Gemma Postill is an MD/PhD student at the University of Toronto, and a Visiting Doctoral Researcher at the #PopHealthLab. Her research focuses on the epidemiology of chronic disease and multimorbidity, with a strong interest in applying advanced analytical and machine learning methods to population health data. Her work aims to understand the patterns and impacts of multiple chronic conditions across the life course and to identify opportunities for data-informed, patient-centred care and prevention strategies. 

Gemma’s research has included the development and evaluation of predictive models for premature mortality among people with inflammatory bowel disease (IBD), leveraging large administrative health datasets and machine learning approaches to assess how chronic conditions and their age of onset influence health trajectories. She has co-led population-based studies that highlight the importance of multidisciplinary care and integrated prevention approaches for individuals with complex multimorbidity. This work has been published in leading peer-reviewed journals and has contributed to advances in understanding multimorbidity patterns and health system implications. 

Gemma’s research at the #PopHealthLab applies machine learning and causal inference techniques to characterize trajectories of multimorbidity in older adults. The findings will support more nuanced risk stratification of older adults, inform early intervention strategies, and guide health policy in managing aging populations with complex chronic disease profiles.