Utilizing Canadian Health Data at a Population-Level:

Leveraging Big Data to Inform Clinical Practice, Policy, and Research

This presentation will provide a high-level overview of benefits and challenges of working with Canadian Health Data. This presentation will review commonly used data sources within Canada, along with considerations for data analysis and linkage. Using live case examples, this presentation will also highlight the key benefits of a social healthcare system for population-level analytics.

Dr. Fabrice Mowbray is an Assistant Professor and Director of the Data Center within the College of Nursing at Michigan State University. He received his Bachelor’s and Master’s of Science in Nursing (MScN) from the University of Windsor and a PhD in Health Research Methodology from McMaster University, Ontario, Canada. He also completed a doctoral fellowship in predictive analytics at the MacData Institute. Clinically, Fabrice has worked as a registered nurse in the emergency department and intensive care units at the Detroit Medical Center. He is a research methodologist currently working with GRADE to inform the conduct and reporting of prognostic (i.e., predictive) models and clinical decision rules. Fabrice currently lives in Windsor, Ontario, and continues to conduct research and trials in Canadian hospitals, with a primary focus on geriatric models of care in the emergency department and inpatient settings."