Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry

SNOMED CT terminology is not backed by standard norms of encoding among pathologists. The vast number of concepts ordered in hierarchies and axes, together with the lack of rules of use, complicates the functionality of SNOMED CT for coding, extracting, and analyzing the data. Defining subgroups of...

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Autores: Sanz, Xavier, Pareja, Laura, Rius, Ariadna, Rodenas, Pepi, Abdón, Núria, Gálvez, Jordi, Esteban, Laura, Escribà Jordana, Josep M., Borràs Andrés, Josep Maria, Ribes Puig, Josepa
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/120843
Acceso en línea:https://hdl.handle.net/2445/120843
Access Level:acceso abierto
Palabra clave:Patologia
Glossaris
Terminologia
Catalunya
Espècimens biològics
Pathology
Glossaries
Terminology
Catalonia
Biological specimens
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spelling Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology RegistrySanz, XavierPareja, LauraRius, AriadnaRodenas, PepiAbdón, NúriaGálvez, JordiEsteban, LauraEscribà Jordana, Josep M.Borràs Andrés, Josep MariaRibes Puig, JosepaPatologiaGlossarisTerminologiaCatalunyaEspècimens biològicsPathologyGlossariesTerminologyCataloniaBiological specimensSNOMED CT terminology is not backed by standard norms of encoding among pathologists. The vast number of concepts ordered in hierarchies and axes, together with the lack of rules of use, complicates the functionality of SNOMED CT for coding, extracting, and analyzing the data. Defining subgroups of SNOMED CT by discipline could increase its functionality. The challenge lies in how to choose the concepts to be included in a subset from a total of over 300,000. Besides, SNOMED CT does not cover daily need, as the clinical reality is dynamic and changing. To adapt SNOMED CT to needs in a flexible way, the possibility exists to create extensions. In Catalonia, most pathology departments have been migrating from SNOMED II to SNOMED CT in a bid to advance the development of the Catalan Pathology Registry, which was created in 2014 as a repository for all the pathological diagnoses. This article explains the methodology used to: (a) identify the clinico-pathological entities and the molecular diagnostic procedures not included in SNOMED CT; (b) define the theoretical subset and microglossary of pathology; (c) describe the SNOMED CT concepts used by pathologists of 1.17 million samples of the Catalan Pathology Registry; and d) adapt the theoretical subset and the microglossary according to the actual use of SNOMED CT. Of the 328,365 concepts available for coding the diagnoses (326,732 in SNOMED CT and 1,576 in Catalan extension), only 2% have been used. Combining two axes of SNOMED CT, body structure and clinical findings, has enabled coding most of the morphologies.Elsevier2018201820182018info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersion10 p.application/pdfhttps://hdl.handle.net/2445/120843Articles publicats en revistes (Ciències Clíniques)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésVersió postprint del document publicat a: https://doi.org/10.1016/j.jbi.2017.11.010Journal of Biomedical Informatics, 2018, vol. 78, p. 167-176https://doi.org/10.1016/j.jbi.2017.11.010cc-by-nc-nd (c) Elsevier, 2017http://creativecommons.org/licenses/by-nc-nd/3.0/esinfo:eu-repo/semantics/openAccessoai:recercat.cat:2445/1208432026-05-29T05:05:01Z
dc.title.none.fl_str_mv Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
title Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
spellingShingle Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
Sanz, Xavier
Patologia
Glossaris
Terminologia
Catalunya
Espècimens biològics
Pathology
Glossaries
Terminology
Catalonia
Biological specimens
title_short Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
title_full Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
title_fullStr Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
title_full_unstemmed Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
title_sort Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry
dc.creator.none.fl_str_mv Sanz, Xavier
Pareja, Laura
Rius, Ariadna
Rodenas, Pepi
Abdón, Núria
Gálvez, Jordi
Esteban, Laura
Escribà Jordana, Josep M.
Borràs Andrés, Josep Maria
Ribes Puig, Josepa
author Sanz, Xavier
author_facet Sanz, Xavier
Pareja, Laura
Rius, Ariadna
Rodenas, Pepi
Abdón, Núria
Gálvez, Jordi
Esteban, Laura
Escribà Jordana, Josep M.
Borràs Andrés, Josep Maria
Ribes Puig, Josepa
author_role author
author2 Pareja, Laura
Rius, Ariadna
Rodenas, Pepi
Abdón, Núria
Gálvez, Jordi
Esteban, Laura
Escribà Jordana, Josep M.
Borràs Andrés, Josep Maria
Ribes Puig, Josepa
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Patologia
Glossaris
Terminologia
Catalunya
Espècimens biològics
Pathology
Glossaries
Terminology
Catalonia
Biological specimens
topic Patologia
Glossaris
Terminologia
Catalunya
Espècimens biològics
Pathology
Glossaries
Terminology
Catalonia
Biological specimens
description SNOMED CT terminology is not backed by standard norms of encoding among pathologists. The vast number of concepts ordered in hierarchies and axes, together with the lack of rules of use, complicates the functionality of SNOMED CT for coding, extracting, and analyzing the data. Defining subgroups of SNOMED CT by discipline could increase its functionality. The challenge lies in how to choose the concepts to be included in a subset from a total of over 300,000. Besides, SNOMED CT does not cover daily need, as the clinical reality is dynamic and changing. To adapt SNOMED CT to needs in a flexible way, the possibility exists to create extensions. In Catalonia, most pathology departments have been migrating from SNOMED II to SNOMED CT in a bid to advance the development of the Catalan Pathology Registry, which was created in 2014 as a repository for all the pathological diagnoses. This article explains the methodology used to: (a) identify the clinico-pathological entities and the molecular diagnostic procedures not included in SNOMED CT; (b) define the theoretical subset and microglossary of pathology; (c) describe the SNOMED CT concepts used by pathologists of 1.17 million samples of the Catalan Pathology Registry; and d) adapt the theoretical subset and the microglossary according to the actual use of SNOMED CT. Of the 328,365 concepts available for coding the diagnoses (326,732 in SNOMED CT and 1,576 in Catalan extension), only 2% have been used. Combining two axes of SNOMED CT, body structure and clinical findings, has enabled coding most of the morphologies.
publishDate 2018
dc.date.none.fl_str_mv 2018
2018
2018
2018
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/120843
url https://hdl.handle.net/2445/120843
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Versió postprint del document publicat a: https://doi.org/10.1016/j.jbi.2017.11.010
Journal of Biomedical Informatics, 2018, vol. 78, p. 167-176
https://doi.org/10.1016/j.jbi.2017.11.010
dc.rights.none.fl_str_mv cc-by-nc-nd (c) Elsevier, 2017
http://creativecommons.org/licenses/by-nc-nd/3.0/es
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by-nc-nd (c) Elsevier, 2017
http://creativecommons.org/licenses/by-nc-nd/3.0/es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10 p.
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Articles publicats en revistes (Ciències Clíniques)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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