Date of Award
6-6-2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Systems Engineering
First Advisor
Daniel Berleant
Abstract
We review the problem of a system-level balanced scheduling scenario. A hospital clinic has a queue for patients needing care. After being seen in clinic, many require follow-up surgery, for which they also wait in a queue. The rate-limiting factor is physician availability for both clinic visits and surgical cases. Much existing work has been done to optimize clinic appointments, as well as to optimize surgical appointments. This novel approach models the entire patient journey at the system level, through both clinic and surgery, to optimize the total patient experience. A discrete-event simulation model of the system is built based on historic patient encounter data and validated. The system model is then optimized to determine the proper allocation of physician resources across the system to minimize total patient wait time using machine learning optimization techniques. The results are then compared to baseline to compare improvements.
Recommended Citation
Forbus, John, "Using Discrete-Event Simulation to Balance Staff Allocation and Patient Flow Between Clinic and Surgery in a Pediatric Hospital Setting" (2024). Theses and Dissertations. 1196.
https://research.ualr.edu/etd/1196
