Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT.

Steven H. Brown; Brent A. Bauer; Dietland L. Wahner-Roedler; Peter L. Elkin

Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT.

Steven H. Brown, Brent A. Bauer, Dietland L. Wahner-Roedler, Peter L. Elkin

General Internal Medicine

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

Abstract

OBJECTIVE: To evaluate SNOMED-CT 's ability to represent simple and compositional concepts in FDA approved oncology drug indications. METHODS: Oncology drug indications were decomposed into single and compositional concepts. SNOMED-CT's coverage of single concepts and the semantics needed to create compositional concepts were evaluated using automated and manual techniques. RESULTS: SNOMED-CT covered 86.3% of single concepts present in oncology drug indications; 11.3% of indications were covered completely. Coverage was best for concepts describing diseases, anatomy, and patient characteristics. Medications accounted for 50.5% of missing concepts. Excluding drug names, 45.2% of indications were completely represented. SNOMED-CT's semantics completely represented 60.1% of compositional expressions. CONCLUSIONS: SNOMED-CT's overall coverage of the concepts in oncology drug indications was good. Improvements or alternatives are needed for medications and semantics.

Original language	English (US)
Pages (from-to)	115-119
Number of pages	5
Journal	AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
State	Published - 2003

ASJC Scopus subject areas

General Medicine

Cite this

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title = "Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT.",

abstract = "OBJECTIVE: To evaluate SNOMED-CT 's ability to represent simple and compositional concepts in FDA approved oncology drug indications. METHODS: Oncology drug indications were decomposed into single and compositional concepts. SNOMED-CT's coverage of single concepts and the semantics needed to create compositional concepts were evaluated using automated and manual techniques. RESULTS: SNOMED-CT covered 86.3% of single concepts present in oncology drug indications; 11.3% of indications were covered completely. Coverage was best for concepts describing diseases, anatomy, and patient characteristics. Medications accounted for 50.5% of missing concepts. Excluding drug names, 45.2% of indications were completely represented. SNOMED-CT's semantics completely represented 60.1% of compositional expressions. CONCLUSIONS: SNOMED-CT's overall coverage of the concepts in oncology drug indications was good. Improvements or alternatives are needed for medications and semantics.",

author = "Brown, {Steven H.} and Bauer, {Brent A.} and Wahner-Roedler, {Dietland L.} and Elkin, {Peter L.}",

year = "2003",

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T1 - Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT.

AU - Brown, Steven H.

AU - Bauer, Brent A.

AU - Wahner-Roedler, Dietland L.

AU - Elkin, Peter L.

PY - 2003

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N2 - OBJECTIVE: To evaluate SNOMED-CT 's ability to represent simple and compositional concepts in FDA approved oncology drug indications. METHODS: Oncology drug indications were decomposed into single and compositional concepts. SNOMED-CT's coverage of single concepts and the semantics needed to create compositional concepts were evaluated using automated and manual techniques. RESULTS: SNOMED-CT covered 86.3% of single concepts present in oncology drug indications; 11.3% of indications were covered completely. Coverage was best for concepts describing diseases, anatomy, and patient characteristics. Medications accounted for 50.5% of missing concepts. Excluding drug names, 45.2% of indications were completely represented. SNOMED-CT's semantics completely represented 60.1% of compositional expressions. CONCLUSIONS: SNOMED-CT's overall coverage of the concepts in oncology drug indications was good. Improvements or alternatives are needed for medications and semantics.

AB - OBJECTIVE: To evaluate SNOMED-CT 's ability to represent simple and compositional concepts in FDA approved oncology drug indications. METHODS: Oncology drug indications were decomposed into single and compositional concepts. SNOMED-CT's coverage of single concepts and the semantics needed to create compositional concepts were evaluated using automated and manual techniques. RESULTS: SNOMED-CT covered 86.3% of single concepts present in oncology drug indications; 11.3% of indications were covered completely. Coverage was best for concepts describing diseases, anatomy, and patient characteristics. Medications accounted for 50.5% of missing concepts. Excluding drug names, 45.2% of indications were completely represented. SNOMED-CT's semantics completely represented 60.1% of compositional expressions. CONCLUSIONS: SNOMED-CT's overall coverage of the concepts in oncology drug indications was good. Improvements or alternatives are needed for medications and semantics.

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Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT.

Abstract

ASJC Scopus subject areas

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