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为多州比较实效研究网络制定隐私和安全政策框架。

Development of a privacy and security policy framework for a multistate comparative effectiveness research network.

机构信息

Health Equity Institute, San Francisco State University, San Francisco, CA 94132, USA.

出版信息

Med Care. 2013 Aug;51(8 Suppl 3):S66-72. doi: 10.1097/MLR.0b013e31829b1d9f.

Abstract

Comparative effectiveness research (CER) conducted in distributed research networks (DRNs) is subject to different state laws and regulations as well as institution-specific policies intended to protect privacy and security of health information. The goal of the Scalable National Network for Effectiveness Research (SCANNER) project is to develop and demonstrate a scalable, flexible technical infrastructure for DRNs that enables near real-time CER consistent with privacy and security laws and best practices. This investigation began with an analysis of privacy and security laws and state health information exchange (HIE) guidelines applicable to SCANNER participants from California, Illinois, Massachusetts, and the Federal Veteran's Administration. A 7-member expert panel of policy and technical experts reviewed the analysis and gave input into the framework during 5 meetings held in 2011-2012. The state/federal guidelines were applied to 3 CER use cases: safety of new oral hematologic medications; medication therapy management for patients with diabetes and hypertension; and informational interventions for providers in the treatment of acute respiratory infections. The policy framework provides flexibility, beginning with a use-case approach rather than a one-size-fits-all approach. The policies may vary depending on the type of patient data shared (aggregate counts, deidentified, limited, and fully identified datasets) and the flow of data. The types of agreements necessary for a DRN may include a network-level and data use agreements. The need for flexibility in the development and implementation of policies must be balanced with responsibilities of data stewardship.

摘要

在分布式研究网络 (DRN) 中进行的比较效果研究 (CER) 受到不同州法律和法规以及旨在保护健康信息隐私和安全的机构特定政策的约束。Scalable National Network for Effectiveness Research (SCANNER) 项目的目标是开发和展示一种可扩展的、灵活的 DRN 技术基础设施,使近实时 CER 符合隐私和安全法律以及最佳实践。这项调查始于分析适用于来自加利福尼亚州、伊利诺伊州、马萨诸塞州和联邦退伍军人管理局的 SCANNER 参与者的隐私和安全法律以及州健康信息交换 (HIE) 指南。一个由 7 名政策和技术专家组成的专家小组在 2011 年至 2012 年举行的 5 次会议上审查了分析结果并为框架提供了意见。该州/联邦准则适用于 3 个 CER 用例:新型口服血液药物的安全性;糖尿病和高血压患者的药物治疗管理;以及急性呼吸道感染治疗中提供者的信息干预。政策框架提供了灵活性,从用例方法而不是一刀切的方法开始。政策可能因共享的患者数据类型(汇总计数、去识别、有限和完全识别数据集)和数据流向而异。DRN 所需的协议类型可能包括网络级和数据使用协议。政策制定和实施的灵活性需求必须与数据管理责任相平衡。

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