Date: June 8th 2011 from 12pm to 1pm EST
Abstract: The case of Sorrell v. IMS Health Inc., currently under review by the Supreme Court, highlights a number of claims that are being increasingly made by the privacy community. The litigation challenges a Vermont law that would limit the dissemination and use of prescription drug data for marketing purposes. The prescription data identifies the prescribing physician and pharmacy, but does not identify the patient. Based on a number of examples, the claim has been made that prescription records can be easily re-identified, and therefore the information collected from the pharmacies is essentially personal health information being collected and disclosed without patient authorization.
In this webinar we examine this claim from a number of perspectives. We first explain current de-identification standards in the US and what role they play in the health data sharing ecosystem. This is followed by a critical summary of the evidence that currently exists on the re-identification risk from prescription records, and health records in general. From our analysis, we are able to draw some conclusions, based on current evidence, about the re-identification risks from properly de-identified health data in general, and prescription records specifically.
Attendees will be informed about the identifiability issues surrounding the Sorrell v IMS case, and develop an understanding and appreciation of the current evidence on the re-identification risk when health data is disclosed for secondary purposes (i.e., what can be justified and what cannot be).
Speakers: Daniel Barth-Jones, PhD, MPH, Assistant Professor of Clinical Epidemiology, Mailman School of Public Health, Columbia University;
Khaled El-Emam, PhD, Canada Research Chair in Electronic Health Information, Associate Professor, Faculty of Medicine and the School of Information Technology and Engineering, University of Ottawa
Jane Yakowitz, JD, Visiting Assistant Professor, Brooklyn Law School
Biography: Dr. Daniel C. Barth-Jones is an Assistant Professor of Clinical Epidemiology at the Mailman School of Public Health at Columbia University in New York and an Adjunct Assistant Professor and Epidemiologist at the Wayne State University School of Medicine in Detroit, Michigan. Dr. Barth-Jones received both his Master of Public Health and Ph.D. degree in Epidemiology from the University of Michigan. Dr. Barth-Jones’ work on statistical disclosure science has focused the importance of properly balancing two vital public policy goals: effectively protecting individual’s privacy and preserving the scientific accuracy of statistical and geo-statistical analyses conducted with de-identified health data. He has authored several peer-reviewed publications and a book chapter on statistical disclosure assessment and control. His interests include statistical disclosure analyses/control methods for statistical de-identification of healthcare data, and geospatial and statistical modeling in epidemiology. He also maintains an active research agenda in the areas of theoretical population vaccinology, infectious disease epidemic modeling and simulation, and health economic evaluations of public health policies for vaccination and preventative intervention programs
Dr. Khaled El Emam is an Associate Professor at the University of Ottawa, Faculty of Medicine, 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 and secure disease surveillance for public health purposes. 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 and2004, 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 2002and 2005. He holds a Ph.D. from the Department of Electrical and Electronics, King’s College, at the University of London (UK).
Jane Yakowitz is a visiting Assistant Professor at Brooklyn Law School. She received a B.S. in mathematics and a J.D. from Yale. Her research interests include privacy law, the legal profession, and empirical legal studies. She previously served as the Director of Project SEAPHE (Scale and Effects of Admissions Preferences in Higher Education) at UCLA School of Law, where she conducted peer-reviewed research on admissions, academic performance, and labour outcomes for law school applicants. Professor Yakowitz has negotiated complex public records disclosures and has prepared large de-identified databases for public research use. These experiences inform her research on data privacy law. In her recent article (forthcoming in the Harvard Journal of Law & Technology), Professor Yakowitz argues that the risk of re-identification from properly anonymized research data is trivial, and easily outweighed by the social utility of freely accessible data.
More on the Sorrel vs. IMS case here. [Cornel Law]