This DIMACS tutorial will provide researchers, analysts and managers with an overview of the federal HIPAA Privacy regulations and an introduction to the principles and methods of statistical disclosure limitation that can be used to statistically de-identify healthcare data to meet the HIPAA privacy regulations.
This one and a half day tutorial will provide participants with a detailed overview of the HIPAA privacy regulations, theory and methods for statistical disclosure limitation, and applied examples of disclosure limitation methods. Participants completing the course should be able to:
Participants will learn about statistical disclosure for various data models (tabular data, microdata, social networks), but the primary focus will be on statistical disclosure for microdata in healthcare databases. While statistical disclosure theory will be covered in some detail, the course orientation will be practical and applied, focusing primarily on providing participants with the knowledge needed to understand the statistical de-identification process for healthcare datasets in accordance with the HIPAA privacy rule and to identify confidentiality problems of potential concern. Upon completion of the course, it is expected that participants would be able to work successfully with statistical disclosure experts providing HIPAA statistical de-identification certifications.
Participants will be provided with lecture slides, and classroom notes. The course will include computer-based presentations on conducting disclosure analyses and implementing disclosure control methods.