Data De-Identification Toolkit

Aaron Kite-Powell, Kelly Moran


Developing effective data-driven algorithms and visualizations for disease surveillance hinges on the ability to provide application developers with realistic data. However, the sensitivity of the data creates a barrier to its distribution. We have created a tool that assists data providers with de-identifying their data in preparation for sharing. The functions in the tool help data providers comply with the HIPAA "Safe Harbor" de-identification standard [1] by removing or obscuring information such as names, geographic locations, and identifying numbers.

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Online Journal of Public Health Informatics * ISSN 1947-2579 *