Social, Behavioral, and Environmental Determinants of Health: Successes, Challenges, and Opportunities
Health outcomes are shaped by both individual-level social, behavioral, and environmental determinants of health-such as education, income, and behaviors-and broader contextual factors including neighborhoods, housing, and access to resources. This talk will highlight opportunities and challenges in assessing these health determinants across levels, with a focus on leveraging real-world data such as electronic health records, claims, and geospatial information. Examples will illustrate how linking individual and contextual determinants enhances understanding of outcomes from COVID-19 to chronic disease management. We will also discuss key considerations-data quality, interoperability, and equity-while emphasizing pathways toward actionable insights that advance health equity.
Bio: Jiang Bian specializes in biomedical informatics and health data science, interdisciplinary fields focused on leveraging data, information, and knowledge to drive scientific discovery, problem-solving, and decision-making, all aimed at improving human health. He has a diverse background in data harmonization and integration, AI/machine learning, causal AI, natural language processing, ontology development and evaluation, and software engineering. Bian brings extensive experience in developing real-world data infrastructure, informatics tools, and systems, as well as applying advanced AI and data science methods to analyze and interpret multimodal clinical and biomedical data. Bian serves as Chief Data Scientist at Regenstrief, Chief Data Scientist at IU Health, Associate Dean of Data Science and Vice Chair for Translational Informatics in the Department of Biostatistics and Health Data Science at the IU School of Medicine, Chief Research Information Officer of the IU Melvin and Bren Simon Comprehensive Cancer Center, and Indiana Clinical and Translational Sciences Institute (CTSI) Regenstrief Institute Deputy Director.