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Preserving temporal relations in clinical data while maintaining privacy.

George Hripcsak1, Parsa Mirhaji2, Alexander Fh Low3

  • 1Department of Biomedical Informatics, Columbia University Medical Center, New York, NY 10032, USA hripcsak@columbia.edu.

Journal of the American Medical Informatics Association : JAMIA
|March 26, 2016
PubMed
Summary
This summary is machine-generated.

Protecting patient privacy in research is crucial. Our new Shift and Truncate (SANT) method obscures date information, reducing re-identification risk in large observational studies.

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Area of Science:

  • Health Informatics
  • Data Privacy
  • Observational Research

Background:

  • Maintaining patient privacy is a significant challenge in large-scale observational research.
  • Publicly available data increases the risk of identifying study subjects.
  • Existing methods may not be robust to frequent data updates or inferring boundary dates.

Purpose of the Study:

  • To introduce a novel method for obscuring date information in clinical data.
  • To reduce the risk of re-identification for study subjects in observational research.
  • To comply with patient privacy regulations like HIPAA.

Main Methods:

  • The Shift and Truncate (SANT) method assigns a random shift value to each patient's dates.
  • All dates within a patient's record are shifted by this random amount.
  • Data are then truncated from the beginning and end of the dataset to a desired granularity.

Main Results:

  • The SANT method effectively obscures date information to a chosen level of granularity.
  • The approach is robust to frequent data updates and inferring boundary dates.
  • Temporal information finer than the specified granularity cannot be disclosed.

Conclusions:

  • The Shift and Truncate method is a valuable tool for enhancing patient privacy in research.
  • It offers a scientific approach to reduce re-identification risks under HIPAA.
  • This method may aid in qualifying data for Safe Harbor provisions.