This event is part of the DCI Network Webinars on COVID-19 Data Platforms and Telemedicine event series.
Christopher G. Chute, M.D., Dr.P.H., M.P.H.
Bloomberg Distinguished Professor of Health Informatics
Professor of Medicine The Johns Hopkins Hospital
The emergence of EHR data at scale affords the opportunity to leverage vast amounts of real-world data in observational clinical outcomes research. The paradigm of observational research introduces limitations in data completeness, and requirements for data integration and harmonization. This talk will address the basic issue of harmonization pipelines for integrating data across multiple clinical organizations, using the National COVID Cohort Collaborative (N3C) as a demonstration use case.
Dr. Chute received his undergraduate and medical training at Brown University, internal medicine residency at Dartmouth, and doctoral training in Epidemiology and Biostatistics at Harvard. He is Board Certified in Internal Medicine and Clinical Informatics, and an elected Fellow of the American College of Physicians, the American College of Epidemiology, HL7, the American Medical Informatics Association, and the American College of Medical Informatics (ACMI), as well as a Founding Fellow of the International Academy of Health Sciences Informatics; he was president of ACMI through 2018. His 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. He has had a deep interest in semantic consistency, harmonized information models, and ontology. His current research focuses on translating basic science information to clinical practice, and how we classify dysfunctional phenotypes (disease). He is presently PI on a spectrum of high-profile informatics grants from NIH spanning translational science, and co-lead of the National COVID Cohort Collaborative (N3C). He holds leadership roles on many HIT standards efforts and chaired ISO Technical Committee 215 on Health Informatics and the World Health Organization (WHO) International Classification of Disease Revision (ICD-11).