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Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT

BACKGROUND: SNOMED CT is a standardized and comprehensive clinical terminology that is used in Electronic Health Records to capture, store and access clinical data of patients. Studies have, however, shown that there are inconsistencies inherent in the modeling of concepts in SNOMED CT that can have...

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Autor principal: Agrawal, Ankur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290591/
https://www.ncbi.nlm.nih.gov/pubmed/30537959
http://dx.doi.org/10.1186/s12911-018-0673-z
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author Agrawal, Ankur
author_facet Agrawal, Ankur
author_sort Agrawal, Ankur
collection PubMed
description BACKGROUND: SNOMED CT is a standardized and comprehensive clinical terminology that is used in Electronic Health Records to capture, store and access clinical data of patients. Studies have, however, shown that there are inconsistencies inherent in the modeling of concepts in SNOMED CT that can have an impact on its usage to record clinical data and in clinical decision-making tools. METHODS: An effective lexical approach to identifying inconsistencies with high likelihood in the structural modeling of the concepts of SNOMED CT is discussed and assessed. The approach uses the two or more concepts in the context of their lexical similarity to compare their modeling in order to identify inconsistencies. A sample of 50 sets is randomly picked from the Procedure hierarchy of SNOMED CT and evaluated for inconsistencies. RESULTS: Of the 50 randomly picked sets, 58% are found to exhibit one or more concepts with inconsistencies. In terms of concepts, 29% of the 146 concepts are found to exhibit one or more inconsistencies. CONCLUSIONS: The assessment of the sample concepts shows that SNOMED CT is not free from inconsistencies which may affect its use in clinical care and decision support systems. The proposed methodology is found to be effective in identifying areas of SNOMED CT that may be in need of quality assessment.
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spelling pubmed-62905912018-12-17 Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT Agrawal, Ankur BMC Med Inform Decis Mak Research BACKGROUND: SNOMED CT is a standardized and comprehensive clinical terminology that is used in Electronic Health Records to capture, store and access clinical data of patients. Studies have, however, shown that there are inconsistencies inherent in the modeling of concepts in SNOMED CT that can have an impact on its usage to record clinical data and in clinical decision-making tools. METHODS: An effective lexical approach to identifying inconsistencies with high likelihood in the structural modeling of the concepts of SNOMED CT is discussed and assessed. The approach uses the two or more concepts in the context of their lexical similarity to compare their modeling in order to identify inconsistencies. A sample of 50 sets is randomly picked from the Procedure hierarchy of SNOMED CT and evaluated for inconsistencies. RESULTS: Of the 50 randomly picked sets, 58% are found to exhibit one or more concepts with inconsistencies. In terms of concepts, 29% of the 146 concepts are found to exhibit one or more inconsistencies. CONCLUSIONS: The assessment of the sample concepts shows that SNOMED CT is not free from inconsistencies which may affect its use in clinical care and decision support systems. The proposed methodology is found to be effective in identifying areas of SNOMED CT that may be in need of quality assessment. BioMed Central 2018-12-12 /pmc/articles/PMC6290591/ /pubmed/30537959 http://dx.doi.org/10.1186/s12911-018-0673-z Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Agrawal, Ankur
Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title_full Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title_fullStr Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title_full_unstemmed Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title_short Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT
title_sort evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of snomed ct
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290591/
https://www.ncbi.nlm.nih.gov/pubmed/30537959
http://dx.doi.org/10.1186/s12911-018-0673-z
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