The National Academy of Medicine’s Leadership Consortium: Collaboration for a Value & Science-Driven Health System provides a trusted venue for national leaders in health and health care to work cooperatively toward their common commitment to effective, innovative care that consistently adds value to patients and society. Consortium Members are leaders from core stakeholder communities brought together by their common commitment to steward the advances in science, value and culture necessary for a health system that continuously learns and improves in fostering healthier people.
"A learning health care system is one in which science, informatics, incentives, and culture are aligned for continuous improvement, innovation, and equity - with best practices seamlessly embedded in the delivery process, individuals and families active participants in all elements, and new knowledge generated as an integral by-product of the delivery experience."
NAM Leadership Consortium Charter
Advancing health and health care through cooperative projects
Action Collaboratives engage key stakeholders with similar interests and field responsibilities in cooperative activities to advance science and value in health and health care. These ad hoc convening activities aim to foster sector information sharing and cooperation in accelerating the evolution of a continuously learning health system, and progress on findings highlighted in prior Academies reports of mutual priority. Action Collaboratives currently support activities in four overlapping and complementary areas:
Advancing a culture of health equity and engagement that places the needs of people and communities at its core.
Supporting the conditions necessary for transforming real world experiences into valuable data that are routinely used to improve population and patient-level health.
Fostering improvements and innovation in digital infrastructure so that health technology is developed and applied in ways that consistently lead to better population and patient-level health.
Supporting payment systems that incentivize value and population health.
Employing an inclusive, “collaborative without walls” approach—balanced with practicality around individual projects—these convening activities bring together stakeholders with mutual interests to harness their substantial talent and expertise in the identification and development of cooperative efforts most practical and strategic to field advancement.
Projects of the Action Collaboratives are participant identified, driven, and supported, with facilitation by Consortium staff. They vary in structure and content to meet the needs of specific issues and challenges. Some focus on identifying issues of common interest and marshaling needed leadership, expertise and resources; others aim at cooperative development of tools needed for progress; and others seek to highlight strategies, through individually authored literature summaries, technical discussions, and cooperative issue reviews. Certain activities lead to proposals for formal workshops and studies for consideration by the NAM and the Academies.
Consortium activities are both informational and project focused. Projects are participant generated and supported, NAM-staff facilitated, and participant executed and “owned.” Products are ascribed to the engaged individuals. They are not products of the NAM or the Academies. Endorsement and use is at the discretion of individual organizations.
Health Data Sharing to Support Better Outcomes: Building a Foundation of Stakeholder Trust
The effective use of data is foundational to the concept of a learning health system—one that leverages and shares data to learn from every patient experience, and feeds the results back to clinicians, patients and families, and health care executives to transform health, health care, and health equity. More than ever, the American health care system is in a position to harness new technologies and new data sources to improve individual and population health.
We can improve together by sharing and using data in ways that produce trust and respect. Patients and families deserve nothing less.
Artificial Intelligence in Health Care: The Hope, the Hype, the Promise, the Peril
The emergence of artificial intelligence (AI) in health care offers unprecedented opportunities to improve patient and clinical team outcomes, reduce costs, and impact population health. While there have been a number of promising examples of AI applications in health care, it is imperative to proceed with caution or risk the potential of user disillusionment, another AI winter, or futher exacerbation of existing health- and technology-driven disparities.
This Special Publication synthesizes current knowledge to offer a reference document for relevant health care stakeholders. It outlines the current and near-term AI solutions; highlights the challenges, limitations, and best practices for AI development, adoption, and maintenance; offers an overview of the legal and regulatory landscape for AI tools designed for health care application; prioritizes the need for equity, inclusion, and a human rights lens for this work; and outlines key considerations for moving forward.
AI is poised to make transformative and disruptive advances in health care, but it is prudent to balance the need for thoughtful, inclusive health care AI that plans for and actively manages and reduces potential unintended consequences, while not yielding to marketing hype and profit motives.
Caring for the Individual Patient: Understanding Heterogeneous Treatment Effects
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. Despite persistent assertions from clinicians that determining the best therapy for each patient is a more complicated endeavor than just picking the best treatment on average, traditional approaches have been overly reliant on the average effects estimated from the outcomes of clinical trials.
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 particular 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.
Leadership Consortium Staff
J. Michael McGinnis, Executive Director | Bio and CV
Laura Adams, Senior Counsel, Science and Technology | LAdams@nas.edu
Mahnoor (Noor) Ahmed, Associate Program Officer, Science and Technology | MAhmed@nas.edu
Ayodola Anise, Portfolio Director, Value and Culture | AAnise@nas.edu
Ariana Bailey, Senior Program Assistant | ABailey@nas.edu
Anna Cupito, Associate Program Officer, Value and Culture | ACupito@nas.edu
Elaine Fontaine, Consultant | EFontaine@nas.edu
Jennifer Lee, Visiting Scholar | JLee@nas.edu
Angana Roy, Program Strategy Officer | ARoy@nas.edu
Asia Williams, Research Associate | AsWilliams@nas.edu