April 13, 2022

Spotlight: Shan Liu leverages modeling to improve healthcare systems and policies

Dr. Shan Liu’s career captures her sustained dedication to the use of mathematical modeling and analysis for improving healthcare systems and policies on the local and global scales. She continually highlights the importance of utilizing interdisciplinary approaches in her discipline and strives to impart this idea to her students and peers.

“I strongly believe in evidence-based guidance to health policymaking and using some of these more advanced analytical tools that come from engineering,” said Liu. “Industrial engineering in particular is relatively new to healthcare, and I really enjoy collaborating and trying to bring these two disciplines together.”

Liu is an associate professor of industrial and systems engineering at the University of Washington, where her passions for teaching and research intersect daily. She teaches several engineering courses at the undergraduate and graduate level and mentors multiple graduate students in her discipline. Liu’s graduate students are trained in both industrial engineering and areas of healthcare, as they learn how to model different healthcare interventions, such as disease processes, through systems engineering and operations research tools in order to address the issue more holistically.

Currently, one of Liu’s major research projects at the local level involves a collaboration with the UW Department of Surgery to assess trauma center locations and services in Washington state. With funding from a Population Health Initiative pilot research grant, Liu, Dr. Rebecca Maine and the rest of the team are working to understand the interactions between the services provided at various trauma center levels and demographic variables with the goal of using optimization models to improve the state’s trauma care system.

Liu is also working on a project in its early stages at Seattle Children’s Hospital that utilizes simulation and optimization to address pediatric mental health needs. The team plans to design local care systems that optimize community support and minimize the factors that currently cause bottlenecks in the system. They are looking at factors such as waiting times, staffing issues, and other hinderances to patient flow in order to help create an acute care system that provides optimal support for children in their mental health journey.

“Healthcare is one of the biggest challenges for the US. It’s extremely costly and inefficient. A lot of times the outcome is poor,” said Liu. “In this area, I can help by using modeling and quantitative methods to work with clinicians and policymakers to make a difference. It’s a very unique and exciting area.”

Another research project Liu is involved in revolves around understanding the way different combinations of non-pharmaceutical intervention policies (i.e., mask wearing, social distancing) and vaccine rollout policies intersect and affect King County’s COVID-19 hospitalization and death rates. This topical project is constantly evolving with the introduction of new viral variants and transmissibility updates.

“This is a really cool collaboration with the Department of Global Health and faculty from the Dept. of Infectious Diseases who are the experts, so it’s really good for my PhD students to get exposed to public policy, not just to practice simulating something, but to truly understand how these policies work in the real world,” said Liu.

In addition, Liu is involved in multiple projects at the global health level. One of these projects seeks to use optimization methods to determine the best locations for point of care machines that do HIV viral load testing in Kenya. This project focuses specifically on pediatric HIV viral load and drug resistance testing and studies variables including transportation, batch-testing delays and waiting times at processing facilities to help streamline the HIV treatment process in areas that demonstrate the highest demand for this technology.

“I’ve always had a strong interest in the intersection between technology and policy,” said Liu. “I feel like technology can be great but if you don’t do the implementation or process or adoption correctly, it can have a disastrous effect. If the policy isn’t there, it doesn’t matter how good the technology is.”

Working on a global vaccine improvement index, specifically for countries with lower social demographic indices, is another area of Liu’s population health research. By analyzing patterns and demographics in countries with positive vaccine improvement, Liu and the team at the Population Health Initiative hope to develop data visualizations that ultimately contribute to the improvement of vaccine uptake in lower income countries.

Liu’s commitment to contributing her mathematical modeling and engineering expertise to local population and global health issues is consistently illustrated through her many research projects and professional involvements. Her belief in interdisciplinary collaboration and the necessity of adapting mathematically modeling and optimization to real-world issues has largely led to her success in this field and continues to motivate her education and research pursuits.

“I think to be successful, a researcher needs to understand the methodology and quantitative side – there’s the decision analysis portion, the optimization portion, the statistics portion – and you need to have a pretty good understanding of these tools,” explained Liu. “Problems in healthcare are so complex. If you only have one tool, that’s probably not going to be enough to solve your research question.”