Date: April 28th 2010 from 12pm to 1pm EST
Abstract: Reading media reports recently one may get the impression that it has become easier to re-identify data sets. Such a view is based on a small number of analyses of re-identification attempts and cases. This presentation provides a detailed critical appraisal of the evidence supporting such claims. Our focus will be on the re-identification of clinical data sets. Our appraisal shows that the claims on the re-identification of clinical data being rampant and easy are severely exaggerated, and that there is no evidential support for them. We present a pragmatic model for reasoning about re-identification risk and show how it can be used to decide when sufficient de-identification has been applied given the prevailing risks for a particular data use or disclosure.
Speaker: Khaled El Emam, CHEO Research Institute
Biography: Khaled is an Associate Professor at the University of Ottawa, Faculty of Medicine and the School of Information Technology and Engineering, a senior investigator at the Children’s Hospital of Eastern Ontario Research Institute, and a Canada Research Chair in Electronic Health Information at the University of Ottawa. His main area of research is developing techniques for health data anonymization. Previously Khaled was a Senior Research Officer at the National Research Council of Canada, and prior to that he was head of the Quantitative Methods Group at the Fraunhofer Institute in Kaiserslautern, Germany. He has (co)-founded two companies to commercialize the results of his research work. In 2003 and 2004, he was ranked as the top systems and software engineering scholar worldwide by the Journal of Systems and Software based on his research on measurement and quality evaluation and improvement, and ranked second in 2002 and 2005. He holds a Ph.D. from the Department of Electrical and Electronics, King’s College, at the University of London (UK).