Beyond Data Security: Promoting Confidentiality and Advancing Science

超越数据安全：促进保密并推动科学发展

• 批准号: 8692324
• 负责人: LAURA M. BESKOW
• 金额: $ 45.34万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-24 至 2017-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8692324
• 关键词: Advocate; Area; Attention; Benefits and Risks; Big Data; Bioethics; Cataloging; Catalogs; Code; Confidentiality; Consent; Consent Forms; Data; Data Quality; Data Security; Development; Disclosure; Discrimination; Disease; Effectiveness; Environment; Feedback; Foundations; Frequencies; Genetic; Genome; Genomics; Goals; Health; Human; Human Genome; Individual; Informed Consent; Internet; Interview; Investigation; Knowledge; Language; Laws; Learning; Legal; Measures; Modeling; Nature; Outcome; Participant; Perception; Policies; Practice Guidelines; Privacy; Procedures; Regulation; Research; Research Design; Research Personnel; Risk; Science; Security Measures; Solutions; Structure; Surveys; System; Time; base; data sharing; evidence base; flexibility; genome wide association study; interest; prospective; public health relevance; public trust; risk sharing; success; tool

DESCRIPTION (provided by applicant): A range of potential solutions has been proposed to the confidentiality challenges in genome research and how best to proceed in this era of "big data" is not known. Some advocate measures to further restrict access to genomic information. Others argue for strengthening laws that prohibit misuse. In the meantime, the strengths and weaknesses of the current "web" of protections created by federal and state law are poorly understood. In addition, emerging models are breaking from tradition by ceding control to participants over whether, with whom, and for what purposes their data are shared. There is an urgent need to better understand the existing constellation of legal protections, how they apply to a swiftly evolving research environment, and how best to inform prospective participants about the extent and limitations of these protections in different contexts. The objective of the proposed research is to gather empirical data regarding the actual scope of the confidentiality protections applicable to genome research (beyond basic security measures), as well as how these are and should be described to prospective participants. To achieve this objective, we will: (1) Conduct in-depth qualitative interviews to explore thought leaders' views of risks, benefits, and confidentiality in genome research; (2) Carry out extensive analysis of the legal tools for protecting confidentiality in genome research (e.g., genetic anti-discrimination laws, data sharing policies and regulations), including their application to realistic research scenarios encompassing both current and evolving approaches to control over data sharing; and (3) Assess current consent language and develop flexible model language that simply and accurately describes the confidentiality risks and protections in genome research. The conduct of these aims will be highly integrated, with each one informing and being informed by the others. The expected outcome will be an extensive body of complementary, high quality data concerning the strengths and limitations of legal means to protect confidentiality in genome research-including in the context of emerging approaches to control over data sharing-and how the risks and protections both are and should be described to prospective participants. These data will further support several important areas of future research, including investigation of participant opinions and understanding, genome researcher perspectives, and rigorous empirical assessment of our model consent language.

描述（由申请人提供）：针对基因组研究中的保密性挑战，已经提出了一系列潜在的解决方案，但在这个“大数据”时代如何最好地进行尚不清楚。一些人主张采取措施进一步限制基因组信息的获取。其他人则主张加强禁止滥用的法律。与此同时，人们对联邦和州法律当前建立的保护“网络”的优点和缺点知之甚少。此外，新兴模型正在打破传统，将数据是否共享、与谁共享以及出于何种目的共享的控制权交给参与者。迫切需要更好地了解现有的法律保护体系，它们如何适用于快速发展的研究环境，以及如何最好地告知潜在参与者这些保护措施在不同背景下的范围和局限性。拟议研究的目的是收集有关适用于基因组研究的保密保护的实际范围（超出基本安全措施）的经验数据，以及如何以及应该如何向潜在参与者描述这些数据。为实现这一目标，我们将：（1）进行深入的定性访谈，探讨思想领袖对基因组研究的风险、收益和保密性的看法； (2) 对基因组研究中保护机密性的法律工具（例如基因反歧视法、数据共享政策和法规）进行广泛分析，包括将其应用于现实研究场景，包括当前和不断发展的数据共享控制方法； (3) 评估当前的同意语言并开发灵活的模型语言，以简单、准确地描述基因组研究中的保密风险和保护。这些目标的实现将高度整合，每个目标都向其他目标通报信息并被其他目标通报。预期结果将是大量补充性的高质量数据，涉及保护基因组研究机密性的法律手段的优势和局限性（包括在控制数据共享的新兴方法的背景下），以及如何向潜在参与者描述风险和保护。这些数据将进一步支持未来研究的几个重要领域，包括对参与者意见和理解的调查、基因组研究人员的观点以及对我们模型同意语言的严格实证评估。