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First published February 24, 2006 as JAMIA PrePrint; doi:10.1197/jamia.M1823
Journal of the American Medical Informatics Association 2006;13(3):334-343
© 2006 American Medical Informatics Association

A more recent version of this article appeared on May 1, 2006
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Submitted on March 8, 2005
Accepted on February 1, 2006

A System for Automated Lexical Mapping

Jennifer Y. Sun MD, MS1* and Yao Sun MD, PhD1

Affiliation of the authors: 1 Newborn Medicine Informatics Program, Children's Hospital, Boston, MA

* To whom correspondence should be addressed.

Objective To automate the mapping of disparate databases to standardized medical vocabularies.

Background Merging of clinical systems and medical databases, or aggregation of information from disparate databases, frequently requires a process where vocabularies are compared and similar concepts are mapped.

Design Using a normalization phase followed by a novel alignment stage inspired by DNA sequence alignment methods, automated lexical mapping can map terms from various databases to standard vocabularies such as the UMLS (Unified Medical Language System) and LOINC (Logical Observation Identifiers Names and Codes).

Measurememts This automated lexical mapping was evaluated using three real-world laboratory databases from different healthcare institutions. We report sensitivity, specificity, percent correct (true positives plus true negatives divided by total number of terms), true positive and true negative rates as measures of system performance.

Results The alignment algorithm was able to map 57-78% (average of 63% over all runs and databases) of equivalent concepts through lexical mapping alone. True positive rates ranged from 18-70%; true negative rates ranged from 5-52%.

Conclusion Lexical mapping can facilitate the integration of data from diverse sources and decrease the time and cost required for manual mapping and integration of clinical systems and medical databases.




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