Meet Dr. Christopher G. Chute, whose role as Director of the Data Integration and Quality Core at JH AITC places him at the forefront of aging research and technology. In his day job, Dr. Chute serves as Bloomberg Distinguished Professor of Health Informatics; Professor of Medicine, Public Health, and Nursing; and the Chief Research Information Officer at Johns Hopkins Medicine. His work focuses on the representation of clinical information for analyses, decision support, and translational research, emphasizing semantic consistency and harmonized information models. Dr. Chute has led a wide array of research projects as Principal Investigator, as well as played a pivotal role in health information technology standards, including chairing the World Health Organization International Classification of Diseases 11th Revision. His contributions to the field are recognized through his election as a fellow in multiple prestigious medical and informatics associations. Follow along as we delve into a conversation about leveraging real-world data, challenges in AI and aging research, and Dr. Chute's insights into the future of health informatics and technology.
#1 - Can you share with us a little about your work or research?
My career has focused on how we can represent clinical information to support analyses and inferencing, including comparative effectiveness analyses, decision support, best evidence discovery, and translational research. I have had a deep interest in semantic consistency, harmonized information models, and ontology. My current research focuses on leveraging real-world data to improve clinical practice, and how we classify dysfunctional phenotypes (disease). I have been Principal Investigator on a large portfolio of research, have been active on many health information technology standards efforts, and chaired the World Health Organization International Classification of Diseases 11th Revision.
#2 - What initially drew you to this intersection of AI, AgeTech, aging, and dementia? Is there a personal story or motivation behind your commitment to this field?
The magnitude of the challenge globally makes this an important issue to address.
#3 - In your view, where is the biggest gap in the current landscape of aging and dementia research and care, and how can AI and emerging technologies help bridge this?
AI research ultimately requires comparable and consistent data, which remains a challenge in this field.
#4 - Any words of wisdom for budding startups or researchers eager to dive into the AI and AgeTech space?
To the extent that investigators can align with data standards, health data in particular, the greater the impact of their efforts and contributions can be through cross-study analytics.
#5 - What's the most constructive piece of criticism or feedback you've received in your career, and how did it shape your research or business trajectory?
Try not to overlook unexpected opportunities.