Protecting Privacy and Facilitating Shared Access of Clinical and Genetic Data of Special Populations

保护隐私并促进特殊人群临床和遗传数据的共享访问

• 批准号: 9843564
• 负责人: LUCILA OHNO-MACHADO
• 金额: $ 156.91万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-12-15 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9843564
• 关键词: Address; Agreement; Algorithms; American Indians; Biomedical Research; Calibration; Cardiovascular Diseases; Cardiovascular system; Chronic Disease; Clinical Data; Code; Communication; Communities; Data; Data Analyses; Diagnostic; Docking; Employment; Ethics; Evaluation; Event; Factor Analysis; Feedback; Funding; Genetic; Genetic study; Genome; Genotype; Goals; Grain; Health Sciences; Healthcare; Heart; Incidence; Individual; Insurance; Interview; Intuition; Measures; Medical Genetics; Meta-Analysis; Methods; Modeling; Multivariate Analysis; National Heart, Lung, and Blood Institute; Oklahoma; Outcome; Outcomes Research; Output; Participant; Persons; Phenotype; Policies; Population Group; Prevalence; Privacy; Privatization; Procedures; Process; Research; Research Institute; Research Personnel; Resources; Risk; Risk Factors; Secure; Services; Site; Special Population; Statistical Data Interpretation; Structure; Surveys; Survival Analysis; System; Systems Analysis; Technology; Texas; Time; Tribes; Underserved Population; United States National Institutes of Health; Universities; Visualization; Work; analytical method; base; data access; data de-identification; data sharing; demographics; design; disadvantaged population; expectation; federated computing; formative assessment; genomic data; improved; innovation; interest; novel; operation; phenotypic data; preference; privacy preservation; privacy protection; scientific computing; social implication; virtual; web interface; web services

PROJECT SUMMARY The Strong Heart Study (SHS) is a multi-center, longitudinal resource designed to better understand cardiovascular disease in American Indians, identify significant risk factors, promote new research and deliver better health care. To achieve these goals, SHS data should be accessible to interested and qualified researchers, while no harm is done to the study participants who contribute their data. Thus private information in the data and the identity of the participants should be protected, and SHS tribal sovereignty and agreements that include tribal review and approval of all SHS data use requests should be respected. Our study aims to address these issues using advanced technologies and scientific computing toolkits to enable shared, but protected, data access, as well as to understand the data sharing preferences of SHS participants. The first aim is to develop an innovative, secure data-centric service to protect computation on SHS data according to governance practices that are acceptable to participating SHS tribes, SHS investigators, and the NIH. Specifically, we will build a system for secure analysis on protected data through a virtual private network, in which only approved operations and outputs are permitted. The proposed framework will allow researchers to easily and securely perform specific statistical analysis on SHS data and meta-analyses. The second aim is to develop novel federated computing models to support the SHS Coordinating Center and Genetics Center to analyze data in a distributed manner. The methods for achieving the second aim rely on new, practical federated data analysis technology. For example, in the case of vertically partitioned data, different data from the same SHS participants may be stored at different sites, such as genomic data and phenotype data that are currently stored at the SHS Genetics Center and the SHS Coordinating Center, respectively. The third aim is to understand the data sharing expectations and preferences of SHS participants to inform the implementation of the data sharing models. This aim will be carried out through qualitative and quantitative methods, which include the use of individual interviews and surveys of SHS participants.

项目摘要 强大的心脏研究（SHS）是一种多中心的纵向资源，旨在更好地了解 美洲印第安人的心血管疾病，确定重要的危险因素，促进新研究并提供 更好的医疗保健。为了实现这些目标，SHS数据应访问有兴趣和合格的 研究人员，尽管对贡献数据的研究参与者没有伤害。因此私人信息 在数据和参与者的身份中，应受到保护，并将部落的主权和协议提供 包括部落审查和所有SHS数据使用请求的批准。我们的研究旨在 使用高级技术和科学计算工具包解决这些问题，以启用共享，但 受保护，数据访问以及了解SHS参与者的数据共享偏好。第一个 目的是开发一种创新，安全的以数据为中心的服务，以根据SHS数据进行计算 参与的SHS部落，SHS调查人员和NIH可以接受的治理实践。 具体来说，我们将通过虚拟专用网络，在 仅允许使用批准的操作和输出。拟议的框架将使研究人员能够 轻松，安全地对SHS数据和荟萃分析进行特定的统计分析。第二个目标是 开发新颖的联合计算模型，以支持SHS协调中心和遗传学中心 以分布式方式分析数据。实现第二个目标的方法取决于新的，实用的 联合数据分析技术。例如，对于垂直分区的数据，来自 相同的SHS参与者可以存储在不同的站点，例如基因组数据和表型数据 目前分别存储在SHS遗传学中心和SHS协调中心。第三个目标是 了解SHS参与者的数据共享期望和偏好，以告知实施 数据共享模型。这个目标将通过定性和定量方法实现， 包括使用个人访谈和SHS参与者的调查。