Discrete Event Simulation of a Specialty Outpatient Clinic
Authors: Samantha Mangoni
Faculty Mentor: Xiang Zhong
College: Herbert Wertheim College of Engineering
The objective of this study was to test the validity and efficacy of discrete-event simulation (DES) in modeling a specialty outpatient clinic, and to apply the model to predict how the clinic could improve their patient flow. Arena software was used to develop this DES model. Real-life model inputs included the time that patients spent in each clinic process, clinic room utilization rate, and physician room schedules. The DES was validated via a comparison between the model’s outputs and raw clinic data, and further validated by clinic leadership. Once validated, the DES was modified to represent different scenarios, such as changes in clinic scheduling and resource usage. Analysis of the models revealed that adding two volunteers to escort patients in the morning and afternoon would decrease the queue time to see a physician by 33.9% and 65.2% respectively. The model results also suggested that there is currently not enough congestion in the clinic for changing the current dedicated room assignment to un-assigned room scheduling to make a significant difference in any of the clinic queue sizes. The results of the analysis and validation support the usability of DES in modelling and analysis of specialty outpatient clinics and providing decision support.
Click the video below to view the student's poster pitch.
Hello Samantha! Your research is extremely interesting, especially during our current situation. Do you see use for your DES in our state of pandemic, and would you easily be able to simulate the day-to-day fluctuations that we are seeing with an increase number of COVID-19 cases?
Thank you, I appreciate your interest. Good question! I do think that DES could be useful in our current state of pandemic, especially for hospitals that are overwhelmed by patients. DES could assist hospitals/clinics in making decisions about how they could change their processes in response to a high patient arrival rate. We actually did something similar in our study when we looked at whether or not the clinic should change their scheduling to a “random room schedule” when there is an abnormally high patient arrival rate.
Hi Samantha, interesting research!
Do you have any predictions on how accounting for walk-ins would affect the flow of the system? Did you notice any kind of arrival patterns for walk-in patients while collecting data?