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K A Zollo

Publications and source records attributed to K A Zollo.

2 recordsLinked to original sources

Department of Veterans Affairs, University of Utah consortium participation in the NLM/AHCPR Large Scale Vocabulary Test.

The Large Scale Vocabulary Test (LSVT) was designed to evaluate how well the Metathesaurus plus planned additions to Meta covered the documentation needs of clinicians. Our consortium collected 10,538 clinical narratives from patient problem lists recorded at 65 Veterans Hospitals, internal medicine ambulatory care practices, diagnostic history and physical examination data elements from Iliad, and nursing shift notes and emergency transport patient records. The results showed 94% of submitted terms resulted in acceptable matches. 49% of submitted terms were judged to be synonymous with the match terms, 35% were judged to be more specific (usually due to modifiers), 2%, were less specific, and 6% had an associative relationship. In 8% of cases either no match was found by the LSVT interface or all proposed matches were rejected by the raters. The LSVT content was quite suitable for coding our narratives. Necessary improvements for an electronic record would include the ability to compose modifiers together with root concepts.

Ambulatory Care↗

Automated mapping of observation codes using extensional definitions.

OBJECTIVE: To create "extensional definitions" of laboratory codes from derived characteristics of coded values in a clinical database and then use these definitions in the automated mapping of codes between disparate facilities. DESIGN: Repository data for two laboratory facilities in the Intermountain Health Care system were analyzed to create extensional definitions for the local codes of each facility. These definitions were then matched using automated matching software to create mappings between the shared local codes. The results were compared with the mappings of the vocabulary developers. MEASUREMENTS: The number of correct matches and the size of the match group were recorded. A match was considered correct if the corresponding codes from each facility were included in the group. The group size was defined as the total number of codes in the match group (e.g., a one-to-one mapping is a group size of two). RESULTS: Of the matches generated by the automated matching software, 81 percent were correct. The average group size was 2.4. There were a total of 328 possible matches in the data set, and 75 percent of these were correctly identified. CONCLUSIONS: Extensional definitions for local codes created from repository data can be utilized to automatically map codes from disparate systems. This approach, if generalized to other systems, can reduce the effort required to map one system to another while increasing mapping consistency.

Algorithms↗