Transforming Health Systems Through Causal Inference: A Conversation with Dr. Miguel Hernán

In this episode of "Gateway to Informatics," Dr. Philip Payne, the WashU medicine chief data scientist and director of I2DB, engages in a thought-provoking conversation with Dr. Miguel Hernán, a leading expert in causal inference from the Harvard T.H. Chan School of Public Health. Dr. Hernán shares insights into his career journey, which began unexpectedly in medical school and evolved through work in biostatistics and epidemiology. He emphasizes the significant impact of mentors, particularly highlighting the influence of Jamie Robbins, who taught him the importance of asking the right questions and connecting theory to practice.The discussion delves into the concept of causal inference, explaining its critical role in both clinical decision-making and policymaking. Dr. Hernán underscores the need for precise questions and robust methods to derive meaningful insights from health system data, which can lead to better clinical outcomes and informed policies. They also explore the future implications of integrating advanced data analysis methods, non-structured data, and collaboration across disciplines. The episode concludes with advice for aspiring students and the potential for transformative impacts in health data science, emphasizing the ongoing evolution and interdisciplinary nature of the field.Gateway to Informaticsi2db.washu.edu/gatewaytoinformaticsProduced by the Institute for Informatics, Data Science & Biostatistics (I2DB), WashU Medicine.Follow us on LinkedIn, X (formerly Twitter), and Bluesky.Have feedback or questions? Contact us!