UTEP Helps Optimize COVID-19 Vaccination Clinics in the U.S.
Last Updated on March 25, 2021 at 12:00 AM
Originally published March 25, 2021
By Christina Rodriguez
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 that included Guadalupe Valencia-Skanes, associate vice president for business affairs; Sandy Vasquez, associate vice president for human resources; José Humberto Ablanedo Rosas, Professor in Western Hemisphere Trade Research II and associate professor of operations and supply chain management; and Joshua Holguin, IMSE graduate research assistant. The team observed several of El Paso’s drive-though and walk-in clinics in early 2021 and identified areas that likely created bottlenecks, which produced delays and other issues.
The group 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.”
This project also has allowed UTEP students to use their skills and training to help remedy a real-world problem.
Holguin, the graduate assistant, said he was happy to contribute to the defense against the COVID-19 pandemic by developing simulations and strategies that could help reduce the number of cases throughout the nation and community.
“I have been fortunate to collaborate with the UTEP vaccination optimization process alongside an expert in the healthcare industry, Dr. Madathil,” Holguin said. “The experience has shown me how to communicate professionally, present and build simulations for crisis scenarios.”
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.”