Danielle Whicher – författare

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.

Learning health systems are driven by multiple stakeholders—patients, clinicians and clinical teams, health care organizations, academic institutions, government, industry, and payers. Each stakeholder group has its own sources of data, its own priorities, and its own goals and needs with respect to sharing that data. However, in America''s current health system, these stakeholders operate in silos without a clear understanding of the motivations and priorities of other groups. The three stakeholder working groups that served as the authors of this Special Publication identified many cultural, ethical, regulatory, and financial barriers to greater data sharing, linkage, and use. What emerged was the foundational role of trust in achieving the full vision of a learning health system.

This Special Publication outlines a number of potentially valuable policy changes and actions that will help drive toward effective, efficient, and ethical data sharing, including more compelling and widespread communication efforts to improve awareness, understanding, and participation in data sharing. Achieving the vision of a learning health system will require eliminating the artificial boundaries that exist today among patient care, health system improvement, and research. Breaking down these barriers will require an unrelenting commitment across multiple stakeholders toward a shared goal of better, more equitable health.

We can improve together by sharing and using data in ways that produce trust and respect. Patients and families deserve nothing less.

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 further 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.

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.

This Special Publication is based on a workshop, held by the National Academy of Medicine, that considered patient and stakeholder perspectives on the importance of understanding heterogeneous treatment effects (HTE) and best practices for implementing clinical programs that take HTE into account. 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.

Health services research is "the multidisciplinary field of scientific investigation that studies how social factors, financing systems, organizational structures and processes, health technologies, and personal behaviors affect access to health care and the quality and cost of health care." Since the 1960s, health services research has provided the foundation for progress, effectiveness, and value in health care. Ironically, at a time in which appreciation has never been higher for both the need and potential from health services research, the political and financial support for sustenance and growth appear to be weakening.

With funding support from AcademyHealth, the American Association of Colleges of Nursing, the American Board of Family Medicine, the American Society of Anesthesiologists, the Association of American Medical Colleges, the Federation of American Hospitals, and the Robert Wood Johnson Foundation, this National Academy of Medicine Special Publication identifies the range of issues that health services research must consider, address, and potentially overcome to transform the field to meet the needs of a 21st-century health care system. These issues are broad, multidisciplinary, and will require a coordinated effort to address—as well as dedicated and sustainable funding. Federal support for health services research has never been more critical. Now is a critical time for the field to articulate its priorities, demonstrate its utility, and transform to meet the needs of a 21st-century health care system. The physical and financial health of the nation is at stake.

To advance insights and perspectives on how to better manage the care of the high-need patient population, the National Academy of Medicine, with guidance from an expert planning committee, was tasked with convening three workshops held between July 2015 and October 2016. The resulting special publication, Effective Care for High-Need Patients: Opportunities for Improving Outcomes, Value, and Health, summarizes the presentations, discussions, and relevant literature.

In 2016, the National Academy of Medicine (NAM) hosted a series of meetings, which was sponsored by the Patient-Centered Outcomes Research Institute, with support from NAM''s Executive Leadership Network. The series underscored the importance of partnerships between researchers and health system leadership and considered opportunities to build institutional capacity, cross-institutional synergy, and system-wide learning. During these meetings, health system executives, researchers, and others discussed building infrastructure that simultaneously facilitates care delivery, care improvement and evidence development. The vision is a digital system-wide progress toward continuous and seamless learning and improvement throughout health and health care. This publication aims to answer the following questions: