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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Detalles Bibliográficos
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
Descripción
Sumario: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.