Robbie Freeman is the Vice President of Clinical Innovation at the Mount Sinai Health System. He is passionate about leveraging technology to improve quality, patient safety and care delivery. Over the past 9 years, Robbie has held several leadership roles within the Mount Sinai Health System (MSHS). He is Co-Director of the Clinical Data Science Team, tasked with building predictive models that leverage AI to improve patient safety and hospital operations; to-date, the team has deployed predictive models addressing falls, patient deterioration, delirium, discharge planning and malnutrition. He holds a Master’s in Business Analytics from the NYU Stern School of Business, a B.S in Human Biology from the University at Albany, a M.S.N in Clinical Systems Management from Excelsior College and is a graduate of the Philips School of Nursing at Mount Sinai BI where he currently serves on the Board of Trustees.
Developing a Machine Learning Platform for Quality and Patient Safety
This session will explore one organization's journey with embedding AI into hospital operations and clinical workflows. We will cover the framework used to develop and deploy real-time products that predict: Clinical Deterioration, Malnutrition, Delirium and Falls. We will share how these tools are being leveraged at scale across a multi-hospital system to enhance patient safety, quality of care, and the patient experience.
Data science in combination with new tools help predict which patients will benefit most from health care interventions. Session contributors are representatives from medical organizations discussing various data science applications and their approaches to using data and predictive modeling to analyze and identify meaningful patterns that result in better patient outcomes.