Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language

Taxonomic triangulation is a data mining technique for the management of care knowledge. This technique uses standardized languages, such as North American Nursing Diagnosis Association International, Nursing Outcomes Classification, and Nursing Interventions Classification, as well as logic. Its pu...

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Autores: González Aguña, Alexandra, Fernández Batalla, Marta, Gasco González, Sara, Cercas Duque, Adriana, Jiménez Rodríguez, María Lourdes|||0000-0003-4398-5404, Santamaría García, José María|||0000-0001-7203-4021
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Alcalá (UAH)
Repositorio:e_Buah Biblioteca Digital Universidad de Alcalá
Idioma:inglés
OAI Identifier:oai:ebuah.uah.es:10017/63611
Acceso en línea:http://hdl.handle.net/10017/63611
https://dx.doi.org/10.1097/CIN.0000000000000662
Access Level:acceso abierto
Palabra clave:Data mining
Diagnosis
Knowledge management
Nursing methodology research
Standardized nursing terminology
Enfermería
Nursing
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spelling Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized LanguageGonzález Aguña, AlexandraFernández Batalla, MartaGasco González, SaraCercas Duque, AdrianaJiménez Rodríguez, María Lourdes|||0000-0003-4398-5404Santamaría García, José María|||0000-0001-7203-4021Data miningDiagnosisKnowledge managementNursing methodology researchStandardized nursing terminologyEnfermeríaNursingTaxonomic triangulation is a data mining technique for the management of care knowledge. This technique uses standardized languages, such as North American Nursing Diagnosis Association International, Nursing Outcomes Classification, and Nursing Interventions Classification, as well as logic. Its purpose is to find patterns in the data and identify care diagnoses. Triangulation can be applied to databases (clinical records) or to bibliographic sources (eg, protocols). The objective of this study is to identify the care diagnoses implicit in the nursing care protocols of the Community of Madrid. The method followed has three phases: knowledge extraction for mapping of variables, linking to diagnoses, and triangulation with analysis. The study analyzes six protocols, and 344 variables (167 assessment, 29 planning, and 148 intervention) and 6118 links have been extracted. Triangulation identified 165 NANDA diagnoses (68.48%), and only 25 labels were not revealed through this process. As a limitation, the results depend on the knowledge presented in protocols and change with language editions. Some labels included in the sample are recent and are not included in the links with nursing outcomes classification and nursing interventions classification. In conclusion, taxonomic triangulation makes it possible to manage knowledge, discover data patterns, and represent care situations.20212021-03-01journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10017/63611https://dx.doi.org/10.1097/CIN.0000000000000662reponame:e_Buah Biblioteca Digital Universidad de Alcaláinstname:Universidad de Alcalá (UAH)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:ebuah.uah.es:10017/636112026-06-18T11:13:07Z
dc.title.none.fl_str_mv Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
title Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
spellingShingle Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
González Aguña, Alexandra
Data mining
Diagnosis
Knowledge management
Nursing methodology research
Standardized nursing terminology
Enfermería
Nursing
title_short Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
title_full Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
title_fullStr Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
title_full_unstemmed Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
title_sort Taxonomic Triangulation of Care in Healthcare Protocols: Mapping of Diagnostic Knowledge From Standardized Language
dc.creator.none.fl_str_mv González Aguña, Alexandra
Fernández Batalla, Marta
Gasco González, Sara
Cercas Duque, Adriana
Jiménez Rodríguez, María Lourdes|||0000-0003-4398-5404
Santamaría García, José María|||0000-0001-7203-4021
author González Aguña, Alexandra
author_facet González Aguña, Alexandra
Fernández Batalla, Marta
Gasco González, Sara
Cercas Duque, Adriana
Jiménez Rodríguez, María Lourdes|||0000-0003-4398-5404
Santamaría García, José María|||0000-0001-7203-4021
author_role author
author2 Fernández Batalla, Marta
Gasco González, Sara
Cercas Duque, Adriana
Jiménez Rodríguez, María Lourdes|||0000-0003-4398-5404
Santamaría García, José María|||0000-0001-7203-4021
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Data mining
Diagnosis
Knowledge management
Nursing methodology research
Standardized nursing terminology
Enfermería
Nursing
topic Data mining
Diagnosis
Knowledge management
Nursing methodology research
Standardized nursing terminology
Enfermería
Nursing
description Taxonomic triangulation is a data mining technique for the management of care knowledge. This technique uses standardized languages, such as North American Nursing Diagnosis Association International, Nursing Outcomes Classification, and Nursing Interventions Classification, as well as logic. Its purpose is to find patterns in the data and identify care diagnoses. Triangulation can be applied to databases (clinical records) or to bibliographic sources (eg, protocols). The objective of this study is to identify the care diagnoses implicit in the nursing care protocols of the Community of Madrid. The method followed has three phases: knowledge extraction for mapping of variables, linking to diagnoses, and triangulation with analysis. The study analyzes six protocols, and 344 variables (167 assessment, 29 planning, and 148 intervention) and 6118 links have been extracted. Triangulation identified 165 NANDA diagnoses (68.48%), and only 25 labels were not revealed through this process. As a limitation, the results depend on the knowledge presented in protocols and change with language editions. Some labels included in the sample are recent and are not included in the links with nursing outcomes classification and nursing interventions classification. In conclusion, taxonomic triangulation makes it possible to manage knowledge, discover data patterns, and represent care situations.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-03-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10017/63611
https://dx.doi.org/10.1097/CIN.0000000000000662
url http://hdl.handle.net/10017/63611
https://dx.doi.org/10.1097/CIN.0000000000000662
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:e_Buah Biblioteca Digital Universidad de Alcalá
instname:Universidad de Alcalá (UAH)
instname_str Universidad de Alcalá (UAH)
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