Opportunities around Transactional Medical Records with Application to Chronic Condition Management

Speaker: Jim Warren

Affiliation: Chair in Health Informatics, National Institute for Health Innovation (NIHI), University of Auckland

Time: Monday 10/01/2011 from 14:00 to 15:00

Venue: Access Grid UWS. Presented from Campbelltown (26.1.50), accessible from Parramatta (EB.1.32) and Penrith (Y239).

Abstract: Data that is recorded as part of the operation of healthcare per se is a fantastic resource to apply for quality improvement in healthcare delivery. Prescribing and laboratory test results are two of the best elements to use as these are objective and functional (as compared to, say, the notation of a problem or symptom). These data are recorded as acts at points in time, however, which leaves the problem of inferring the bigger picture. For example, one instance of an antihypertenisive prescription can imply hypertension (although not always reliably), and a clinical decision to pursue lifelong pharmacological management (unless heroic lifestyle changes are made by the patient).

The talk overviews NIHI research on analysis of electronic health record (EHR) data, particularly recent examination of general practice records around treatment of hypertension. We will show how the findings highlight problems and opportunities around medication adherence, and look at the broader issues and applications for inference from EHR data in chronic condition management.

Biography: Jim Warren is Professor of Health Informatics at the University of Auckland. Based in the Department of Computer Science, he 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 in their own care. 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, and increasingly he finds that gaps in supply of long-term medications, such as blood pressure medication, provide a particularly fruitful area of focus.