211. Optimizing Surgical Trays for Uncertain Surgery Schedules
Contributed abstract in session FC-3: Patient and Resource Scheduling, stream Regular talks.
Friday, 14:00-15:30Room: Room S2
Authors (first author is the speaker)
| 1. | Johanna Leweke
|
| Research and Teaching Area Combinatorial Optimization, RWTH Aachen University | |
| 2. | Hayo Bos
|
| University of Twente | |
| 3. | Christina Büsing
|
| Lehr- und Forschungsgebiet Kombinatorische Optimierung, RWTH Aachen University | |
| 4. | Felix Engelhardt
|
| Research and Teaching Area Combinatorial Optimization, RWTH Aachen University | |
| 5. | Gréanne Leeftink
|
| CHOIR, University of Twente |
Abstract
Ensuring the availability of surgical instruments in hospitals is crucial for successful operations. In this context, grouping reusable instruments into fixed trays is common, as it offers the benefits of better inventory control and lower sterilization costs. Yet, instrument trays can lead to wastage, e.g., through unneeded instruments being assigned to operations. Additionally, once a tray is opened, its instruments must be sterilized, regardless of use. While having a variety of trays available helps reduce sterilization costs by ensuring the best fit for each surgery, it can lead to significant storage expenses. Therefore, optimizing tray configurations and effectively assigning them to the surgery schedule constitutes a relevant and practical problem for many hospitals. In this talk, we start by presenting a mathematical model that considers the three decisions: tray configuration, determining the quantity of each tray type in the inventory, and assignment based on uncertain realizations of the master surgery schedule. In a first stage, we propose greedy heuristics to configure both trays and inventory such that the number of instruments is minimized while restricting the number of trays. For the second stage, an assignment to the surgery schedule is found that minimizes the sterilization costs. Afterwards, a local search algorithm allows for small inventory changes. All algorithms are evaluated in a computational study making use of real-word data from a Dutch hospital.
Keywords
- Clinical modelling
- Integrated planning of health services
- Resource scheduling
Status: accepted
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