The Banting Foundation and CANSSI Ontario are pleased to announce Professor Glen McGee as a recipient of a 2021 Banting–CANSSI Ontario Discovery Award.
Glen McGee is an Assistant Professor in the Department of Statistics and Actuarial Science in the Faculty of Mathematics at the University of Waterloo.
Professor McGee completed his PhD in Biostatistics at Harvard University and received a BScH in Mathematics from Queen’s University. His research interests are developing statistical tools to solve problems in epidemiology, environmental health, and health policy.
He received this year’s award for the project: Addressing Informative Presence Bias in Analyses of Electronic Health Records.
McGee intends to develop statistical tools to characterize and correct biases that arise from the analysis of electronic health records of patients with autism spectrum disorder. Research on the relationship between complex diseases, like autism and other potentially related conditions, often relies on electronic health records–a key and rich source of data. However, patients with autism tend to visit doctors more often than others, meaning they have more opportunities to have diagnoses of other conditions in their health records. This disparity causes analyses to be biased and can lead to reporting spurious associations in the medical literature.
Despite being motivated by autism research, McGee’s work may be applied more broadly, as the proposed methods have the potential to improve the way medical research is conducted whenever conditions of interest increase a patient’s contact with the medical system.
About the Banting–CANSSI Ontario Discovery Award in Data Science
In 2019 the Banting Research Foundation and CANSSI Ontario partnered to offer two Banting-CANSSI Ontario Discovery Award in Data Science for new investigators appointed at Ontario universities. These new investigator awards are a one-year grant of up to $25,000 and are intended to support statistical or computational research related to a health or biomedical problem.