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Related Experiment Video

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Privacy preserving interactive record linkage (PPIRL).

Hye-Chung Kum1, Ashok Krishnamurthy, Ashwin Machanavajjhala

  • 1Population Informatics Research Group, Department of Computer Science, UNC-CH & Department of Health Policy and Management, Texas A&M Health Science Center, USA.

Journal of the American Medical Informatics Association : JAMIA
|November 9, 2013
PubMed
Summary
This summary is machine-generated.

Integrating big data requires careful record linkage. A human-machine hybrid system enhances privacy-preserving record linkage (PPIRL) by combining computer platforms with human oversight, improving both data utility and privacy.

Keywords:
Electronic Health Records (EHR)decoupled dataentity resolutionmedical record linkageprivacyprivacy preserving interactive record linkage (PPIRL)

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Area of Science:

  • Biomedical Informatics
  • Computer Science
  • Data Science

Background:

  • Record linkage is crucial for integrating disparate databases in Big Data biomedical research.
  • Balancing data privacy with linkage quality necessitates hybrid human-machine systems to manage data uncertainty.
  • Existing private record linkage methods often assume a known linkage function, which is rare in practice.

Purpose of the Study:

  • To formalize a new framework for privacy-preserving interactive record linkage (PPIRL).
  • To analyze existing literature using the developed PPIRL framework.
  • To evaluate the effectiveness of a computer-based third-party linkage platform.

Main Methods:

  • Synthesizing computer science literature on private record linkage.
  • Developing a formal framework for PPIRL with defined privacy and utility properties.
  • Analyzing Secure Decoupled Linkage (SDLink) platform features: encryption, obfuscation, and minimum information disclosure.

Main Results:

  • A novel framework for PPIRL was established, enabling tractable analysis of privacy and utility.
  • The analysis of literature through this framework provides insights into current practices.
  • The SDLink platform demonstrates a flexible, computerized approach to third-party linkage.

Conclusions:

  • Human-based third-party linkage centers are the international standard for privacy-preserving record linkage.
  • A computer-based third-party platform with micro-level disclosure control and frequent human interaction offers significant improvements.
  • This human-machine hybrid system enhances both privacy and utility compared to traditional linkage center models.