Philip Payne

USA

Washington University in St. Louis

Director Institute for Informatics

Interoperabilidad y Experiencia en USA

Precision Medicine and Healthcare Transformation: A Tale of Two Populations

With increasing attention being placed upon the need to transform our healthcare delivery system into a data-driven enterprise the emphasizes individual and population health, there is an equally increasing recognition that achieving comprehensive health data interoperability is of critical importance. Such data interoperability has the potential to lead to dramatic improvements in: 1) the conduct of collaborative and open research programs that can inform advances in foundational basic and clinical science knowledge; 2) our ability to identify and apply computable bio-molecular and clinical phenotypes and facilitate precision medicine paradigms; and 3) the delivery of contextual information at patient and population levels that is both timely and actionable and that leads to improved outcomes and safety at a lower cost. When these benefits are assessed collectively, it becomes increasingly clear that data interoperability represents a foundational basis for the realization of a personalized and value-base health and healthcare system, with all of the benefits therein. In this talk, we will explore a number of important questions that contribute to our ability to achieve such a vision, namely: 1) how can we deliver data interoperability “at scale” in increasing complex and geographically or temporally distributed settings; 2) how can ensuing collections of multi-scale data be integrated and reasoned upon in an efficient manner; and 3) in what ways will such data “liquidity” impact the ways in which health and healthcare research and innovation are pursued.

09:15-09:50

Información del expositor

Dr. Payne is the founding Director of the Institute for Informatics (I2) at Washington University in St. Louis, where he also serves as a Professor in the Division of General Medical Sciences. Previously, Dr. Payne was Professor and Chair of the Department of Biomedical Informatics at The Ohio State University. Dr. Payne is an internationally recognized leader in the field of clinical research informatics (CRI) and translational bioinformatics (TBI). His research portfolio is actively supported by a combination of NCATS, NLM, and NCI grants and contracts, as well a variety of awards from both non-profit and philanthropic organizations. Dr. Payne received his Ph.D. with distinction in Biomedical Informatics from Columbia University, where his research focused on the use of knowledge engineering and human-computer interaction design principles in order to improve the efficiency of multi-site clinical and translational research programs. Prior to pursuing his graduate training, Dr. Payne served in a number of technical and leadership roles at both the UCSD Shiley Eye Center and UCSD Moores Cancer Center. Dr. Payne’s leadership in clinical research informatics community has been recognized through his appointment to numerous national steering, scientific, editorial, and advisory committees, including efforts associated with the American Medical Informatics Association (AMIA), AcademyHealth, the Association for Computing Machinery (ACM), the National Cancer Institute (NCI), the National Library of Medicine (NLM), and the CTSA consortium, as well as his engagement as a consultant to academic health centers throughout the United States and the Institute of Medicine. Dr. Payne is the author of over 190 publications focusing on the intersection of biomedical informatics and the clinical and translational science domains, including several seminal reports that have served to define a new sub-domain of biomedical informatics theory and practice specifically focusing upon clinical research applications. His current research interests include:
• Knowledge-based approaches to the discovery and analysis of bio-molecular and clinical phenotypes and the ensuing identification of precision diagnostic and therapeutic strategies in cancer;
• Interventional approaches to the use of electronic health records in order to address modifiable risk factors for disease and enable patient-centered decision making;
• The study of human factors and workflow issues surrounding the optimal use of healthcare information technology; and,
• The design and evaluation of open-science platforms that enable collaborative and cumulative approaches to biomedical data analytics.