ORAHS2024
Abstract Submission

171. Operating room scheduling with consideration of the Post-Anesthesia Care Unit: a simulation study

Contributed abstract in session TA-5: Operating Room Scheduling /1, stream Regular talks.

Tuesday, 9:00-10:30
Room: Room S6

Authors (first author is the speaker)

1. Gabriela Pinto Espinosa
SKEMA Centre for Analytics and Management Science, KU Leven FEB Research Centre for Operations Management, SKEMA Business School, KU Leuven
2. Aida Jebali
SKEMA Centre for Analytics and Management Science, SKEMA Business School
3. Erik Demeulemeester
KBI, KU Leuven

Abstract

Operating Rooms (ORs) play a crucial role in revenue and cost generation within healthcare institutions. They are the bottleneck resource of surgical patients’ care and highly impact the activity of other departments. Consequently, OR Planning and Scheduling is a vastly studied field due to its complexity, stemming from the uncertainty of the OR environment and of the multiple resources it involves. Building on Schoenfelder et al. (2021), we propose a simulation study to test and compare different scheduling heuristics and management policies for the Daily Scheduling problem. Our objective is, first, to evaluate heuristics proposed by Schoenfelder et al. (2021), Wang et al. (2022) and Jung et al. (2019), but with a key contribution of integrating the Post-Anesthesia Care Unit (PACU) in OR scheduling and simulation. Specifically, we consider PACU bed availability and OR blocking, with uncertain surgery and anesthesia recovery durations, as well as elective and non-elective patients with uncertain arrivals. Then, we introduce novel heuristics, considering the PACU in the decision making, for the sequencing of surgeries in the OR, assignment of patients to PACU beds and online policies after the realization of uncertainty on the arrival of non-elective patients and surgery and recovery durations. We analyze the performance of the proposed solutions by studying KPIs related to cost, work-life quality of the hospital staff and patient satisfaction.

Keywords

Status: accepted


Back to the list of papers