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Presenter: Jonathan Chen, MD, PhD
Instructor, General Medical Disciplines and Research Fellow, PCOR
Stanford University
Jonathan Chen is an instructor in the Stanford Department of Medicine. His research interests focus on data-mining electronic medical records for insights to inform medical decision making. He completed his VA Research Fellowship in Medical Informatics in 2015 and completed clinical training withing Stanford Internal Medicine residency program in 2014.
Chen’s broader interests are to apply similar concepts towards advanced clinical decision support systems to support precision medicine in the “big data” era of electronic medical records. He is currently focused on automated data-mining for clinical decision support, analogous to Netflix or Amazon’s “Customer’s who bought A also bought B” recommender systems.
With the support of a five year NIH Big Data 2 Knowledge K01 Career Development Award, Chen is working to develop an approach to systematically extract and disseminate the undocumented collective wisdom of practicing clinicians, translating endpoint clinical data into a reproducible and executable form of expertise.
Presenter: Mark Musen, MD, PhD
Professor, Medical Informatics and of Biomedical Data Science
Stanford University
Dr. Musen is Professor of Biomedical Informatics at Stanford University, where he is Director of the Stanford Center for Biomedical Informatics Research. Dr. Musen conducts research related to intelligent systems, reusable ontologies, metadata for publication of scientific data sets, and biomedical decision support. His group developed Protégé, the world’s most widely used technology for building and managing terminologies and ontologies. He is principal investigator of the National Center for Biomedical Ontology, one of the original National Centers for Biomedical Computing created by the U.S. National Institutes of Heath (NIH). He is principal investigator of the Center for Expanded Data Annotation and Retrieval (CEDAR). CEDAR is a center of excellence supported by the NIH Big Data to Knowledge Initiative, with the goal of developing new technology to ease the authoring and management of biomedical experimental metadata. Dr. Musen chairs the Health Informatics and Modeling Topic Advisory Group for the World Health Organization’s revision of the International Classification of Diseases (ICD-11) and he directs the WHO Collaborating Center for Classification, Terminology, and Standards at Stanford University.
Early in his career, Dr. Musen received the Young Investigator Award for Research in Medical Knowledge Systems from the American Association of Medical Systems and Informatics and a Young Investigator Award from the National Science Foundation. In 2006, he was recipient of the Donald A. B. Lindberg Award for Innovation in Informatics from the American Medical Informatics Association. He has been elected to the American College of Medical Informatics and the Association of American Physicians. He is founding co-editor-in-chief of the journal Applied Ontology.
Presenters: Nigam Shah, MBBS, PhD
Associate Professor, Biomedical Informatics Research
Stanford University
Dr. Nigam Shah is associate professor of Medicine (Biomedical Informatics) at Stanford University, Assistant Director of the Center for Biomedical Informatics Research, and a core member of the Biomedical Informatics Graduate Program. Dr. Shah’s research focuses on combining machine learning and prior knowledge in medical ontologies to enable use cases of the learning health system.
Dr. Shah received the AMIA New Investigator Award for 2013 and the Stanford Biosciences Faculty Teaching Award for outstanding teaching in his graduate class on “Data driven medicine”. Dr. Shah was elected into the American College of Medical Informatics (ACMI) in 2015 and is inducted into the American Society for Clinical Investigation (ASCI) in 2016. He holds an MBBS from Baroda Medical College, India, a PhD from Penn State University and completed postdoctoral training at Stanford University.
Presenter: David Dorr, MD, MS
Assistant Professor, Medical Informatics and Clinical Epidemiology
Oregon Health and Science University
David A. Dorr, MD MS, earned his BA in Economics (with minors in Mathematics and Psychology) and his MD from Washington University in St. Louis. He then completed Internal Medicine residency at Oregon Health & Science University, and earned a Master’s in Medical Informatics and Health Services Administration from the University of Utah.
Broadly, David’s interests lie in complex care management, especially for older adults and other at-risk populations, coordination of care, collaborative care, chronic disease management, quality, and the requirements of clinical information systems to support these areas. From these interests, he has broadened into clinical information needs, Electronic Health Record (EHR) deployment and Health Information Exchange as a way to expand systems-based approaches to all of health care. Finally, David performs evaluations of care management and informatics initiatives using a variety of methodologies.
His current projects include dissemination, further innovation, and evaluation of the Care Management Plus project (funded by The John A. Hartford Foundation). He developed the Integrated Care Coordination Information System (ICCIS), a population management system connected to multiple EHRs and other data sources that does risk stratification, complex care management, quality measurement, and reporting. He works on primary care redesign modeling, using pragmatic/effectiveness trial designs to study how changes in incentives, technology infrastructure, and practice facilitation can help improve health, reduce cost, and improve patient satisfaction with care; his current study is the TOPMED trial (www.topmedtrial.org, funded by the Gordon and Betty Moore Foundation ) and he provides technical assistance for the Comprehensive Primary Care initiative (http://innovation.cms.gov/initiatives/Comprehensive-Primary-Care-Initiative/) and informatics initiatives.