Workshop: Identifying the Research Challenges Underlying a National-Scale Learning Health System

研讨会：确定国家规模的学习健康系统背后的研究挑战

• 批准号: 1249354
• 负责人: Charles Friedman
• 金额: $ 9.98万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2014-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1249354&HistoricalAwards=false
• 关键词: Workshop; Identifying; Research; Challenges; Underlying

It is widely acknowledged that improving health in the United States will require the creation of a national-scale Learning Health System. A Learning Health System (LHS) will allow the nation to take full advantage of advanced computational methods and the increasing amounts of health-related data available in digital form. An LHS would enable such data to be rapidly mobilized and continuously analyzed--and the results subsequently shared in "actionable" forms--to improve health care quality; empower public health and biomedical research; and enable patients and their families, along with their care providers, to make better-informed collaborative health decisions. The creation of an LHS at national scale is a monumental socio-technical challenge. These challenges invoke a broad scope of open fundamental scientific questions that, to date, have not been clearly identified. To address these issues we will undertake a road-mapping activity in the form of a two-day invitational workshop in Washington, DC. The workshop, engaging approximately 35 of the nation's leading scientists, will identify and describe these open questions, and will identify interrelationships among them. Participants will bring expertise spanning three broad challenge areas underlying a national-scaled LHS: 1) system requirements, modeling and performance; 2) data, knowledge, and analytics; and 3) organization, economics, and policy. These challenge areas invoke the computational/informational sciences and related fields of engineering, the behavioral and social sciences, and the biomedical sciences. The results of this workshop will provide clear direction for a next generation of research to address a class of problems of vital interest to health and well-being of individuals and populations. Also, because the challenges to be addressed in the workshop are profoundly interdisciplinary, the results will create potential for collaboration among groups of scientists who have not yet come together around these most important problems.

人们普遍认为，改善美国的健康状况需要建立一个全国性的学习健康系统。 学习健康系统（LHS）将使国家能够充分利用先进的计算方法和越来越多的数字形式的健康相关数据。LHS将使这些数据能够被快速调动和持续分析-随后以“可操作”的形式分享结果-以提高医疗保健质量;增强公共卫生和生物医学研究的能力;并使患者及其家属沿着他们的护理提供者，做出更明智的协作健康决策。在全国范围内建立LHS是一项巨大的社会技术挑战。 这些挑战引发了广泛的开放性基本科学问题，迄今尚未明确确定。为了解决这些问题，我们将在华盛顿举办为期两天的邀请研讨会，开展路线图活动。 该研讨会将邀请大约35名美国顶尖科学家参加，将确定和描述这些开放性问题，并确定它们之间的相互关系。参与者将带来跨越国家级LHS三大挑战领域的专业知识：1）系统要求，建模和性能; 2）数据，知识和分析; 3）组织，经济和政策。这些挑战领域涉及计算/信息科学和相关的工程领域、行为和社会科学以及生物医学科学。这次讲习班的成果将为下一代研究提供明确的方向，以解决对个人和人口的健康和福祉至关重要的一类问题。 此外，由于研讨会要解决的挑战是深刻的跨学科问题，其结果将为尚未围绕这些最重要问题聚集在一起的科学家群体之间的合作创造潜力。