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Molli Sanocki

Molli Sanocki

Head of Healthcare Analytics at LexisNexis Risk Solutions

Dr. Molli Sanocki currently leads a team of data scientists at LexisNexis Risk Solutions that is focused on development of models, improvement of data quality, and research and development.  The Healthcare division supports a broad portfolio of products built on socio-economic, provider, and deidentified claims data.  Molli has ten years of experience in developing models using deidentified patient data, primarily focused on life-science use cases.  Her educational background is a combination of Mathematics, Computer Science, and Statistics, and, prior to her work in the Healthcare industry, she was a university professor.  Throughout her career, Molli has devoted her time to mentorship, leadership development, and fostering an inclusive workplace.  


Track: Life Science & Healthcare

Meeting the Challenges of Secondary Use of Patient Data

Obtaining a full picture of a patient often involves several health-related datasets in addition to insights into the aspects of a patient’s life outside of their health records.  Over time, patients move, change jobs, change insurance coverage, and even change names.  Unfortunately, the more information that is added to a deidentified patient record, the greater the risk of reidentification.  Based on all of these challenges, what techniques can be used to create an effective dataset that protects a patient’s privacy and provides the essential information to answer the specific research questions?  In this talk, we will explore our approach to the creation of a referential patient token that allows more accurate tracking across life events, our methods for using this token to combine various real-world data assets, and our approach to expert determination to ensure that the dataset produced protects a patient’s privacy while still meeting the needs of the researcher.