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Taking Action Against Clinician Burnout: A Systems Approach to Professional Well-Being
News
National Academy of Medicine to Join The Longevity Project as Independent Content Collaborator
The National Academy of Medicine (NAM) will serve as an independent content collaborator on The Longevity Project, which focuses on driving discussion around the 100-year life and identifying “key policy, product and organizational opportunities of the new era of...
Young Leaders Illustrate Health Equity in their Lives and Communities in NAM Art Gallery
On October 28, 2019, the National Academy of Medicine (NAM) hosted a pop-up art exhibition that offers insights from young people, ages 5-26, about how the social determinants of health - factors in the environment where people are born, live, learn, work, play,...
To ensure high quality patient care, the health care system must address clinician burnout tied to work and learning environments, administrative requirements
Between one-third and one-half of U.S. clinicians experience burnout and addressing the epidemic requires systemic changes by health care organizations, educational institutions, and all levels of government, says a new report from the National Academy of...
Team From University of Maryland, Baltimore, Wins Grand Prize in 2019 D.C. Public Health Case Challenge
The winners of the seventh annual D.C. Public Health Case Challenge were announced at this year’s National Academy of Medicine (NAM) Annual Meeting. The challenge aims to promote interdisciplinary, problem-based learning around a public health issue of importance to...
Featured Publication
Caring for the Individual Patient: Understanding Heterogeneous Treatment Effects
A Special Publication from the National Academy of Medicine
Evidence-based medicine arose from a clear need and represents a major advance in the science of clinical decision-making. Despite broad acceptance of evidence-based medicine, however, a fundamental issue remains unresolved: evidence is derived from groups of people, yet medical decisions are made by and for individuals. For evidence to be more applicable to individual patients, we need to combine methods for strong causal inference (first and foremost, randomization) with methods for prediction that permit inferences about which patients are likely to benefit and which are not. Better population-based outcomes will only be realized when we understand more completely how to treat patients as the unique individuals they are.
