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Composite CDE: modeling composite relationships between common data elements for representing complex clinical data

BACKGROUND: Semantic interoperability is essential for improving data quality and sharing. The ISO/IEC 11179 Metadata Registry (MDR) standard has been highlighted as a solution for standardizing and registering clinical data elements (DEs). However, the standard model has both structural and semanti...

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Autores principales: Kim, Hye Hyeon, Park, Yu Rang, Lee, Suehyun, Kim, Ju Han
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333279/
https://www.ncbi.nlm.nih.gov/pubmed/32620117
http://dx.doi.org/10.1186/s12911-020-01168-0
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author Kim, Hye Hyeon
Park, Yu Rang
Lee, Suehyun
Kim, Ju Han
author_facet Kim, Hye Hyeon
Park, Yu Rang
Lee, Suehyun
Kim, Ju Han
author_sort Kim, Hye Hyeon
collection PubMed
description BACKGROUND: Semantic interoperability is essential for improving data quality and sharing. The ISO/IEC 11179 Metadata Registry (MDR) standard has been highlighted as a solution for standardizing and registering clinical data elements (DEs). However, the standard model has both structural and semantic limitations, and the number of DEs continues to increase due to poor term reusability. Semantic types and constraints are lacking for comprehensively describing and evaluating DEs on real-world clinical documents. METHODS: We addressed these limitations by defining three new types of semantic relationship (dependency, composite, and variable) in our previous studies. The present study created new and further extended existing semantic types (hybrid atomic and repeated and dictionary composite common data elements [CDEs]) with four constraints: ordered, operated, required, and dependent. For evaluation, we extracted all atomic and composite CDEs from five major clinical documents from five teaching hospitals in Korea, 14 Fast Healthcare Interoperability Resources (FHIR) resources from FHIR bulk sample data, and MIMIC-III (Medical Information Mart for Intensive Care) demo dataset. Metadata reusability and semantic interoperability in real clinical settings were comprehensively evaluated by applying the CDEs with our extended semantic types and constraints. RESULTS: All of the CDEs (n = 1142) extracted from the 25 clinical documents were successfully integrated with a very high CDE reuse ratio (46.9%) into 586 CDEs (259 atomic and 20 unique composite CDEs), and all of CDEs (n = 238) extracted from the 14 FHIR resources of FHIR bulk sample data were successfully integrated with high CDE reuse ration (59.7%) into 96 CDEs (21 atomic and 28 unique composite CDEs), which improved the semantic integrity and interoperability without any semantic loss. Moreover, the most complex data structures from two CDE projects were successfully encoded with rich semantics and semantic integrity. CONCLUSION: MDR-based extended semantic types and constraints can facilitate comprehensive representation of clinical documents with rich semantics, and improved semantic interoperability without semantic loss.
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spelling pubmed-73332792020-07-06 Composite CDE: modeling composite relationships between common data elements for representing complex clinical data Kim, Hye Hyeon Park, Yu Rang Lee, Suehyun Kim, Ju Han BMC Med Inform Decis Mak Technical Advance BACKGROUND: Semantic interoperability is essential for improving data quality and sharing. The ISO/IEC 11179 Metadata Registry (MDR) standard has been highlighted as a solution for standardizing and registering clinical data elements (DEs). However, the standard model has both structural and semantic limitations, and the number of DEs continues to increase due to poor term reusability. Semantic types and constraints are lacking for comprehensively describing and evaluating DEs on real-world clinical documents. METHODS: We addressed these limitations by defining three new types of semantic relationship (dependency, composite, and variable) in our previous studies. The present study created new and further extended existing semantic types (hybrid atomic and repeated and dictionary composite common data elements [CDEs]) with four constraints: ordered, operated, required, and dependent. For evaluation, we extracted all atomic and composite CDEs from five major clinical documents from five teaching hospitals in Korea, 14 Fast Healthcare Interoperability Resources (FHIR) resources from FHIR bulk sample data, and MIMIC-III (Medical Information Mart for Intensive Care) demo dataset. Metadata reusability and semantic interoperability in real clinical settings were comprehensively evaluated by applying the CDEs with our extended semantic types and constraints. RESULTS: All of the CDEs (n = 1142) extracted from the 25 clinical documents were successfully integrated with a very high CDE reuse ratio (46.9%) into 586 CDEs (259 atomic and 20 unique composite CDEs), and all of CDEs (n = 238) extracted from the 14 FHIR resources of FHIR bulk sample data were successfully integrated with high CDE reuse ration (59.7%) into 96 CDEs (21 atomic and 28 unique composite CDEs), which improved the semantic integrity and interoperability without any semantic loss. Moreover, the most complex data structures from two CDE projects were successfully encoded with rich semantics and semantic integrity. CONCLUSION: MDR-based extended semantic types and constraints can facilitate comprehensive representation of clinical documents with rich semantics, and improved semantic interoperability without semantic loss. BioMed Central 2020-07-03 /pmc/articles/PMC7333279/ /pubmed/32620117 http://dx.doi.org/10.1186/s12911-020-01168-0 Text en © The Author(s) 2020 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/. 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 in a credit line to the data.
spellingShingle Technical Advance
Kim, Hye Hyeon
Park, Yu Rang
Lee, Suehyun
Kim, Ju Han
Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title_full Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title_fullStr Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title_full_unstemmed Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title_short Composite CDE: modeling composite relationships between common data elements for representing complex clinical data
title_sort composite cde: modeling composite relationships between common data elements for representing complex clinical data
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333279/
https://www.ncbi.nlm.nih.gov/pubmed/32620117
http://dx.doi.org/10.1186/s12911-020-01168-0
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