Date of Award
5-2023
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Industrial Engineering
Committee Chair/Advisor
Dr. Emily Tucker
Committee Member
Dr. Kevin Taaffe
Committee Member
Dr. Tugce Isik
Abstract
We develop a discrete-event simulation model to study how staffing strain affects patient outcomes across a network of Emergency Departments (EDs). The aim is to observe how clinician staffing and transfers throughout the system affect the system’s behavior. We will study the network of the seven EDs in the Prisma Health-Upstate system. Patient acuity and resource need are stratified using the five-level Emergency Severity Index (ESI). Patient flow data within and between EDs are collected from EPIC, staffing data from ShiftAdmin, and environmental COVID-19 prevalence data from the Department of Health and Environmental Control. Time periods include the Omicron wave and pre-Omicron trough. Analyses are conducted to test the system when there are clinician shortages and increased patient transfers throughout the system, and combinations of the two. Results suggest that when the clinician staffing is reduced there are increases in patients’ length-of-stay. It is also observed that when transfers increase, the average length of stay (LOS) within the network increases. Strain at one of the EDs through clinician shortage may change conditions at other locations in its network because of patient transfers. Further research is suggested to consider a network-effects under endogenous strain.
Recommended Citation
Nelson, Aisha, "Network Effects of Emergency Department Clinician Strain and Patient Congestion" (2023). All Theses. 3989.
https://tigerprints.clemson.edu/all_theses/3989