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Home NEWS Science News

UTEP helps optimize COVID-19 vaccination clinics in the U.S.

Bioengineer by Bioengineer
March 26, 2021
in Science News
Reading Time: 3 mins read
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Credit: J.R. Hernandez / UTEP Communications

EL PASO, Texas – Sreenath Chalil Madathil, Ph.D., assistant professor in industrial manufacturing and systems engineering (IMSE) at The University of Texas at El Paso, is working to streamline the process and ease the patient experience at COVID-19 vaccination clinics in the United States to ensure faster vaccine distribution.

Madathil led a team of UTEP faculty, staff and students who observed several of El Paso’s drive-though and walk-in clinics in early 2021. The team identified areas that likely created bottlenecks, which produce delays and other issues. They used the information from their observations to develop simulation models to experiment with a clinic’s performance to further identify potential slowdowns, calculate resource utilization and reduce patient waiting time.

“We are truly pleased to have Dr. Madathil’s expertise informing COVID-19 vaccination clinic design and implementation,” said Patricia Nava, Ph.D., interim dean of UTEP’s College of Engineering. “It’s great that his team is so diverse in specialties and includes a student. Moreover, it is exciting to have a project that is so clearly impactful for our community. Learning about this project’s existence will help demonstrate to potential students that engineering really is about using your creativity to harness science, math, and technology to make things better for humans and their environment.”

Using simulation models, UTEP researchers can track various performance measures such as wait time, number of people in the queue and resource utilization.

“This quantitative scientific methodology will help university and community leaders efficiently plan for resources,” Madathil said. “Our experts from IMSE, the College of Business Administration, the College of Health Sciences, the School of Nursing, and UTEP administration collaborated to develop these models. Moreover, the administration can test various ‘What-if’ scenarios if they need to test for potential increased capacity or working time. These models help stakeholders plan and design their vaccination event so that its implementation is carried out seamlessly. Developing such a decision support system is one small example of how we help our community.”

Madathil fervently believes in the need to streamline health systems to reduce patient wait times and improve the overall patient experience. He is helping a few hospital systems in El Paso and Washington, D.C., to implement drive-through vaccination clinics. He anticipates the need for similar projects to continue to grow.

“We identified simple bottlenecks that, if not adequately addressed, will result in over mile-long traffic blocks and long waiting times. It is a huge inconvenience and unfair to the current priority population who receive the vaccines to have to wait for over two hours in a car,” Madathil said. “We cannot afford to not learn from the mistakes of vaccine distribution to our senior people and improve the process. We must do it correctly the first time. We hope that this simple model helps improve patient experience and speedy recovery of our COVID-19 infected world.”

###

UTEP is one of the largest and most successful Hispanic-serving institutions in the country, with a student body that is 83% Hispanic. It enrolls nearly 25,000 students in 166 bachelor’s, master’s and doctoral programs in 10 colleges and schools. With more than $100 million in total annual research expenditures, UTEP is ranked in the top 5% of research institutions nationally and fifth in Texas for federal research expenditures at public universities.

Media Contact
Victor H. Arreola
[email protected]

Original Source

http://www.utep.edu/newsfeed/campus/utep-helps-optimize-covid-19-vaccination-clinics-in-the-us.html?HomeBanner

Tags: Health Care Systems/ServicesInfectious/Emerging DiseasesManagement Science/Operations ResearchPublic HealthTechnology/Engineering/Computer ScienceTransportation/Travel
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