Date of Award


Document Type


Degree Name

Master of Science (MS)


Industrial Engineering

Committee Chair/Advisor

Kevin Taaffe

Committee Member

Ronald Pirrallo, MD

Committee Member

Emily Tucker, PhD


The problems associated with Emergency Department (ED) crowding are numerous, varied, and complex. Though overcrowded Emergency Departments are frequently attributed to overcrowded hospitals, crowding is also impacted by bottlenecks in patient flow. While discrete-event simulation (DES) is commonly used to model ED flow, external resources are typically excluded from these models due to their complexity and the limited amount of known information for these processes. Instead, external resources such as consults, labs, and imaging are modeled using estimation and/or educated guesswork. In this study, the impact of imaging on patient flow was assessed through data analysis of specific imaging factors, such as image type, priority, and the number of image orders. This information was used to incorporate the imaging process into the DES model of the study hospital. Sensitivity analysis was then conducted to determine the impact of changes to the imaging process on average patient care time. The results of the sensitivity analysis showed that reducing the number of image orders for a patient has a more substantial impact on patient care time than shifting the ESI level split or image priority classifications. Further, it was determined that process changes aimed at ESI 3 have the most substantial impact on patient care time. In addition to developing a more accurate simulation model of the ED, this research illuminates the potential for changes in the imaging process to impact ED performance and patient care. The insight gained from this study can be used as the basis for changes in standard practice at the study hospital, such as placing a stronger focus on reducing the number of image orders for each patient.



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