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Research Paper |
Affiliations of the authors: Healthcare Informatics (TWV) and Health Economics and Outcomes Research (RMM), SmithKline Beecham, Collegeville, Pennsylvania.
Correspondence and reprints: Timothy W. Victor, Assistant Director, Research and Biostatistics, Healthcare Informatics, SmithKline Beecham, MS UP4305, 1250 South Collegeville Road, Collegeville PA 19426-2990; e-mail: <timothy.w.victor{at}sbphrd.com>.
Objective: This paper provides a detailed description of a method developed for purposes of linking records of individual patients, represented in diverse data sets, across time and geography.
Design: The procedure for record linkage has three major componentsdata standardization, weight estimation, and matching. The proposed method was designed to incorporate a combination of exact and probabilistic matching techniques.
Measurements: The procedure was validated using convergent, divergent, and criterion validity measures.
Results: The output of the process achieved a sensitivity of 92 percent and a specificity that approached 100 percent.
Conclusions: The procedure is a first step in addressing the current trend toward larger and more complex databases.
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