Doctoral Dissertations


"The healthcare system in the United States is complex and challenging to understand, and the emergency department (ED) serves as a bridge between outpatient and inpatient care. According to the Centers for Disease Control and Prevention, over 130 million people visited emergency rooms in the United States in 2018. The ED is composed of multiple subunits and components that make it difficult to comprehend fully. In this study, a combination of engineering analysis methods was used to identify and understand the issues in the ED.

The first contribution of this research involved collecting data through job shadowing of human entities at the Phelps Health Emergency Department in Rolla, Missouri. This approach helped identify issues affecting patient flow and wait times. A Model Based Systems Engineering model was developed to represent and understand the structure, activities, and use cases in the ED, which provided a better understanding of the complex system of the ED. For second contribution a small-scale discrete event simulation model was created to analyze resource utilization and average patient total time in the ED. The impact of staffing and other factors on ED performance during different shifts was identified by comparing day and night shift simulations. Finally, a discrete event model was developed based on the data collected from the job shadowing process, and a multi-objective optimization was conducted to minimize patient total wait time and maximize resource utilization. The findings from this study could be used by healthcare stakeholders to improve ED-related decisions"--Abstract, p. iv


Long, Suzanna, 1961-

Committee Member(s)

Corns, Steven
Canfield, Casey I.
Marley, Robert J.
Burton, Casey
Ferreira, Susan


Engineering Management and Systems Engineering

Degree Name

Ph. D. in Systems Engineering


Missouri University of Science and Technology

Publication Date

Spring 2023


xii, 90 pages

Note about bibliography

Includes_bibliographical_references_(page 89)


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Document Type

Dissertation - Open Access

File Type




Thesis Number

T 12249

Electronic OCLC #