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A Query Workflow Design to Perform Automatable Distributed Regression Analysis in Large Distributed Data Networks

    Basic Details
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    Description

    Patient privacy and data security concerns often limit the feasibility of pooling patient-level data from multiple sources for analysis. Distributed data networks (DDNs) that employ privacy-protecting analytical methods, such as distributed regression analysis (DRA), can mitigate these concerns. However, DRA is not routinely implemented in large DDNs. This article describes the design and implementation of a process framework and query workflow that allow automatable DRA in real-world DDNs that use PopMedNetā„¢, an open-source distributed networking software platform.

    Author(s)

    Qoua L. Her, Jessica M. Malenfant, Sarah Malek, Yury Vilk, Jessica Young, Lingling Li, Jeffery Brown, Sengwee Toh

    Corresponding Author

    Qoua Her, Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, 401 Park Drive, Suite 401 East, Boston, MA. Email: qoua_her@harvardpilgrim.org