DIMACS Tutorial: Statistical De-identification of Confidential Health Data with Application to the HIPAA Privacy Regulations

April 30 - May 1, 2009
DIMACS Center, CoRE Building, Rutgers University

Daniel Barth-Jones, Columbia University, db2431 at columbia.edu
Alina Campan, Northern Kentucky University, campana1 at nku.edu
Traian Marius Truta, Northern Kentucky University, trutat1 at nku.edu
Presented under the auspices of the Special Focus on Computational and Mathematical Epidemiology and the Special Focus on Communication Security and Information Privacy.

Call for Participation:

Researchers (epidemiologists, biostatisticians, medical informatics and health systems scientists, etc.), analytic professionals (from business, marketing, pharmaceutical industry, etc.) and the privacy officers/managers who supervise such staff will benefit from this short course. Technical and management personnel in the pharmaceutical and healthcare information industries will find the course particularly useful. Participants with some prior background in mathematics, statistics, and data/information management will find this course most useful. Knowledge of SAS statistical software will be helpful for following the in-class computer instruction, but participants with experience in other statistical packages should also be able to follow the statistical disclosure analyses examples.

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Document last modified on July 31, 2008.