title: Reducing patient re-identification risk for laboratory results within research datasets.
abstract: OBJECTIVE
  To try to lower patient re-identification risks for biomedical research databases containing laboratory test results while also minimizing changes in clinical data interpretation.
  
  
  METHODS
  In our threat model, an attacker obtains 5-7 laboratory results from one patient and uses them as a search key to discover the corresponding record in a de-identified biomedical research database. To test our models, the existing Vanderbilt TIME database of 8.5 million Safe Harbor de-identified laboratory results from 61 280 patients was used. The uniqueness of unaltered laboratory results in the dataset was examined, and then two data perturbation models were applied-simple random offsets and an expert-derived clinical meaning-preserving model. A rank-based re-identification algorithm to mimic an attack was used. The re-identification risk and the retention of clinical meaning for each model's perturbed laboratory results were assessed.
  
  
  RESULTS
  Differences in re-identification rates between the algorithms were small despite substantial divergence in altered clinical meaning. The expert algorithm maintained the clinical meaning of laboratory results better (affecting up to 4% of test results) than simple perturbation (affecting up to 26%).
  
  
  CONCLUSIONS
  With growing impetus for sharing clinical data for research, and in view of healthcare-related federal privacy regulation, methods to mitigate risks of re-identification are important. A practical, expert-derived perturbation algorithm that demonstrated potential utility was developed. Similar approaches might enable administrators to select data protection scheme parameters that meet their preferences in the trade-off between the protection of privacy and the retention of clinical meaning of shared data.
authors: Department of Biomedical Informatics, School of Medicine, Vanderbilt University, Nashville, TN 37232-8340, USA. ravi.v.atreya@vanderbilt.edu
authors: Ravi V
authors: RV
authors: Atreya
authors: Joshua C
authors: JC
authors: Smith
authors: Allison B
authors: AB
authors: McCoy
authors: Bradley
authors: B
authors: Malin
authors: Randolph A
authors: RA
authors: Miller
mesh_terms: D000465:Algorithms; D035843:Biomedical Research; D002984:Clinical Laboratory Information Systems; D016494:Computer Security; D003219:Confidentiality; D057286:Electronic Health Records; D005240:Feasibility Studies; D006801:Humans; D033181:Information Dissemination; D008498:Medical Record Linkage; D014481:United States