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Design and Implementation of a Secure Computing Environment for Analysis of Sensitive Data at an Academic Medical Center

机译:学术医学中心用于敏感数据分析的安全计算环境的设计与实现

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摘要

Academic medical centers need to make sensitive data from electronic health records, payer claims, genomic pipelines, and other sources available for analytical and educational purposes while ensuring privacy and security. Although many studies have described warehouses for collecting biomedical data, few studies have described secure computing environments for analysis of sensitive data. This case report describes the Weill Cornell Medicine Data Core with respect to user access, data controls, hardware, software, audit, and financial considerations. In the 2.5 years since launch, the Data Core has supported more than 200 faculty, staff, and students across nearly 60 research and education projects. Other institutions may benefit from adopting elements of the approach, including tools available on Github, for balancing access with privacy and security.
机译:学术医疗中心需要从电子健康记录,付款人索赔,基因组管道以及其他可用于分析和教育目的的来源中获取敏感数据,同时确保隐私和安全。尽管许多研究描述了用于收集生物医学数据的仓库,但很少有研究描述了用于分析敏感数据的安全计算环境。该案例报告从用户访问,数据控制,硬件,软件,审计和财务考虑方面描述了威尔康奈尔医学数据核心。自发布以来的2.5年中,数据核心为近60个研究和教育项目中的200多名教职员工提供了支持。其他机构可能会受益于采用该方法的元素,包括Github上可用的工具,以平衡访问与隐私和安全性。

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