TWC: Medium: Collaborative: Broker Leads for Privacy-Preserving Discovery in Health Information Exchange

TWC：媒介：协作：经纪人主导健康信息交换中的隐私保护发现

• 批准号: 1408874
• 负责人: XiaoFeng Wang
• 金额: $ 36万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1408874&HistoricalAwards=false
• 关键词: TWC; Medium; Collaborative; Broker; Leads

Support for research on distributed data sets is challenged by stakeholder requirements limiting sharing. Researchers need early stage access to determine whether data sets are likely to contain the data they need. The Broker Leads project is developing privacy-enhancing technologies adapted to this discovery phase of data-driven research. Its approach is inspired by health information exchanges that are based on a broker system where data are held by healthcare providers and collected in distributed queries managed by the broker. Such systems have potential to support public health and biomedical research. The project targets "similar patient queries" where the query is a patient medical record and the response is information about similar patients. Such queries have value for many applications, including developing cohorts for finding institutions for further discussions about joint research.Broker Leads uses the concept of a "lead" in which data holders provide representative collections of non-identifiable real or synthetic data meeting strong privacy guarantees, e.g., differential privacy. Even though such data may be unsuitable for clinical decision making and scientific discovery due to the transformations done for privacy protection, they guide a user of a broker lead system to the data sets very likely to be useful to addressing a given similar patient query. These data sets can then be used with other privacy-protecting strategies, such as secure multiparty computation or restrictive data use agreements ensuring adequate data protection. In addition to providing practical and well-analyzed strategies for early stages of research on healthcare data, this project will provide new insights into practical issues with privacy technology in end-to-end applications.

利益相关者的要求限制共享，对分布式数据集的研究支持。研究人员需要早期访问才能确定数据集是否可能包含所需的数据。经纪人领导项目正在开发适合于数据驱动研究的发现阶段的隐私增强技术。它的方法的灵感来自基于经纪人系统的健康信息交换，其中医疗保健提供商持有数据并收集在经纪人管理的分布式查询中。这样的系统有可能支持公共卫生和生物医学研究。 该项目的目标是“类似的患者查询”，其中查询是患者​​的病历，并且反应是有关类似患者的信息。此类查询对许多应用程序都有价值，包括开发用于查找有关联合研究的进一步讨论的同类群体。经纪主管使用了“铅”的概念，在该概念中，数据持有人提供了代表性的非可识别的真实或合成数据符合强大隐私保证的藏品，例如不同的隐私。 即使由于为隐私保护进行的转换而导致的转换，此类数据可能不适合临床决策和科学发现，但它们指导经纪人铅系统的用户对数据集的用户很可能对处理给定的类似患者查询很有用。然后可以将这些数据集用于其他隐私保护策略，例如安全的多方计算或限制性数据使用协议，以确保足够的数据保护。 除了为医疗保健数据研究的早期阶段提供实践和精心分析的策略外，该项目还将为端到端应用程序中隐私技术的实际问题提供新的见解。