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Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL
BACKGROUND: For standardization of terms in the reports of medical device adverse events, 89 Japanese medical device adverse event terminologies were published in March 2015. The 89 terminologies were developed independently by 13 industry associations, suggesting that there may be inconsistencies a...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767687/ https://www.ncbi.nlm.nih.gov/pubmed/35042480 http://dx.doi.org/10.1186/s12911-022-01748-2 |
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author | Yagahara, Ayako Yokoi, Hideto |
author_facet | Yagahara, Ayako Yokoi, Hideto |
author_sort | Yagahara, Ayako |
collection | PubMed |
description | BACKGROUND: For standardization of terms in the reports of medical device adverse events, 89 Japanese medical device adverse event terminologies were published in March 2015. The 89 terminologies were developed independently by 13 industry associations, suggesting that there may be inconsistencies among the terms proposed. The purpose of this study was to integrate the 89 sets of terminologies and evaluate inconsistencies among them using SPARQL. METHODS: In order to evaluate the inconsistencies among the integrated terminology, the following six items were evaluated: (1) whether the two-layer structure between category term and preferred term is consistent, (2) whether synonyms of a preferred term are involved. Reversing the layer-category order of matching was also performed, (3) whether each preferred term is subordinate to only one category term, (4) whether the definitions of terms are uniquely determined, (5) whether CDRH-NCIt terms corresponding to preferred terms are uniquely determined, (6) whether a term in a medical device problem is used for patient problems. RESULTS: About 60% of the total number of duplicated terms were found. This is because industry associations that created multiple terminologies adopted the same terms in terminologies of similar medical device groups. In the case that all terms with the same spelling have the same concept, efficient integration can be achieved automatically using RDF. Furthermore, we evaluated six matters of inconsistency in this study, terms that need to be reviewed accounted for about 10% or less than 10% in each item. CONCLUSIONS: The RDF and SPARQL were useful tools to explore inconsistencies of hierarchies, definition statements, and synonyms when integrating terminolgy by term notation, and these had the advantage of reducing the physical and time burden. |
format | Online Article Text |
id | pubmed-8767687 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-87676872022-01-19 Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL Yagahara, Ayako Yokoi, Hideto BMC Med Inform Decis Mak Research BACKGROUND: For standardization of terms in the reports of medical device adverse events, 89 Japanese medical device adverse event terminologies were published in March 2015. The 89 terminologies were developed independently by 13 industry associations, suggesting that there may be inconsistencies among the terms proposed. The purpose of this study was to integrate the 89 sets of terminologies and evaluate inconsistencies among them using SPARQL. METHODS: In order to evaluate the inconsistencies among the integrated terminology, the following six items were evaluated: (1) whether the two-layer structure between category term and preferred term is consistent, (2) whether synonyms of a preferred term are involved. Reversing the layer-category order of matching was also performed, (3) whether each preferred term is subordinate to only one category term, (4) whether the definitions of terms are uniquely determined, (5) whether CDRH-NCIt terms corresponding to preferred terms are uniquely determined, (6) whether a term in a medical device problem is used for patient problems. RESULTS: About 60% of the total number of duplicated terms were found. This is because industry associations that created multiple terminologies adopted the same terms in terminologies of similar medical device groups. In the case that all terms with the same spelling have the same concept, efficient integration can be achieved automatically using RDF. Furthermore, we evaluated six matters of inconsistency in this study, terms that need to be reviewed accounted for about 10% or less than 10% in each item. CONCLUSIONS: The RDF and SPARQL were useful tools to explore inconsistencies of hierarchies, definition statements, and synonyms when integrating terminolgy by term notation, and these had the advantage of reducing the physical and time burden. BioMed Central 2022-01-19 /pmc/articles/PMC8767687/ /pubmed/35042480 http://dx.doi.org/10.1186/s12911-022-01748-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Yagahara, Ayako Yokoi, Hideto Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title | Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title_full | Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title_fullStr | Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title_full_unstemmed | Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title_short | Terminology integration and inconsistency identification of adverse event terminology for Japanese medical devices using SPARQL |
title_sort | terminology integration and inconsistency identification of adverse event terminology for japanese medical devices using sparql |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8767687/ https://www.ncbi.nlm.nih.gov/pubmed/35042480 http://dx.doi.org/10.1186/s12911-022-01748-2 |
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