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

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

Author information

1
Health Equity Institute, San Francisco State University, San Francisco, CA 94132, USA. kathykim@sfsu.edu

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.

PMID:
23774516
DOI:
10.1097/MLR.0b013e31829b1d9f
[Indexed for MEDLINE]

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