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Proceedings of the AMIA Symposium logoLink to Proceedings of the AMIA Symposium
. 2002:305–309.

Analysis of identifier performance using a deterministic linkage algorithm.

Shaun J Grannis 1, J Marc Overhage 1, Clement J McDonald 1
PMCID: PMC2244404  PMID: 12463836

Abstract

As part of developing a record linkage algorithm using de-identified patient data, we analyzed the performance of several demographic variables for making linkages between patient registry records from two hospital registries and the Social Security Death Master File. We analyzed samples from each registry totaling 6,000 record-pairs to establish a linkage gold-standard. Using Social Security Number as the exclusive linkage variable resulted in substantial linkage error rates of 4.7% and 9.2%. The best single variable combination for finding links was Social Security Number, phonetically compressed first name, birth month, and gender. This found 87% and 88% of the links without any false links. We achieved sensitivities of 90% to 92% while maintaining 100% specificity using combinations of social security number, gender, name, and birth date fields. This represents an accurate method for linking patient records to death data and is the basis for a more generalized de-identified linkage algorithm.

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Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Liu S. Development of record linkage of hospital discharge data for the study of neonatal readmission. Chronic Dis Can. 1999;20(2):77–81. [PubMed] [Google Scholar]
  2. Newman T. B., Brown A. N. Use of commercial record linkage software and vital statistics to identify patient deaths. J Am Med Inform Assoc. 1997 May-Jun;4(3):233–237. doi: 10.1136/jamia.1997.0040233. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Pates R. D., Scully K. W., Einbinder J. S., Merkel R. L., Stukenborg G. J., Spraggins T. A., Reynolds C., Hyman R., Dembling B. P. Adding value to clinical data by linkage to a public death registry. Stud Health Technol Inform. 2001;84(Pt 2):1384–1388. [PubMed] [Google Scholar]
  4. Potosky A. L., Riley G. F., Lubitz J. D., Mentnech R. M., Kessler L. G. Potential for cancer related health services research using a linked Medicare-tumor registry database. Med Care. 1993 Aug;31(8):732–748. [PubMed] [Google Scholar]
  5. Sideli R. V., Friedman C. Validating patient names in an integrated clinical information system. Proc Annu Symp Comput Appl Med Care. 1991:588–592. [PMC free article] [PubMed] [Google Scholar]
  6. Van den Brandt P. A., Schouten L. J., Goldbohm R. A., Dorant E., Hunen P. M. Development of a record linkage protocol for use in the Dutch Cancer Registry for Epidemiological Research. Int J Epidemiol. 1990 Sep;19(3):553–558. doi: 10.1093/ije/19.3.553. [DOI] [PubMed] [Google Scholar]

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