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Journal of the American Medical Informatics Association, Vol 3, 66-78, Copyright © 1996 by American Medical Informatics Association
ARTICLES |
JL Kannry, L Wright, M Shifman, S Silverstein and PL Miller
Yale University School of Medicine, New Haven, CT, USA.
OBJECTIVE: To examine the issues involved in mapping an existing structured controlled vocabulary, the Medical Entities Dictionary (MED) developed at Columbia University, to an institutional vocabulary, the laboratory and pharmacy vocabularies of the Yale New Haven Medical Center. DESIGN: 200 Yale pharmacy terms and 200 Yale laboratory terms were randomly selected from database files containing all of the Yale laboratory and pharmacy terms. These 400 terms were then mapped to the MED in three phases: mapping terms, mapping relationships between terms, and mapping attributes that modify terms. RESULTS: 73% of the Yale pharmacy terms mapped to MED terms. 49% of the Yale laboratory terms mapped to MED terms. After certain obsolete and otherwise inappropriate laboratory terms were eliminated, the latter rate improved to 59%. 23% of the unmatched Yale laboratory terms failed to match because of differences in granularity with MED terms. The Yale and MED pharmacy terms share 12 of 30 distinct attributes. The Yale and MED laboratory terms share 14 of 23 distinct attributes. CONCLUSION: The mapping of an institutional vocabulary to a structured controlled vocabulary requires that the mapping be performed at the level of terms, relationships, and attributes. The mapping process revealed the importance of standardization of local vocabulary subsets, standardization of attribute representation, and term granularity.
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