A stochastic model for operating room planning under capacity constraints

The present paper describes a two-stage stochastic programme for operating room planning that takes into account capacity constraints of three hospital resources: operating rooms, beds in the intensive care unit (ICU) and beds in the ward (or medium care unit). Operating room planning consists of deciding on the elective surgeries to perform over each period of the planning horizon, while considering uncertainties related to surgery duration as well as patient length of stay in the ICU and the ward. Sample average approximation is then used to solve the planning problem, aiming to minimise the sum of patient-related costs and expected resource utilisation costs. Computational experiments are conducted to evaluate the performance of the proposed solution method. The obtained results highlight the robustness of operating room plans obtained by a stochastic approach, in comparison to those generated by a deterministic approach, and the importance of considering both ICU and ward beds in operating room planning.