Graduation Semester and Year
2022
Language
English
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Industrial Engineering
Department
Industrial and Manufacturing Systems Engineering
First Advisor
Yuan Zhou
Second Advisor
Victoria Chen
Abstract
The purpose of this research is to examine methods for minimizing the influence of boarding on emergency department (ED) crowding outcomes. To accomplish this purpose, this research uses a hybrid systems model framework by combining agent-based simulation, predictive and optimization models to improve ED outcomes such as length-of-stay and left-without-being-seen rates. For the research, different types of simulation models were examined (discrete event and agent-based/discrete event combination) to identify the most parsimonious for studying ED boarding. Predictive models using simulation output were developed to understand the factors that influence future boarding levels as well as generate predictions. Research has previously highlighted how valuable bed assignment/management strategies can be in ensuring minimal length-of-stays in healthcare systems. Such research is limited for EDs specifically, however. This research contributes by directly leveraging the predictions of future boarding levels to develop a bed assignment strategy that can optimize fast track bed capacity to ensure improved ED outcomes.
Keywords
Emergency department, Hybrid systems modeling, Simulation, Boarding, Forecasting, Operations research
Disciplines
Engineering | Operations Research, Systems Engineering and Industrial Engineering
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Suley, Eniola Oluwasola, "A HYBRID SYSTEMS MODEL FOR EMERGENCY DEPARTMENT BOARDING MANAGEMENT" (2022). Industrial, Manufacturing, and Systems Engineering Dissertations. 147.
https://mavmatrix.uta.edu/industrialmanusys_dissertations/147
Comments
Degree granted by The University of Texas at Arlington