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.

项目概要 强心脏研究 (SHS) 是一项多中心纵向资源，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，促进新的研究并提供 更好的医疗保健。为了实现这些目标，SHS 数据应该可供感兴趣且合格的人访问 研究人员，同时不会对贡献数据的研究参与者造成任何伤害。因此私人信息 参与者的数据和身份应得到保护，SHS部落主权和协议 应尊重所有 SHS 数据使用请求的部落审查和批准。我们的研究旨在 使用先进技术和科学计算工具包来解决这些问题，以实现共享但 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 目标是开发一种创新的、安全的以数据为中心的服务，以保护 SHS 数据的计算 参与 SHS 部落、SHS 调查人员和 NIH 可接受的治理实践。 具体来说，我们将建立一个通过虚拟专用网络对受保护数据进行安全分析的系统， 仅允许经批准的操作和输出。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依赖于新的、实用的方法。 联合数据分析技术。例如，在垂直分区数据的情况下，不同的数据 相同的 SHS 参与者可能存储在不同的站点，例如基因组数据和表型数据 目前分别保存在 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。这一目标将通过定性和定量的方法来实现， 包括对 SHS 参与者进行个人访谈和调查。