Patricia Gabow Receives Lienhard Award From National Academy of Medicine for Transforming Safety Net Hospital Into Nationally Recognized Health System
For her role in transforming a safety net hospital into a national model for high-quality, cost-efficient health care, the National Academy of Medicine today announced Patricia Gabow is the recipient of the 2019 Gustav O. Lienhard Award for Advancement of Health Care....
Daniel Weinberger Receives National Academy of Medicine’s Sarnat Award for His Pioneering Research on Developmental Origins of Schizophrenia
The National Academy of Medicine today announced Daniel Weinberger is the recipient of the 2019 Rhoda and Bernard Sarnat International Prize in Mental Health, for his fundamental role in elucidating the biological origins and genetic expressions of schizophrenia, and...
World at Risk from Deadly Pandemics: Expert group including NAM President Victor Dzau outlines steps to prepare for – and mitigate – the effects of a widespread global health emergency
Governments and international institutions must take bold steps to manage the mounting threat of deadly disease outbreaks. This is the stark warning of a report released today by an international group of experts, which outlines concrete actions to prepare the world...
The National Academy of Medicine (NAM) has selected five outstanding health professionals for the class of 2019 NAM Fellowships. The fellows were chosen based on their professional qualifications, reputations as scholars, professional accomplishments, and relevance of...
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.
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