Workshop
Monday, March 30, 2015 in San Francisco
Full-day: 9:00am - 4:30pm
Workshop sponsored by:
Predictive Analytics in Healthcare: Techniques,
Opportunities, and Challenges in
Changing the Way We Deliver Healthcare
Intended Audience:
- Analysts, Students, CEO's and CIO's of Hospitals and Medical Clinics, Doctors, Nurses, and Medical Administrators and Technical Managers: Analysts who would like a tangible introduction to predictive analytics or who would like to experience analytics using a state-of-the-art data mining software tool.
- Anyone who would like an introduction to the use of predictive analytics in medical settings, and would like to experience doing a modeling exercise in a laboratory format learning a state-of-the-art Predictive Analytic software tool.
Knowledge Level: Beginner through advanced. For the beginner this workshop takes them through a healthcare modeling exercise from start to finish without any required prior training. For the advanced student this workshop will teach where predictive analytics is being used in healthcare, techniques used, and challenges that are faced. This workshop is for anyone interested in learning about the "Re-engineering of Medical / Healthcare Delivery".
Workshop Description
Attendees will learn several things in this workshop:
- Historical background of the development of healthcare delivery and current challenges.
- How to increase quality of care, prevent adverse events, and decrease costs using predictive analytics.
- The role of predictive analytics in Personalized Medicine and Genomics.
- How to use predictive analytics software and build your own models - each attendee will use their own laptop, with software provided by the instructors, to work through a modeling problem
- The future of medicine – innovations and challenges.
Participant background
In addition to historical background and theory that will be presented, this is a hands-on workshop where all participants will be actively involved, and thus will work independently or in a small team throughout the day. The instructors and 'Technical Assistants' (that will roam around the classroom) will individually assist all attendees in understanding and use of both software and modeling issues throughout the day.
Software
Most concepts covered are applicable to all predictive analytics and decisioning projects - regardless of the particular software employed. The software to be used for this workshop is Dell Statistica (which offers a complete 'end-to-end' solution).
Hardware: Bring Your Own Laptop
Each workshop participant is required to bring their own laptop running Windows. Instructions will be provided to install a trial license for the analytics software used during this training program, and will also be workable for a period of time beyond this workshop.
Attendees receive a special "HEALTHCARE – PREDICTIVE ANLAYTICS & DECISIONING for MEDICINE' course workbook and an official certificate of completion at the conclusion of the workshop.
Schedule
- Software installation a 8:00 am
- Workshop program starts at 8:30 am
- Morning Coffee Break at 10:30 - 11:00am
- Lunch provided at 12:30 - 1:15pm
- Afternoon Coffee Break at 3:00 – 3:30 pm
- End of the Workshop: 5:00 pm
Instructors
Nephi Walton, M.D. (M.S. in Bioinformatics):
Nephi Walton earned his MD from the University of Utah School of Medicine and a Masters degree in Biomedical Informatics from the University of Utah Department of Biomedical Informatics where he was a National Library of Medicine fellow. His Masters work was focused on data mining and predictive analytics of viral epidemics and their impact on hospitals. He was the winner of the 2009 AMIA Data Mining Competition and has published papers and co-authored books on data mining and predictive analytics. Also during his time at the University of Utah he spent several years studying genetic epidemiology of autoimmune disease and the application of analytical methods to determining genetic risk for disease, a work that continues today. His work has included several interactive medical education products. He founded a company called BrainSpin that continues this work and has won international awards for innovative design in this area. He is currently a combined Pediatrics/Genetics fellow at Washington University where he is pursuing several research interests including the application of predictive analytics models to genomic data and integration of genomic data into the medical record. He continues to work with the University of Utah and Intermountain Healthcare to further his work in viral prediction models and hospital census prediction and resource allocation models.
Linda A. Winters-Miner, Ph.D. Professor Emeritus of SU; Adjunct Professor at UC-I and UCSD teaching PA of MEDICINE courses
Linda Winters-Miner was trained in Curriculum Design and Educational Statistics, obtaining her Ph.D. from the University of Minnesota. Academic training also included a 2 year NIH – Post-Doctoral Fellowship in MPH/Psychiatric Epidemiology program at the University of Iowa. She has taught in public elementary schools, taught in university settings where she has supervised student teachers, was a consultant in Social Studies for Boise Public Schools, was an Examiner for the Oklahoma Quality Foundation Award, a Coordinator for a Drug Research Protocol for Alzheimer’s for Parke Davis Pharmaceutical Company, and serves on the editorial board for The Journal of Geriatric Psychiatry and Neurology, Sage Publications. She co-authored two books on Alzheimer’s Disease, including Familial Alzheimer’s Disease: Molecular Genetics and Clinical Perspectives (Dekker pub). For 22 years she served as Professor and Director of Academic Programs for Southern Nazarene University – Tulsa adult studies programs for graduate and undergraduate programs in psychology and business, including an MBA in Healthcare Administration. For over ten years she served as an IHI Faculty Member for Second Year Medical Residents, In His Image Residency Program in Tulsa, OK, where she oversaw the design, execution, and data analysis for the residents’ 2nd year medical research projects. She is a Founding Editor of an On-Line Journal called: Innovation & Empowerment: Southern Nazarene University-Tulsa Research Journal,is a member of the ISI ASTROSTATISTICS NETWORK . Linda is the author of the tutorials in the following two Predictive Analytics books: “Handbook of Statistical Analysis & Data Mining Applications” (Academic Press, 2009), and “Practical Text Mining” (Academic Press, 2012). She engaged both her SNU-TULSA university students and her 2nd year medical residents in Predictive Analytics [Data Mining and Text Mining]. Linda is a lead-author and wrote 40% of the 2015 book: Practical Predictive Analytics and Decisioning Systems for Medicine, 2015, Elsevier / ACADEMIC PRESS, publisher.
Derek Walton, Vice President of Closis:
Derek Walton is the president of BrainSpin, and Vice President of Closis.
He specializes in business development, business management, branding strategies, and industry networking initiatives in consumer business environments and has been involved in the creation of innovative tools for healthcare and marketing. He has used analytics in marketing, the gaming industry, sales, and other fields. He organizes training sessions and course development for CLOSIS providing vertical training solutions for analytics problems in many industries.
