Redesign of the University of Virginia’s Emergency Department Waiting Room Layout to Optimize Patient Flow and Increase Satisfaction

Increasing demands on emergency departments (EDs) due to rising patient volumes and operational inefficiencies necessitate innovative solutions to enhance patient flow and satisfaction. Data from UVA Health reveals substantial ED crowding, with a 12% increase in ED visits between 2022 and 2023, and a 25% increase from 2021 to 2023. To address these challenges, a simulated redesign of the waiting room at the University of Virginia (UVA) ED was completed to improve space utilization and streamline patient movement. Current designs, characterized by repeated patient returns to the waiting area, create congestion and hinder the perception of progress in care. This redesign aims to expand available space and create “progression areas” where patients can be effectively managed post-triage, reducing returns to the main lobby and thereby minimizing congestion. Utilizing FlexSim HC simulation software, both the current and proposed layouts are modeled to forecast key operational metrics. Validation was conducted by comparing simulation outcomes with UVA Health data on patient wait times, bed utilization, and throughput, ensuring the reliability of the proposed improvements. While the new waiting room is farther from the Patient in Triage (PIT) area, thus increasing patient travel time and the average total triage time by $2 \%$, the variances of the arrival-to-roomed, arrival-to-triage, and triage-to-roomed times decreased by $57 \%, 83 \%$, and $67 \%$ respectively. Additionally, the time taken to bring trauma patients from registration to a trauma bay decreased by $30 \%$. Reducing the variance of wait times will increase patient satisfaction by eliminating the tail of unexpectedly long wait times. Reducing the variance enhances the reliability of wait time estimates, making actual experiences more aligned with expectations. Further research will focus on implementation challenges, including staff adaptation and continuous real-time assessment of operational performance.