HIoTCoE Panel – IoT Across the Spectrum of Healthcare Delivery Systems

Abstract:

Everyone should leverage IoT to improve healthcare outcomes. But who’s “everyone” and how can they truly leverage IoT in meaningful ways? To truly harness the promise of IoT in healthcare, it’s critical to understand how data generated from these devices can be used by various industry stakeholders.
Enjoy a discussion from industry leaders from across the healthcare ecosystem—including analytics, telehealth, devices, and clinicians—as they discuss essential functionality of IoT devices, as well as the data generated from those devices.

Speakers:

Catherine (CJ) Robison, BSN, RN, is a Health Innovation Scientist at Oracle Health – Propelled by the belief that data, research and innovative solutions have the power to transform healthcare, CJ Robison has developed a diverse and extensive portfolio of expertise in the medical field. As a registered nurse with a degree in biology, CJ began her career on a medical-surgical floor that specializes in geriatric oncology. Following her time in direct patient care, she served as the Magnet Program Director and Manager of Professional Practice at Sentara Leigh Hospital in Virginia where she was instrumental in improving electronic workflows, running workload-acuity models and quantifying resources required to deliver care.  Following this effort, CJ went on to design and manage an array of process improvement initiatives across Sentara.  During the early days of the Pandemic, CJ led a region-wide COVID-mask-making initiative, managing over 1,000 volunteers. In three months, over 40,000 masks  were delivered to nearly 100 organizations throughout the Hampton Roads region. In her “free” time, CJ enjoys spending time with her three rambunctious children, reading extensively and riding horses.

Dr. Mark Wolff has over 25 years of experience in the health and life science industries as a scientist and analyst working in the U.S. and Europe. Mark joined SAS in 2005 and is an Advisory Industry Consultant and Chief Health and Life Science Analytics Strategist for the SAS Global IoT Division. Mark’s areas of expertise include the development and application of advanced and predictive analytics in healthcare and life sciences with a particular interest in outcomes and safety. Current work focuses on methods and application of Machine Learning to real time sensor/IoT data in support of outcomes and safety research, visualization and development of intelligent, decision support systems. Prior to joining SAS Mark held a variety of research and leadership positions in academia, government and industry. He holds a Bachelor of Science degree from Loyola College in Maryland, a Master of Science in Entomology and a Doctorate in Toxicology from North Carolina State University.

Ryan Hochworter is a Medical device and technology leader driving change in the nation’s leading health systems with data AI,ML, and IoMT. Designing connected solutions to improve patient care and shape the future of healthcare. Experienced healthcare sales leader with a demonstrated history of working in the medical device industry. Skilled in Business Development, Cloud, Data Center, Healthcare, Wireless Technologies, Optical Fiber, and Telecommunications. Strong sales professional with a Bachelor’s degree focused in International Business from University at Buffalo.

Dr. Craig Futterman is a pediatric cardiac intensivist and a medical informaticist. He has been practicing for 36 years. He wrote software for Inova Children’s Hospital for 24 years (and then they decide to get an electronic Health Record). He currently works in the Pediatric Cardiac intensive Care Unit at Children’s National Hospital in Washington DC. He is also a medical informaticist at Children’s National as well. He is an associate professor of pediatrics at the George Washington University His research is currently in the area of algorithm building (using machine learning) to predict negative outcomes and real-time visualization of critical care patient data in a new and different format.