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）：已经提出了一系列潜在解决方案，以应对基因组研究的机密性挑战，以及如何在这个“大数据”时代最好地进行。一些倡导的措施，以进一步限制访问基因组信息。其他人则主张加强禁止滥用的法律。同时，对联邦和州法律创建的当前“网络”的优势和劣势知之甚少。此外，新兴模型通过将控制权转移到参与者是否，与谁以及出于其目的共享的目的，从传统中脱颖而出。迫切需要更好地了解现有的法律保护群，它们如何应用于迅速发展的研究环境以及如何最好地告知潜在参与者在不同情况下这些保护的程度和局限性。拟议的研究的目的是收集有关适用于基因组研究的机密性保护的实际范围（超出基本安全措施）的实际范围，以及如何将其描述给潜在参与者。为了实现这一目标，我们将：（1）进行深入的定性访谈，以探讨思想领导者对基因组研究中风险，利益和机密性的看法； （2）对保护基因组研究机密性的法律工具进行了广泛的分析（例如，遗传反歧视法，数据共享政策和法规），包括它们在现实的研究方案中的应用，包括当前和不断发展的方法来控制数据共享； （3）评估当前同意语言，并开发灵活的模型语言，简单而准确地描述了基因组研究中的机密性风险和保护。这些目标的行为将被高度融合，每个目标都会通知并被其他人告知。预期的结果将是广泛的互补，高质量数据，涉及在基因组研究中保护机密性的优势和局限性，包括在新兴方法中控制数据共享以及两者之间的风险和保护措施，以及应向预期参与者描述的风险和保护。这些数据将进一步支持未来研究的几个重要领域，包括研究参与者观点和理解，基因组研究人员的观点以及对我们的模型同意语言的严格经验评估。