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Description

Abstract: Electronic Health Records (EHRs) provide a wealth of information from which to conduct research. Complement this data with Medicare Claims and you have a powerhouse of information that tells a patient’s story. We will discuss our early experiences and the technical design for a Machine Learning project working on this data predicting patient Admissions, and its high-performance implementation within a typical enterprise IT environment.

Learning Objective 1: To understand the benefits and challenges in combining claims and EHR data.

Learning Objective 2 (Optional): To learn about a successful data pipeline enabling machine learning on a combined EHR and claims dataset.

Authors:

Ursula Rogers (Presenter)
Duke University

Shelley Rusincovitch, Duke University
Erich Huang, Duke
Ricardo Henao, Duke University
Michael Gao, Duke University
Mary Schilder, Duke Health
Eugenie Komives, Duke Health

Presentation Materials:

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