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J Am Med Inform Assoc. 2016 Nov;23(6):1040-1045. doi: 10.1093/jamia/ocw001. Epub 2016 Mar 24.

Preserving temporal relations in clinical data while maintaining privacy.

Author information

  • 1Department of Biomedical Informatics, Columbia University Medical Center, New York, NY 10032, USA
  • 2Montefiore Medical Center/Albert Einstein College of Medicine, Bronx, New York, NY 10461, USA.
  • 3Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY 10065, USA.
  • 4Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN 37203, USA.
  • 5Department of Electrical Engineering and Computer Science, School of Engineering, Vanderbilt University, Nashville, TN 37203, USA.



Maintaining patient privacy is a challenge in large-scale observational research. To assist in reducing the risk of identifying study subjects through publicly available data, we introduce a method for obscuring date information for clinical events and patient characteristics.


The method, which we call Shift and Truncate (SANT), obscures date information to any desired granularity. Shift and Truncate first assigns each patient a random shift value, such that all dates in that patient's record are shifted by that amount. Data are then truncated from the beginning and end of the data set.


The data set can be proven to not disclose temporal information finer than the chosen granularity. Unlike previous strategies such as a simple shift, it remains robust to frequent - even daily - updates and robust to inferring dates at the beginning and end of date-shifted data sets. Time-of-day may be retained or obscured, depending on the goal and anticipated knowledge of the data recipient.


The method can be useful as a scientific approach for reducing re-identification risk under the Privacy Rule of the Health Insurance Portability and Accountability Act and may contribute to qualification for the Safe Harbor implementation.

[Available on 2017-11-01]
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