Mark Hlatky is a Professor of Health Policy and a Professor of Medicine (Cardiovasular Medicine) at the Stanford University School of Medicine. His major interests are in outcomes research, evidence-based medicine, and cost-effectiveness analysis. He introduced data collection about economic and quality of life endpoints in several randomized trials, principally trials of therapies for cardiovascular disease.

Hlatky received his MD from the University of Pennsylvania, and, after residency at the University of Arizona, studied as a Robert Wood Johnson Clinical Scholar at the University of California, San Francisco. He trained in cardiology at Duke University Medical Center, and then joined the Duke faculty. He has been at the Stanford University School of Medicine since 1989.

Paul Heidenreich MD, MS is Professor and Vice-Chair for Clinical, Quality, and Analytics in the Department of Medicine. He also directs VA's Quality Enhancement Research Initiative (QUERI) in Medication Management and the Echocardiography Laboratory at the VA Palo Alto Health Care System. His research focuses on interventions to improve the quality of care for heart disease patients; the use of echocardiography to predict prognosis; the cost-effectiveness of new cardiovascular technologies; and outcomes research using existing clinical and administrative data. His administrative efforts focuses on measuring, improving, and disseminating the quality of care provided by faculty in the Department of Medicine.

Alex Macario is a professor of anesthesiology and, by courtesy, of Health Research and Policy. He completed his undergraduate, medical school and business school training at the University of Rochester. He trained in anesthesiology at Stanford University and was chief resident. He then completed a fellowship in heath services research.

Dr. Macario has gained international recognition for his pioneering studies on operating room management, and the economics of surgery and anesthesia. He is particularly interested in the hospitalization costs for surgical patients, economic assessment of new drugs and devices for use in surgical care, and information technology to help physician leaders with clinical and administrative decision support in the surgery suite.

He is director of a Fellowship in the Management of Perioperative Services, based in the Department of Anesthesia. This postgraduate fellowship program trains several physicians per year in management science and applications to the delivery of surgical and anesthesia care.

Ross Shachter's research interests are in the modeling of uncertain processes and decision making. His main focus has been the communication and analysis of the relationships among uncertain quantities in a graphical representation called an influence diagram (closely related to a belief network). Professor Shachter's work in medical decision analysis has included management of bladder cancer follow-up and analysis of AIDS Policy therapies. During a leave of absence at Duke University's Center for Health Policy, he was able to bring his interests together to develop an influence diagram-based approach for medical technology assessment. He has been on the Stanford faculty since receiving his PhD in Operations Research from UC Berkeley in 1982.

Thomas N. Robinson, MD, MPH is the Irving Schulman, MD Endowed Professor in Child Health, Professor of Pediatrics and of Medicine, in the Division of General Pediatrics and the Stanford Prevention Research Center at Stanford University School of Medicine, and Director of the Center for Healthy Weight at Stanford University and Lucile Packard Children's Hospital at Stanford. Dr. Robinson focuses on "solution-oriented" research, developing and evaluating health promotion and disease prevention interventions for children, adolescents and their families to directly inform medical and public health practice and policy.

His research is largely experimental in design, conducting school-, family- and community-based randomized controlled trials to test the efficacy and/or effectiveness of theory-driven behavioral, social and environmental interventions to prevent and reduce obesity, improve nutrition, increase physical activity and decrease inactivity, reduce smoking, reduce children's television and media use, and demonstrate causal relationships between hypothesized risk factors and health outcomes. Robinson's research is grounded in social cognitive models of human behavior, uses rigorous methods, and is performed in generalizable settings with diverse populations, making the results of his research more relevant for clinical and public health practice and policy.

His research is published widely in the peer-reviewed scientific literature. Robinson received both his B.S. and M.D. from Stanford University and his M.P.H. in Maternal and Child Health from the University of California, Berkeley. He completed his internship and residency in Pediatrics at Children's Hospital, Boston and Harvard Medical School, and then returned to Stanford for post-doctoral training as a Robert Wood Johnson Clinical Scholar. Robinson joined the faculty at Stanford in 1993, was appointed Assistant Professor in 1996, and promoted to Associate Professor with tenure in 2003. He was a Robert Wood Johnson Foundation Generalist Physician Faculty Scholar, was a member of the Institute of Medicine's Committees on Prevention of Obesity in Children and Adolescents and Progress in Preventing Childhood Obesity, and is Principal Investigator on numerous prevention studies funded by the National Institutes of Health. Dr. Robinson also is Board Certified in Pediatrics, a fellow of the American Academy of Pediatrics, and practices General Pediatrics at Lucile Packard Children's Hospital at Stanford.

Professor Olshen is a Fellow of The Institute of Mathematical Statistics, The American Statistical Association, The American Association for the Advancement of Science, and The Institute of Electrical and Electronics Engineers.  He is an elected member of the International Statistical Institute. He has been a Guggenheim Fellow and the recipient of a Research Scholar in Cancer Award from the American Cancer Society. His interests include the development of statistical methods for prediction and the assessment of accuracy. He is one of the developers of CARTª binary tree-structured methods for classification, regression, and probability class estimation and of their extensions to survival analysis and clustering. In collaboration with others, he has studied these algorithms theoretically and has applied them to the computer-aided diagnosis of heart attack, as well as to making prognoses for patients with lymphoma, extracting features of organic compounds that tend to make them ulcerogenic, to data compression and the automated detection attempt to find the genes that predispose to hypertension, and to the definition of health states in health services research. His current research also involves the development of parsimonious models for describing longitudinal data, especially as they apply to understanding autoimmune disease of the kidney. Typically, these consist of the sum of an overall mean function and subject-specific coefficients of suitably smoothed eigenfunctions of residuals. In the past, he collaborated with Alan Garber in developing technologies for tracking cholesterol longitudinally in time and quantifying the accuracy of findings. Their ideas are now finding wide-ranging application.

Dr. Musen is Professor of Biomedical Informatics and of Biomedical Data Science, and 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 directs the World Health Organization Collaborating Center for Classification, Terminology, and Standards at Stanford University, which has developed much of the information infrastructure for the authoring and management of the 11^th edition of the International Classification of Diseases (ICD-11).