Boston, MA
Oct. 22-23, 2018
Executive Director, B&CI Information Services
Grady Health System

Robin Frady is a dynamic analytics and technology practitioner with expertise in data translation to drive meaningful clinical and operational action. In her role at Grady Memorial Hospital (Grady), Robin leads a diverse team of professionals focused on the implementation of transformative technologies. She has built a roadmap that streamlines reporting, increases self-service reporting and analytics, assesses data quality, and drives the applicable use of AI for the organization. This includes spearheading the integration of Grady's AI machine, which enables improvements in patient outcomes, reduces costs, and drives operational value for the organization. Robin is also instrumental in developing pioneering change management and engagement strategies that align to and enable emerging IT solutions.
Prior to joining Grady, Robin built and deployed new segmentation capabilities for both Coca Cola and the American Cancer Society.

October 23, 2018
12:15pm - 12:45pm
America Ballroom

As Atlanta’s preeminent safety net hospital, Grady Memorial Hospital is an essential resource for many who otherwise would have little to no access to medical services. In an attempt to lower rates of patient illness, complications, and deliver personalized care, a little over a year ago the hospital incorporated artificial intelligence with the system’s mobile integrated health program.

The results have been impressive: Grady has seen a 10% decrease in readmissions for the targeted population and saved almost $700,000 in direct costs - a greater than 500% return on the program. Additionally, included within the intelligence of the machine are the socioeconomic factors such as literacy, income, access to transportation, and proximity to a food desert that drive more than half a patient’s risk.

In this session, among other things, attendees will learn how Grady has integrated AI to prioritize patient visits and to identify:

Key Takeaways:

  • The clinical, behavioral, and socioeconomic factors contributing to the risk of a re-hospitalization.
  • The actions that will best reduce risk while ensuring patient engagement. 
  • Opportunities for AI application across hospital clinical operations.

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