You don’t have to be a math whiz to be a good physician. But a mathematician may be able to help a physician make better decisions every day.
For example: Should I transfer a patient from one hospital to another when her illness becomes more severe? Should I triage or immediately treat a patient who just arrived in the ER? Can I adjust my inpatient rounds schedule to better align with the ER’s typical patient flow?
Developing quantitative tools to help answer these kinds of questions is the research focus of Gabriel Zayas-Caban, who joined the University of Wisconsin-Madison as an assistant professor of industrial and systems engineering in August 2017.
With his wife, Amy Cochran—a postdoctoral fellow in biostatistics and medical informatics at UW-Madison—he moved to Madison from Ann Arbor, where both completed postdoctoral fellowships at the University of Michigan after earning PhD degrees in applied mathematics at Cornell University.
“We keep telling our friends that Madison has everything that makes Ann Arbor great, but twice as much,” Zayas-Caban jokes, alluding to Madison’s twice-as-large population. With their shared hobby of biking, it didn’t take the couple long to feel at home in a city known for its lakes, beautiful scenery and dedicated bike trails. And as a lifelong basketball player, Zayas-Caban didn’t mind switching his allegiance from the Big Reds to the Badgers either.
He began to seek out extracurricular math activities as a high school junior in Columbia, Missouri, where his family relocated in 2003 so that his mom could pursue a PhD in accounting. Until then, he and his two older siblings—a musically talented brother and a sister who earned her own PhD in industrial and systems engineering at UW-Madison—had grown up in Mayagüez, Puerto Rico, where his dad worked as an engineer and his mom taught college-level accounting.
After completing his bachelor’s degree in math at the University of South Florida, Zayas-Caban continued with graduate school at Cornell, where his interest in healthcare applications of operations research emerged. He developed an optimization algorithm for allocating emergency medical service vehicles after catastrophic events such as hurricanes, and analyzed the process of triaging or treating patients in emergency departments.
As a postdoctoral fellow at the University of Michigan, he proposed decision guidelines for transferring children with respiratory illnesses to a pediatric intensive care unit that specializes in the most severely ill patients. He also joined a research project on newborn screening—performed on nearly four million babies born annually in the United States—that is spearheaded by Professor Beth Tarini at the University of Iowa.
“We carefully analyzed the process by which blood samples for genetic testing are sent from the birthing hospital to the state’s public health laboratory, which runs tests for more than 50 single-gene defects and then mails results to the family’s pediatrician,” Zayas-Caban explains. “Next, we plan to develop a smartphone app that will make the process faster and more efficient.”
Some of the motivation for this project came from a 2013 investigative report about newborn screening by the Milwaukee Journal Sentinel.
All 50 states perform the screen, but the details of the tests vary between states. The Journal Sentinel reporters found that the consequences of delayed or misleading test results—though rare—may be grave enough to prompt lawsuits against pediatricians, since a rapid diagnosis of single-gene metabolic disorders can make the difference between a baby growing up healthy or suffering permanent damage to her brain or other organs.
The scheduling process for newborn screening is an example of what mathematicians call a queueing system—and for Zayas-Caban, a powerful illustration of the potential for systems engineers to help reduce adverse health outcomes. This makes him a great fit for UW-Madison’s recently established Wisconsin Institute for Healthcare Systems Engineering, which is directed by his colleague Pascale Carayon, the Procter & Gamble Bascom Professor in Total Quality in industrial and systems engineering.
“I think modeling people’s average behavior in a queueing system and combining it with each patient’s unique clinical data can improve patient flow and other types of medical decisions,” Zayas-Caban says. “At UW-Madison, I look forward to many new opportunities to collaborate with engineers and physicians on designing better healthcare systems.”
Author: Silke Schmidt