SpecificationReferences

References

Specification v3.4.0, section References

The following peer-reviewed and government sources provide empirically validated collision probabilities:

  1. Zech J, Husk G, Moore T, Shapiro JS. “Measuring the Degree of Unmatched Patient Records in a Health Information Exchange Using Exact Matching.” Applied Clinical Informatics. 2016;7(2):330-340. — Collision rates from 85 million records in the Social Security Death Master File. https://pmc.ncbi.nlm.nih.gov/articles/PMC4941843/
  2. Sweeney L. “Simple Demographics Often Identify People Uniquely.” Carnegie Mellon University, Data Privacy Working Paper 3. 2000. — Population uniqueness from U.S. Census data. https://dataprivacylab.org/projects/identifiability/paper1.pdf
  3. Golle P. “Revisiting the Uniqueness of Simple Demographics in the US Population.” ACM Workshop on Privacy in Electronic Society (WPES ’06). 2006. — Revised uniqueness estimates with 2000 Census methodology. https://doi.org/10.1145/1179601.1179615
  4. Fellegi IP, Sunter AB. “A Theory for Record Linkage.” Journal of the American Statistical Association. 1969;64(328):1183-1210. — Theoretical framework establishing per-field collision probability (u-probability). https://doi.org/10.1080/01621459.1969.10501049
  5. Sayers A, Ben-Shlomo Y, Blom AW, Steele F. “Probabilistic record linkage.” International Journal of Epidemiology. 2016;45(3):954-964. — Review of u-probability estimation methodology. https://pmc.ncbi.nlm.nih.gov/articles/PMC5005943/
  6. Winkler WE. “Overview of Record Linkage and Current Research Problems.” U.S. Census Bureau Research Report Series (Statistics #2006-2). 2006. — Census Bureau methodology for estimating collision probabilities. https://www.census.gov/content/dam/Census/library/working-papers/2006/adrm/rrs2006-02.pdf
  7. The Sequoia Project. “A Framework for Cross-Organizational Patient Identity Management.” Version 3.1. 2018. — Empirical uniqueness probabilities from operational health information exchanges. https://sequoiaproject.org/wp-content/uploads/2018/06/The-Sequoia-Project-Framework-for-Patient-Identity-Management-v31.pdf
  8. RAND Corporation (Hillestad R et al.). “Identity Crisis: An Examination of the Costs and Benefits of a Unique Patient Identifier for the U.S. Health Care System.” Monograph MG-753. 2008. — Collision analysis across composite identifier keys in 80 million records. https://www.rand.org/content/dam/rand/pubs/monographs/2008/RAND_MG753.pdf
  9. National Institute of Standards and Technology. “De-Identifying Government Datasets.” NIST Special Publication 800-188. 2023. — Government framework for probability-based evaluation of identifier systems. https://csrc.nist.gov/pubs/sp/800/188/final
Was this page helpful?