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Electronic Health Records + Natural Language Processing + Machine Learning = Improved Sentinel Outcome Detection Algorithms

    Event Information
    12:00pm - 1:00pm EST
    Event Type
    Event Location

    This presentation describes the work of a multi-site team to improve automated algorithms for identifying health outcomes of interest to the FDA Sentinel Initiative by applying data-driven machine learning and natural language processing (NLP) methods to rich information from electronic health records. We will describe the motivation, approach, results and implications of this work developing and validating an algorithm to identify anaphylaxis, a rare but potentially life-threatening adverse event associated with medical products use that cannot be accurately measured using traditional, administrative claims data alone.

    Target Audience:
    Medical informaticists, medical product safety and real-world evidence researchers and regulators

    Event Materials

    View a recording of the webinar here.

    View the presentation of the webinar here.



    Susan Gruber, PhD, David S. Carrell, PhD