A Health Informatics Short Course presented and cosponsored by the Center for Quantitative Medicine and the CICATS Division of Biomedical Informatics.
Data is growing in healthcare and rapidly accumulating clinical information can improve patient care and support knowledge discovery. Eighty percent of clinically relevant data is currently unused, however. To fully harness the potential of clinical information, informatics is needed to enable comparative effectiveness and translational research. Such research requires electronic health record derived structured data linked with supplemental sources to provide patient-level information that can be aggregated and analyzed to support hypothesis generation, comparative assessment, and personalized care.
This intensive short course examines the unique characteristics of clinical and life sciences data including the analytic principles, methods and tools for translating health data and information into actionable knowledge for improved health care.
Date: Thursday, June 26, 2014
Time: 1 – 5 p.m.
Location: Center for Quantitative Medicine, 195 Farmington Avenue, Suite 210
$100.00 – Student Registration (copy of valid student ID required with your registration)
$200.00 – Early Bird (postmarked by May 30, 2014)
$250.00 – Advance (by June 19, 2014)
To ensure individualized attention, space is limited to 15 participants on a first-come, first-served basis. Save money and register early to guarantee your seat with our early bird rates. If you wish to pay by Visa®, MasterCard® or Discover® card, you may register by calling UConnLink at 860-679-7692 or 1-800-535-6232, otherwise mail your completed registration with a check made payable to the “UConn Health Center” to the address listed on the registration form. UConn departments may also pay by submitting a transfer voucher. Advanced registration only. No onsite walk-in registrations will be allowed.
At the end of the course, participants will be able to:
- Identify and characterize different types of medical data and coding standards.
- Describe informatics frameworks and tools that enable clinical researchers to use existing clinical data for clinical and translational research
- Discuss the principles and applications of data analytical methods (i.e., information retrieval, natural language processing, and big data/text mining).
- Develop foundational concepts of clinical data analysis and analytical thinking that are instrumental in solving problems in translational research.
Who Should Attend?
This short course is aimed at junior and senior researchers, faculty, postdoctoral fellows, graduate students, research assistants and associates, and clinicians who conduct clinical or translational research or who are interested in health informatics.
All registrations are confirmed in writing. If you don’t receive a confirmation, call 860-679-3075.
Registration includes a $50.00 nonrefundable registration fee. Should you cancel your registration before June 19, 2014, you will be refunded the entire short course fee less $50. Sorry no refunds after June 19, 2014.
Business casual attire is suggested. Since meeting room temperatures and personal comfort levels vary, it is recommended that you dress in layers and bring a sweater or jacket.
Directions to 195 Farmington Avenue
From I-84 East or West, Take Exit 39 (if coming from I-84 West, Exit 39 is after 39A). Turn right at the first traffic light onto Route 4 East (Farmington Avenue). At the fifth traffic light, turn right to enter the 195 Farmington Avenue complex which is adjacent to the UConn Health campus. The Center for Quantitative Medicine office is in Suite 210.
UConn Health is on Connecticut Transit (CTTRANSIT) bus routes 66F, 66H, and 66T. For current weekday and weekend schedules, call CTTRANSIT at 860-525-9181 or visit their website at http://www.cttransit.com.
Ample, convenient free parking is available in the lot immediately outside the center’s offices.
For Further Information
Matthew J. Cook, M.P.H., M.B.I.
Director, Education & Outreach
Center for Quantitative Medicine
263 Farmington Avenue, MC 6029
Farmington, CT 06030-6029
William Yasnoff, M.D., Ph.D., FACMI
Dr. Yasnoff is director of the division of biomedical informatics at UConn Health, adjunct professor of health sciences informatics at Johns Hopkins, a nationally recognized health informatics consultant, and a fellow of the American College of Medical Informatics. He initiated and organized the activities at the U.S. Department of Health and Human Services leading to the President’s establishment of the Office of National Coordinator for Health Information Technology in 2004. Earlier, he developed and implemented the nation’s first state immunization registry. He earned his Ph.D. in computer science and M.D. from Northwestern, has served as faculty for numerous informatics courses, and is the author of multiple textbook chapters.
Xiaoyan Wang, Ph.D.
Xiaoyan Wang, Ph.D. is an assistant professor at UConn Health. Her primary research areas include electronic health records (EHRs), natural language processing (NLP), text mining, clinical data integration analysis, and knowledge discovery from big data. Dr. Wang developed the first framework of quantitative pharmacovigilance using NLP, informatics and statistics on EHRs to detect novel adverse drug events. She received her doctorate in biomedical informatics at Columbia University.
Fei Wang, Ph.D.
Fei Wang, Ph.D. is a member of the research staff in the Healthcare Analytics Group at IBM’s TJ Watson Research Center. He has published over 100 papers in the data mining and analytics fields. His research interests are in data mining, machine learning algorithms and their applications in health informatics. Dr. Wang’s work on patient similarity evaluation with EHRs has been the fundamental technique for the IBM’s first healthcare software product — IBM Patient Care and Insights. He earned his Ph.D. degree in Automation from Tsinghua University.
Matthew J. Cook, M.P.H., M.B.I.
Matthew J. Cook, M.P.H., M.B.I. is a university director of research IT and informatics within the Office of the CIO and director of education and outreach for the Center for Quantitative Medicine (CQM) at UConn Health. He earned his M.P.H. degree at UConn and his master’s degree in biomedical informatics from Oregon Health and Sciences University.
Michael Blechner, M.D.
Dr. Blechner is an academic informatician and Assistant Professor of Pathology and Laboratory Medicine at UConn Health. He earned his medical degree at Dartmouth Medical School, completed his residency at Hartford Hospital and a two-year fellowship in medical informatics at Brigham and Women’s Hospital, Harvard Medical School and MIT. Dr. Blechner currently serves as the director of Pathology Informatics and Transfusion Medicine at the Health Center and conducts research in clinical informatics. He also teaches biomedical informatics to UConn medical students, residents and graduate students.