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Wagholikar, Kavishwar

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Wagholikar

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Kavishwar

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Wagholikar, Kavishwar

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Now showing 1 - 3 of 3
  • Publication

    SMART-on-FHIR implemented over i2b2

    (Oxford University Press, 2016) Wagholikar, Kavishwar; Mandel, Joshua; Klann, Jeffery G; Wattanasin, Nich; Mendis, Michael; Chute, Christopher G; Mandl, Kenneth; Murphy, Shawn

    We have developed an interface to serve patient data from Informatics for Integrating Biology and the Bedside (i2b2) repositories in the Fast Healthcare Interoperability Resources (FHIR) format, referred to as a SMART-on-FHIR cell. The cell serves FHIR resources on a per-patient basis, and supports the “substitutable” modular third-party applications (SMART) OAuth2 specification for authorization of client applications. It is implemented as an i2b2 server plug-in, consisting of 6 modules: authentication, REST, i2b2-to-FHIR converter, resource enrichment, query engine, and cache. The source code is freely available as open source. We tested the cell by accessing resources from a test i2b2 installation, demonstrating that a SMART app can be launched from the cell that accesses patient data stored in i2b2. We successfully retrieved demographics, medications, labs, and diagnoses for test patients. The SMART-on-FHIR cell will enable i2b2 sites to provide simplified but secure data access in FHIR format, and will spur innovation and interoperability. Further, it transforms i2b2 into an apps platform.

  • Publication

    Feasibility of Homomorphic Encryption for Sharing I2B2 Aggregate-Level Data in the Cloud

    (American Medical Informatics Association, 2017) Raisaro, Jean Louis; Klann, Jeffrey; Wagholikar, Kavishwar; Estiri, Hossein; Hubaux, Jean-Pierre; Murphy, Shawn

    The biomedical community is lagging in the adoption of cloud computing for the management of medical data. The primary obstacles are concerns about privacy and security. In this paper, we explore the feasibility of using advanced privacy-enhancing technologies in order to enable the sharing of sensitive clinical data in a public cloud. Our goal is to facilitate sharing of clinical data in the cloud by minimizing the risk of unintended leakage of sensitive clinical information. In particular, we focus on homomorphic encryption, a specific type of encryption that offers the ability to run computation on the data while the data remains encrypted. This paper demonstrates that homomorphic encryption can be used efficiently to compute aggregating queries on the ciphertexts, along with providing end-to-end confidentiality of aggregate-level data from the i2b2 data model.

  • Publication

    Automating Installation of the Integrating Biology and the Bedside (i2b2) Platform

    (SAGE Publications, 2018) Wagholikar, Kavishwar; Mendis, Michael; Dessai, Pralav; Sanz, Javier; Law, Sindy; Gilson, Micheal; Sanders, Stephan; Vangala, Mahesh; Bell, Douglas S; Murphy, Shawn

    Informatics for Integrating Biology and the Bedside (i2b2) is an open source clinical data analytics platform used at more than 150 institutions for querying patient data. An i2b2 installation (called hive) comprises several i2b2 cells that provide different functionalities. Given the complex architecture of i2b2 installation, creating a working installation of the platform is challenging for new users. This is despite the availability of extensive documentation for i2b2 and access to a large and active mailing list community of i2b2 users. To address this problem, we have created an automated installation package, called i2b2-quickstart, which automatically downloads the latest i2b2 source code and dependencies, and compiles and configures the i2b2 cells to create a functional i2b2 hive installation. This package will serve as a convenient starting point and reference implementation that will facilitate researchers in the installation and exploration of the i2b2 platform.