Dr. Sherry Yun Wang is an Assistant Professor at Chapman University School of Pharmacy (CUSP). She began her academic journey with a foundation in Geospatial Science from Washington University in St. Louis, an exploration of Data Science at Monash University, and completed comprehensive Ph.D. training in Health Economics and Outcomes Research (HEOR).
Since joining Chapman in May 2021, Dr. Wang has established and led the “Patient Safety Lab,” a research initiative driven by her profound interests in health services research and pharmacoepidemiology, with a special focus on substance use and chronic disease management. She is particularly passionate about exploring the ethical implications of AI and machine learning in healthcare, dedicating her efforts to developing responsible AI solutions that promote equitable and fair access to healthcare resources, especially for individuals struggling with addiction.
Dr. Wang’s current research focuses on investigating algorithmic bias within clinical decision support (CDS) tools, including ML-powered CDS tools for opioid prescribing. Her notable presentations include “Examining Bias in the NarxCare Score: Unveiling Disparities in AI/ML Features for Opioid Prescribing Decisions” at ISPOR 2024 and the recent publication “Predicting Suicidal and Self-Injurious Events in a Correctional Setting Using AI Algorithms on Unstructured Medical Notes and Structured Data” reflects her ongoing efforts to address critical issues and promote fairness and transparency in healthcare AI.
Her contributions are evident through peer-reviewed publications in esteemed journals such as JAMA, Lancet, Clinical Infectious Disease, International Journal of Cardiology, Pharmacogenomics Journal, Drug and Alcohol Dependence, Pain Reports, and Neuroepidemiology. Dr. Wang’s research findings have garnered attention in ISPOR News Across Asia, Physician Weekly, and the COVID newsletter by the Washington State Department of Health. She received the American Association of Colleges of Pharmacy (AACP) New Investigator Award in 2022 and is an awardee of the McGovern Foundation’s McGovern Training Program in Trusted AI.
