Personalized healthcare – matching patients with treatments in order to improve outcomes – is the focus of a growing body of research conducted by Dr. Guihua Wang, assistant professor of operations management in the Naveen Jindal School of Management.

Wang’s studies often use empirical econometrics — which uses data to analyze causal relationships — and machine learning, which automates analytical model building, with a focus on personalized healthcare. In other words, he combines classical empirical methods and state-of-art machine-learning techniques to study the many possible effects of treatments, which can be delivered in medical interventions, through health policy or by healthcare providers.

“More specifically,” Wang said, “I developed new causal machine-learning techniques … and applied them to the analysis of observational healthcare data.”

The data come from various public sources, including the Centers for Disease Control and Prevention, The New York Times and other organizations that provide access to research. He also collaborates with medical practitioners.

Tailoring Treatment

Personalized healthcare has the potential to improve the way patients are treated by allowing doctors to identify different types of patients with a given condition in order to tailor treatment to the underlying cause of the disease, Wang says.

He and his former PhD advisors, Dr. Wallace J. Hopp and Dr. Jun Li (no relation to JSOM faculty member Jun Li) of the University of Michigan, first studied that phenomenon in “Big Data and the Precision Medicine Revolution,” which appeared in the September 2018 (Vol. 27, Issue 9, pages 1647-1664) special big data issue of Production and Operations Management.

The trio’s research in “Using Patient-Specific Quality Information to Unlock Hidden Healthcare Capabilities,” was published in the Summer 2019 (Vol. 21, Issue 3, pages 582-601) issue of Manufacturing & Service Operations Management. That study analyzed the potential value of personalized healthcare information in guiding patients to the right care providers.

More recent research by the trio in “An Instrumental Variable Forest Approach for Detecting Heterogeneous Treatment Effects in Observational Studies,” was published online in Management Science in September. That study addresses “the ubiquitous challenge of using big observational data” to identify different treatment effects.

The treatment of patients with COVID-19 is one area Wang has considered in his research. When it comes to treating the virus with all of its variants, one-size-fits-all medical treatment has not always produced the best results. People affected by the virus also have variants, in their genetic makeup, environment, medical history and in other ways. Identifying the reasons that some people who get COVID-19 become seriously ill or die and others have few symptoms could lead to more effective treatments, Wang says.

Personalized treatment also can apply to the use of COVID-19 vaccines. With three different brand names of vaccines available currently in the United States, Wang says personalized healthcare could provide opportunities for giving individuals the vaccine that has been identified as their best match and likely to produce the best outcomes.

Grounded in Engineering and Supply Chain Management

Wang joined the Jindal School in 2019. He earned a PhD in business administration from the University of Michigan that same year, a master’s degree in industrial engineering from the Georgia Institute of Technology, and a master’s degree in supply chain management as well a bachelor’s degree in biomedical engineering from the National University of Singapore.

His work has been published in top management journals. In July, a study, with co-authors Dr. Ronghuo Zheng of UT Austin and Dr. Tinglong Dai of Johns Hopkins University, into the effect of new airline routes on the sharing of donated kidneys appeared online in Management Science and was featured in a UT Dallas News Center article.

The work suggested that introducing new air routes could reduce the time needed to transport an organ, thus reducing the number of kidneys that are discarded. Since proximity of the recipient is used in determining where the organ goes, adding more direct, faster air routes could result in an increase in the number of kidneys sent to transplant centers across the United States.

Wang’s research into the effect of Medicaid expansion on wait times in hospital emergency departments recently was accepted by Management Science. His research into the effect of stay-at-home orders on residents’ mobility using mobile device data was accepted by Manufacturing & Service Operations Management.

He is a member of the Institute for Operations Research and the Management Sciences, the Manufacturing and Service Operations Management Society and the Production and Operations Management Society.