optimize the monthly case assignment schedule. We evaluated the method on the practical case of the teaching hospital Sainte-Justine (CHUSJ) in Montreal and performed and extensive sensitivity analysis on the parameters. We show that prioritizing patients during this process only increases the quality of the schedule without decreasing the occupancy rate of the operating room. We also use probabilities that need to be discussed with senior management to decide on the acceptable risk to cancel an elective case.

Keywords: Operating room scheduling; ICU; Data-driven approach (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.omega.2022.102608

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