Anonymizing Health Data
Case Studies and Methods to Get You Started
Publisher: O'Reilly Media
Final Release Date: December 2013
Pages: 228

With this practical book, you will learn proven methods for anonymizing health data to help your organization share meaningful datasets, without exposing patient identity. Leading experts Khaled El Emam and Luk Arbuckle walk you through a risk-based methodology, using case studies from their efforts to de-identify hundreds of datasets.

Clinical data is valuable for research and other types of analytics, but making it anonymous without compromising data quality is tricky. This book demonstrates techniques for handling different data types, based on the authors’ experiences with a maternal-child registry, inpatient discharge abstracts, health insurance claims, electronic medical record databases, and the World Trade Center disaster registry, among others.

  • Understand different methods for working with cross-sectional and longitudinal datasets
  • Assess the risk of adversaries who attempt to re-identify patients in anonymized datasets
  • Reduce the size and complexity of massive datasets without losing key information or jeopardizing privacy
  • Use methods to anonymize unstructured free-form text data
  • Minimize the risks inherent in geospatial data, without omitting critical location-based health information
  • Look at ways to anonymize coding information in health data
  • Learn the challenge of anonymously linking related datasets
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oreillyAnonymizing Health Data
 
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5.0

Protecting patient data

By Jaype

from Kenosha WI

Verified Reviewer

Pros

  • Concise
  • Easy to understand
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Expert
    • Intermediate

    Comments about oreilly Anonymizing Health Data:

    I recommend this book to anyone who works with patient health records. The authors describe their risk-based methodology to protect a patients privacy while still providing quality data for secondary use.

    The book is well written. It's easy to follow and the authors do a god job explaining their points.

    The first 2 chapters are the most important as they describe the methodology in detail. The rest of the book uses the same approach against real examples the authors have experienced.

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