2016 Gibbons Lectures:

Medical Applications of Information Technology

Speaker:
Professor Jim Warren, Professor of Health Informatics, Department of Computer, University of Auckland

It has been suggested that more could be done to improve human health by better delivering what we already know than by developing further medical knowledge. There are enormous gaps in health delivery, particularly for long-term (chronic) conditions. These gaps include inadequate detection of individuals at high risk of developing chronic conditions and both health provider and health consumer mismanagement of risk factors once they are identified. After a chronic condition has become manifest, deficiencies in management continue. IT can help through use of decision support systems that compute estimates of risk and recommend evidence-based management. IT can also serve to make screening for risk factors more systematic , and consumers can receive direct 'eTherapy' for problems such as anxiety or to aid in quitting smoking. Further, analysis of large collections of health systems data can serve both to tune decision models and to identify segments of the population most in need of attention.

Jim Warren is Professor of Health Informatics at the University of Auckland. He has a BSc in Computer Science and a PhD in Information Systems from the University of Maryland. He has worked at the University of South Australia where he was the director of their Health Informatics Laboratory. He has been at the University of Auckland since 2005.

Based in the Department of Computer Science, Professor Warren works closely with the University's School of Population Health and National Institute for Health Innovation. In 2008-2010 he served a term as Chair of Health Informatics New Zealand, the member body of the International Medical Informatics Association for New Zealanders. He is also a founding Fellow of the Australasian College of Health Informatics. Jim's primary research interest is in IT for chronic condition management, whether this is through improved `business intelligence' (or data mining), clinical decision support tools for health providers, or information systems to better empower health consumers. He has been interested in the question of how to get useful clinical quality improvement information out of general practice electronic medical records since the early 1990s.