Leveraging Simulation + Machine Learning to Support Patient Flow and Space Planning Decision Making at UF Health

In 2024, UF Health embarked on a journey to build a system-wide Patient Flow Center. As part of this effort, the team built out a Digital Twin of their Gainesville hospital in FutureFlow Rx, a BigBear.ai product that provides accurate census and flow predictions based on discrete event simulation and machine learning technologies.

Throughout 2024 and 2025, the UF Health and BigBear.ai teams collaborated to integrate this technology into their Patient Flow Center. FutureFlow Rx allowed the UF team to improve their decision-making process by having improved census predictions in a central location. Also, the team leveraged FutureFlow Rx to run scenarios to test various construction plans and patient placement changes before implementing. This provided a low-risk environment to understand the impact of such changes on patient mix, boarders, staffing, and more. 

This presentation will detail this journey and highlight lessons learned and results. 

Attendees will learn the best practices and lessons learned regarding the technology implementation. These skills can be translated to other technology implementations.

Identify their own situations/problems that are good candidates for simulation. Simulation is a valuable tool that is not always utilized. Attendees will learn about what types of problems are good candidates for simulation.

Authors

Ashley Benedict is the Chief Project Management Officer for the UF Health Information Technology Department. Her previous job was as Improvement and Innovation Program Coordinator for the VA Sunshine Healthcare Network.  She received her BS and MEng degrees in Industrial and Systems Engineering from the University of Florida and her Ph.D. in Industrial Engineering from Purdue University. Ashley is a Past President of the Society for Health Systems (SHS), an SHS Diplomate, and the 2023 Healthcare Systems Process Improvement Conference chair. Ashley enjoys paddle boarding, traveling, and reading in her free time.

Erica is currently a Healthcare Data Engineer at BigBear.ai. She works with healthcare systems to implement and maximize value using simulation and machine learning solutions. She has prior experience as a Process Improvement professional at Inova Health System. She also applied her industrial engineering skillset as a Manufacturing Engineer at GE Healthcare. Erica graduated from Ohio State University with a B.S. in Industrial and Systems Engineering and has a Masters in Supply Chain Management. She currently resides near Baltimore, MD. 

As a Healthcare Data Engineer at BigBear.ai, Heather helps healthcare systems maximize value from their Electronic Health Record data through integration with simulation and machine learning solutions. Previously, she supported clinical reseach and quality improvement efforts at the Johns Hopkins University School of Medicine in areas of EHR data extraction, analysis, and governance. She holds a M.S. in Information Systems Engineering from Johns Hopkins Whiting School of Engineering and a B.S. in Psychology from Stevenson University. Heather currently resides in Baltimore, MD.