image: Pictured is the UT Arlington team that will use data in an NSF research project that could help physicians make more informed decisions about treating pain. Pictured from left in the front row are: Aera LeBoulluec, Victoria Chen and Li Zeng. Pictured in the back row, from left, are: Robert Gatchel, Jay Rosenberger, Mike Manry and Junzhou Huang. view more
Credit: UT Arlington
A UT Arlington multi-disciplinary team is optimizing and integrating volumes of data in a National Science Foundation research project to help physicians make better, more informed decisions about treating patients' pain.
Jay Rosenberger, an associate professor in the Industrial, Manufacturing and Systems Engineering Department, is leading the team, which will work for three years on the $374,998 NSF grant titled: "Statistics-based Optimization Methods for Adaptive Interdisciplinary Pain Management."
The team includes Distinguished Professor Robert Gatchel of Psychology, Professor Mike Manry of Electrical Engineering, Assistant Professor Junzhou Huang of Computer Science & Engineering, and Rosenberger's IMSE colleagues Professor Victoria Chen and Assistant Professor Li Zeng.
Gatchel is a renowned researcher in pain management who holds the Nancy P. and John G. Penson Endowed Professorship of Clinical Health Psychology. He is a clinical professor at the Eugene McDermott Center for Pain Management at UT Southwestern Medical Center, and he is director of the Center of Excellence for the Study of Health and Chronic Illnesses.
Data from the Eugene McDermott Center is being used for this project.
Chronic pain is a problem that affects nearly 40 percent of the U.S. population at an estimated annual cost of $560 billion to $635 billion, according to the American Academy of Pain Medicine. Costs include everything from lost productivity to treatment and rehabilitation.
"We wanted to create a system that coordinates and optimizes all the available information including the pain data," Rosenberger said. "But we wanted to take other variables like daily living activities or whether a patient is married or single and roll those into treatment possibilities."
Rosenberger said there are so many variables that enter into pain management. He said data such as drugs used for pain in the past, severity of pain and mobility would all be factors used in this analytics project.
Rosenberger, who also is director of UT Arlington's Center on Stochastic Modeling, Optimization & Statistics or COSMOS, said the system is meant only to help physicians, not replace them.
"The initial work started with two PhD students: Chingfeng Lin and Aera Kim LeBoulluec. That work shows a strong potential for this kind of information to help patients," said Rosenberger. He said the project will draw upon new data from patients at the Eugene McDermott Center for Pain Management at UT Southwestern.
One part of the research will explore the bias in assessing treatments on patient outcomes. Patient outcomes are affected by their previous treatments, which in turn affect subsequent treatments. Such mutual interactions cause bias in assessing real treatment effects.
Rosenberger said Zeng and Chen will create a new method for removing the bias, so that doctors understand the true effects of treatments.
Khosrow Behbehani, dean of the College of Engineering, said the project embodies a true interdisciplinary team approach.
"It is truly exciting to see a collaboration of engineers with life scientists and medical professionals that can provide new enabling means to help with the important topic of pain management," Behbehani said. "Undoubtedly, patients with chronic pain will ultimately benefit from the results of this highly collaborative research."
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About UT Arlington
The University of Texas at Arlington is a comprehensive research institution and the second largest institution in The University of Texas System. The Chronicle of Higher Education ranked UT Arlington as the seventh fastest-growing public research university in 2013. U.S. News & World Report ranks UT Arlington fifth in the nation for undergraduate diversity. Visit http://www.uta.edu to learn more. Follow #UTAdna on Twitter.