Patient-Centered Information Commons

以患者为中心的信息共享

• 批准号: 9129865
• 负责人: ISAAC S. KOHANE
• 金额: $ 26.46万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-29 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9129865
• 关键词: Address; Adoption; Architecture; Behavioral; Big Data; Biological Assay; Caring; Categories; Classification; Clinical; Clinical Data; Code; Communities; Data; Data Set; Data Sources; Decentralization; Dependency; Development; Diagnostic; Disease; Electroencephalography; Etiology; Genetic; Genomics; Goals; Health; Image; Individual; Location; Longitudinal Studies; Marshal; Measurement; Measures; Methods; Molecular; Neurodevelopmental Disorder; Nomenclature; Observational Study; Ontology; Outcomes Research; Patient Outcomes Assessments; Patients; Performance; Population; Process; Research; Resources; Retrieval; Running; Science; Social Network; Sociology; Source; Students; Technology; Testing; base; clinical care; computing resources; data sharing; design; disorder risk; experience; interest; meetings; patient oriented; patient population; precision medicine; research and development; research study; social; spelling; success; tool

DESCRIPTION (provided by applicant): We propose to create a massively scalable toolkit to enable large, multi-center Patient-centered Information Commons (PIC) at local, regional and, national scale, where the focus is the alignment of all available biomedical data per individual. Such a Commons is a prerequisite for conducting the large-N, Big Data, longitudinal studies essential for understanding causation in the Precision Medicine (1) framework while simultaneously addressing key complexities of Patient Centric Outcome Research studies required under ACA (Affordable Care Act). Our proposal is solidly grounded in our experience over the last 25 in harnessing clinical care data to the research enterprise. In creating PIC we propose to focus on: 1. Enable the identification and retrieval of all data that pertain to individal health by creating a data sharing architecture that is capacious enough for all relevant data types and that enables patient and institutional autonomy to be respected. 2. Test fully-scaled implementations of the proposed architecture early in the development process, with the active involvement of a committed user community that seeks to use allowed us to refine our designs to facilitate subsequent robust dissemination and adoption. 3. Provide commodity workflows that can be used to 'clean' and complete the often noisy and sparse data gathered in the course of observational studies. 4. Embrace decentralization while enabling the construction of a nationally or regionally-scaled patient-centered information commons. 5. Encourage the selection of standards through the tools that enable the construction of patient-centered information commons. 6. Employ diagnostic classification and prognostication as figures of merit to measure how well a patient-centered information commons adds the understanding of patient populations. In addition to the research and development agenda we have also taken on the development of educational opportunities for end user community to become more familiar with the methods and challenges of data science.

描述（由申请人提供）：我们建议创建一个巨大的可扩展工具包，以在本地，区域和国家规模上实现大型，多中心的以患者为中心的信息共享（PIC），其中重点是每个人的所有可用生物医学数据的对齐。这样的共享是进行大N，大数据，纵向研究的先决条件，这对于理解Precision Medicine（1）框架中的因果关系至关重要，同时介绍了根据ACA（负担得起的护理法案）所需的以患者为中心的结果研究的关键复杂性。在过去25次将临床护理数据与研究企业一起利用的经验中，我们的建议基于我们的经验。在创建图片时，我们建议专注于：1。通过创建与所有相关数据类型相关的数据共享体系结构，启用与个人健康有关的所有数据的识别和检索，并使患者和机构自治受到尊重。 2。在开发过程的早期，测试拟议体系结构的完全缩放的实现，试图使用的坚定用户社区的积极参与使我们能够完善我们的设计，以促进随后的强大传播和采用。 3。提供可用于“清洁”并完成观察性研究过程中收集的嘈杂和稀疏数据的商品工作流程。 4.接受权力下放，同时可以建造以全国或区域为中心的以患者为中心的信息共享。 5。鼓励通过能够构建以患者为中心的信息共享的工具来选择标准。 6.将诊断分类和预后用作功绩的数字来衡量以患者为中心的信息公共信息对患者人群的理解。除了研究和发展议程外，我们还为最终用户社区的教育机会开发，以更加熟悉数据科学的方法和挑战。