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Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System

BACKGROUND: Standardization in clinical documentation can increase efficiency and can save time and resources. OBJECTIVE: The objectives of this work are to compare documentation forms for acute coronary syndrome (ACS), check for standardization, and generate a list of the most common data elements...

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Autores principales: Kentgen, Markus, Varghese, Julian, Samol, Alexander, Waltenberger, Johannes, Dugas, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6729118/
https://www.ncbi.nlm.nih.gov/pubmed/31444871
http://dx.doi.org/10.2196/14107
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author Kentgen, Markus
Varghese, Julian
Samol, Alexander
Waltenberger, Johannes
Dugas, Martin
author_facet Kentgen, Markus
Varghese, Julian
Samol, Alexander
Waltenberger, Johannes
Dugas, Martin
author_sort Kentgen, Markus
collection PubMed
description BACKGROUND: Standardization in clinical documentation can increase efficiency and can save time and resources. OBJECTIVE: The objectives of this work are to compare documentation forms for acute coronary syndrome (ACS), check for standardization, and generate a list of the most common data elements using semantic form annotation with the Unified Medical Language System (UMLS). METHODS: Forms from registries, studies, risk scores, quality assurance, official guidelines, and routine documentation from four hospitals in Germany were semantically annotated using UMLS. This allowed for automatic comparison of concept frequencies and the generation of a list of the most common concepts. RESULTS: A total of 3710 forms items from 86 sources were semantically annotated using 842 unique UMLS concepts. Half of all medical concept occurrences were covered by 60 unique concepts, which suggests the existence of a core dataset of relevant concepts. Overlap percentages between forms were relatively low, hinting at inconsistent documentation structures and lack of standardization. CONCLUSIONS: This analysis shows a lack of standardized and semantically enriched documentation for patients with ACS. Efforts made by official institutions like the European Society for Cardiology have not yet been fully implemented. Utilizing a standardized and annotated core dataset of the most important data concepts could make export and automatic reuse of data easier. The generated list of common data elements is an exemplary implementation suggestion of the concepts to use in a standardized approach.
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spelling pubmed-67291182019-09-23 Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System Kentgen, Markus Varghese, Julian Samol, Alexander Waltenberger, Johannes Dugas, Martin JMIR Med Inform Original Paper BACKGROUND: Standardization in clinical documentation can increase efficiency and can save time and resources. OBJECTIVE: The objectives of this work are to compare documentation forms for acute coronary syndrome (ACS), check for standardization, and generate a list of the most common data elements using semantic form annotation with the Unified Medical Language System (UMLS). METHODS: Forms from registries, studies, risk scores, quality assurance, official guidelines, and routine documentation from four hospitals in Germany were semantically annotated using UMLS. This allowed for automatic comparison of concept frequencies and the generation of a list of the most common concepts. RESULTS: A total of 3710 forms items from 86 sources were semantically annotated using 842 unique UMLS concepts. Half of all medical concept occurrences were covered by 60 unique concepts, which suggests the existence of a core dataset of relevant concepts. Overlap percentages between forms were relatively low, hinting at inconsistent documentation structures and lack of standardization. CONCLUSIONS: This analysis shows a lack of standardized and semantically enriched documentation for patients with ACS. Efforts made by official institutions like the European Society for Cardiology have not yet been fully implemented. Utilizing a standardized and annotated core dataset of the most important data concepts could make export and automatic reuse of data easier. The generated list of common data elements is an exemplary implementation suggestion of the concepts to use in a standardized approach. JMIR Publications 2019-08-23 /pmc/articles/PMC6729118/ /pubmed/31444871 http://dx.doi.org/10.2196/14107 Text en ©Markus Kentgen, Julian Varghese, Alexander Samol, Johannes Waltenberger, Martin Dugas. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 23.08.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on http://medinform.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kentgen, Markus
Varghese, Julian
Samol, Alexander
Waltenberger, Johannes
Dugas, Martin
Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title_full Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title_fullStr Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title_full_unstemmed Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title_short Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System
title_sort common data elements for acute coronary syndrome: analysis based on the unified medical language system
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6729118/
https://www.ncbi.nlm.nih.gov/pubmed/31444871
http://dx.doi.org/10.2196/14107
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