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Area of Science:

  • Health Informatics
  • Public Health
  • Cancer Research

Background:

  • Evaluating cancer prevention programs necessitates linking sensitive health data from multiple sources.
  • Strict data protection regulations in Germany and Europe pose challenges for data linkage and analysis.
  • Existing methods often require individual consent, which is impractical for large-scale programs.

Purpose of the Study:

  • To develop a privacy-compliant method for evaluating the German mammography screening program without individual consent.
  • To facilitate mortality evaluation for over 10 million eligible women.
  • To ensure compliance with German data protection laws for health data analysis.

Main Methods:

  • A multi-center setup involving data owners, a data collection center (DCC), and an evaluation center (EC).
  • Irreversible encryption of record assignment numbers (RAN) and reversible encryption of evaluation data (EDAT).
  • Probabilistic record linkage by the DCC using RANs and a novel 'blinded anonymization' process for k-anonymity in EDAT.

Main Results:

  • A prototype was successfully tested with over 1.5 million simulated records.
  • The core processes demonstrated good performance.
  • Different data generalizations were created, and suppression rates were calculated.

Conclusions:

  • The developed method enables privacy-preserving data linkage for cancer screening program evaluation.
  • The approach is compliant with German data protection authorities.
  • Further improvements like l-diversity and automatic generalization computation are discussed for future applications.