April 5, 2019
8:30 am – noon
Research Triangle Foundation
Topics & Speakers:
AI vs. Machine Learning vs. Cognitive Computing (Greg Nelson, Vidant Health) l PDF
The language of data science has become commonplace in boardrooms and waiting rooms with terms like Big Data, Machine Learning, Artificial Intelligence, Cognitive Computing, NLP & Text Analytics and Deep Learning. But do we know what they mean? Moreover, can we explain these concepts clearly and translate the value to our organizations? As healthcare leaders, we need to not only comprehend, but also explain how we can benefit from these approaches to problem-solving and automation in simple, easily-understood terms.
Promoting Precision Medicine with a Facilitated Network (Marshall Ruffin, Progknowse) l PDF
Health care systems have the data to predict the future for patients far more accurately than we imagine. These predictions are at the heart of precision medicine. Precision medicine involves two relatively new scientific disciplines – genetics and machine learning. Learn how health care systems can use their electronic medical records and genomic test results about their patients to practice state-of-the-art precision medicine to improve patient care and patients’ understanding of their conditions.
AI is More than Buzz: Practical Applications in Healthcare (Jennifer Schaff & Daniel Brannock, Elder Research) l PDF
The adoption of artificial intelligence (AI) is transforming all aspects of healthcare, rapidly improving healthcare quality and reducing associated costs. An important property of machine learning is that many approaches useful for one industry can be repurposed for others – including healthcare. Elder Research will present how example techniques borrowed from the Consumer Packaged Goods (CPG) industry can be used to estimate the financial risk of a patient as well as increase patient’s propensity to pay their bills. Attendees will also learn how to use analytic techniques to seek out exemplary providers, predict disease, and identify potential addiction. We will reveal the importance of developing a data governance plan to diminish daunting data deficiencies, and how quick wins, proof of concepts, and project goals fall into place when a plan and defined procedures are put into place.
An Examination of Real-World Advanced Analytics Use Cases (Heather Hallett & Matthew Schirmer, SAS) l PDF
It is impossible to think about the future of healthcare without encountering those two pixilated vowels — AI — that not only can make us slightly crazed, but can simultaneously make us feel enthusiastic, challenged and empowered. The presenters will discuss analytic maturity and how advanced analytics is being applied to clinical practice to improve quality, efficiency and satisfaction through an examination of real-world use cases. Learn how different technologies are being combined to support those specific use cases, and how health care organizations are manifesting insights in to clinical workflows. Finally, learn how innovations from other industries are being translated to healthcare.
Daniel Brannock, MS brings a background in the natural sciences to his analysis work at Elder Research. He earned an MS in Analytics from NC State University where his practicum with UNC Health Care focused on using electronic health records to predict diabetic patient outcomes. He has spent the last three years applying data science to a broad array of problems and industries. Daniel earned a degree in Chemistry from the University of North Carolina and worked in the pharmaceutical industry for three years prior to seeking his master’s degree. His experience includes ingesting public CMS data to build a graph network and using clinical data to model disease events.
Heather Hallett, RN, MBA is Principal Industry Consultant for SAS. She has over 25 years of experience, ten in direct patient care and 15 in informatics. She has extensive experience working with end users and is educated in the principles of Lean Healthcare. Prior to joining SAS, she worked for a Health Information Exchange vendor, which enabled her to become expert in the types of data generated by clinical systems, principles of clinical data exchange and aggregation and analysis of data for purposes of clinical transformation. She holds a BS in Nursing, a BA in Psychology and a Masters in Health Care Administration.
Greg Nelson, MMCi, CPHIMS is the Vice President for Analytics and Strategy at Vidant Health. Prior to this, he was the founder and Chief Executive Officer of ThotWave, an analytics advisory firm specializing in healthcare analytics. Greg serves as an expert for the International Institute for Analytics and adjunct faculty at Duke University’s Fuqua School of Business. He teaches analytics in both the School of Nursing and at the Fuqua School of Business at Duke University. He earned his bachelor’s degree in Psychology from the University of California-Santa Cruz and Masters of Management in Clinical Informatics from Duke University.
Marshall Ruffin, Jr., MD, MPH, MBA is CEO of Progknowse, a firm developing machine learning algorithms for private and governmental health systems. He previously served as Executive VP and CTO for Inova Health System, and CTO and Health Information Officer for the University of Virginia Medical Center. He is a board-certified general internist, with experience public health, business management, information systems, informatics and predictive analytics. He earned his medical degree from Harvard Medical School, MPH from UNC-Chapel Hill, and MBA from Stanford University Graduate School of Business.
Jennifer Schaff, PhD, MS is a data scientist and Managing Director of Elder Research’s Raleigh office. Since joining Elder Research, she has led teams and applied analytics on many different projects, including improving clinical outcomes, provider assessments, and predicting disease in healthcare as well as marketing, promotions, and trade in the CPG industry. In her previous role, Jennifer directed the Genomics Lab for North Carolina State University where her passion for keeping abreast of innovative technologies and techniques led to annual revenue growth and the service of hundreds of academic and industry based laboratories across the world. She holds a PhD in Plant Pathology and an MS in Analytics.
Matthew Schirmer is a Consulting Manager at SAS and has supported the development of analytic services for the North Carolina Health Information Exchange since its inception. He has over 20 years of experience working with healthcare organizations on quality measurement reporting, cost and utilization analytics, as well as predictive modeling to support care management activities. He received his undergraduate degree from Vanderbilt University and a Masters in Social Work from Portland State University.
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