ORAHS2024
Abstract Submission

189. A metaheuristic approach for surgical case assignment and admission planning problem considering perioperative pathways

Contributed abstract in session FC-3: Patient and Resource Scheduling, stream Regular talks.

Friday, 14:00-15:30
Room: Room S2

Authors (first author is the speaker)

1. Andrea Eusebi
DEI, University of Bologna
2. Cristiano Fabbri
DEI, University of Bologna
3. Marco Leonessi
IRCCS Azienda Ospedaliero Universitaria di Bologna
4. Enrico Malaguti
DEI, University of Bologna
5. Paolo Tubertini
IRCCS Azienda Ospedaliero Universitaria di Bologna
6. Luca Zattoni
DEI, University of Bologna

Abstract

Modern healthcare systems face significant operational strain, particularly in managing surgical waiting lists. Employing quantitative methods is crucial for delivering effective and efficient care services, allowing for optimal utilization of the resources.
We present a linear programming model for scheduling surgical patients, while considering the availability of operating rooms and beds across different specialty wards, and the intensity settings throughout their hospital stay. The schedule considers the anticipated perioperative path of each patient, and clinical details such as diagnosis and proposed surgical procedure.
After observing that general-purpose solvers struggle in managing large instances of the proposed model, we introduce a metaheuristic algorithm to produce good solutions in short time. While considering clinical and organizational constraints, this algorithm not only manages the scheduling of patients, but also aids in making decisions on the allocation of the operating theatre time slots among different surgical disciplines.
In addition, by considering existing patients on the waiting list as well as projections of future admissions based on historical data, the algorithm can support the hospital management in tactical and operational decisions. We present results at both levels, obtained by applying the described approach in a large academic hospital including 11 surgical departments and over 40 operating rooms.

Keywords

Status: accepted

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