A practical method of linking data from Medicare claims and a comprehensive electronic medical records system

Int J Med Inform. 2003 Aug;71(1):57-69. doi: 10.1016/s1386-5056(03)00089-3.


Background: Linking administrative and clinical databases provides opportunities for richer studies to improve healthcare, but linkage may require sophisticated algorithms. Linking US Medicare data with large databases used for everyday clinical practice is seldom described in detail in medical literature.

Objectives: Test a deterministic method of linking data from a local electronic medical records system to Medicare data, and report specific details of the algorithm used as well as lessons learned from the linkage process.

Subjects: Medicare beneficiaries with medical encounters in selected Indiana counties in the 5-year period ending in 1999.

Results: For 6,388 beneficiaries with Medicare data indicating inpatient encounters in the system, 98% had links to the clinical database. Of 7,231 patients hospitalized and registered in the local clinical system, 86% contained a link to Medicare data, and 69% contained a link even without using Social security number (SSN) as an identifier. Medicare data that conflicted with local hospital records by indicating no local hospitalization occurred in 1.8%. More than 2,000 claims contained hospital identifiers that did not exist in the hospital codebook.

Conclusions: Details of a practical, deterministic method of linking Medicare claims to a large electronic records system have been applied and described. Most records were linked without SSN. A variety of inconsistencies were found and these, along with missing or incomplete data, can influence linking. Integrity of specific variables must be assessed carefully.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • Data Collection*
  • Databases, Factual
  • Hospital Information Systems
  • Humans
  • Information Storage and Retrieval*
  • Insurance Claim Review / statistics & numerical data*
  • Medical Records Systems, Computerized / statistics & numerical data*
  • Medicare / statistics & numerical data*