EURO 2024 Copenhagen
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3581. Emergency surgery allocation: Simulation-optimization approach incorporating scheduled elective surgeries under a hybrid emergency strategy

Invited abstract in session WC-10: Capacity and treatment planning in healthcare, stream OR in Health Services (ORAHS).

Wednesday, 12:30-14:00
Room: 11 (building: 116)

Authors (first author is the speaker)

1. Chao Pan
Department of Decision Sciences and Information Management, KU Leuven
2. Erik Demeulemeester
KBI, KU Leuven

Abstract

A sudden surge in emergency surgeries strains the critical and limited resources of the operating room (OR). Relying solely on human judgment for emergency surgery decisions may worsen congestion, leading to potential delays or cancellations of both emergency and elective surgeries. In the worst case, if the initially allocated hospital lacks capacity, the patient may face a second transfer, causing additional treatment delays. To address these risks, we develop a stochastic mixed-integer programming model for emergency patient allocation with a hybrid emergency surgery strategy. We then design a simulation-optimization approach to assess the expected maximum capacity for accommodating emergency surgeries. Our approach expedites decision-making in urgent cases, allowing decision-makers to make more rational choices swiftly. Specifically, we propose an improved sample average approximation method with a stopping rule for single-hospital cases, integrating it into the optimal computing budget allocation algorithm for multi-hospital settings. To demonstrate the efficiency of the proposed algorithms, we conduct experiments with real data from a 3A hospital in China. Our results illustrate the robustness of our methods through a sensitivity analysis of internal factors (overtime length), external factors (release time of emergency patients), and expected elective surgery durations. Additionally, we highlight the benefits of collaborative decision-making in multi-hospital setting.

Keywords

Status: accepted

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