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Understanding Optimal De-identification Methods

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Demand to share sensitive data for secondary use is constantly increasing. Healthcare organizations are facing increased pressure to make their data available, however, they may not be strategically aligned to avoid the inherent risks. With so many options available, it is easy to over rely on simplistic methods that may hinder the data’s use.

There are a number of different options available when it comes to sharing sensitive data. Join Privacy Analytics’ Pamela Buffone as she discusses the various de-identification methods available today and when it is best to apply these techniques. Some of these methods include:

  • Differential privacy
  • Pseudonymization
  • Tokenization
  • Data masking
  • K-anonymity
  • Risk-based anonymization

Understanding the differences between these de-identification methods is key to optimally leveraging data for secondary purposes. Not only will this webinar provide an overview of these practices, but also include recommendations based on industry best practices and standards emerging from regulators. Fill in the form on the right to watch, Understanding Optimal De-identification Methods, and learn more.

The post Understanding Optimal De-identification Methods appeared first on Privacy Analytics.


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