Data science in healthcare

Abstract: Optum has an amazing view of the healthcare system and places like Optum Labs make that data available to researchers and others. But how can this data be used to improve the overall health of our nation? We will talk about a couple of ways that we use this data to help our members and our providers. The insurance industry is, at its heart, an industry of data science. The new capabilities of machine learning, deep learning, supervised and unsupervised modeling, are expanding and extending capabilities that have already been at the core of the industry. We will talk about specific models that enable us to better target members for intervention programs and help providers to better help their patients including a diabetic risk model, a medical adherence model, and a kidney risk model.

Bio: Anne runs the Boston data science team for Optum Enterprise Analytics (OEA) and has built a variety of models that measurably impact business outcomes. Anne combines business experience with data and modeling experience so is able to combine models with pragmatic business acumen. Anne joined Optum in 2016 and her team has since built a variety of machine learning models from disease models to models that improve operational efficiencies for businesses.

In her previous position, she was Chief Data Analyst for IBM’s analytics platform services business, a multi-billion dollar business. Anne has an undergraduate degree in Chemistry; a Master’s in Business Administration from MIT Sloan School of Business and was a Chartered Financial Analyst. She has more than 15 years of experience using data to impact business outcomes.