Implementation of an Artificial Intelligence Algorithm for sepsis detection

Detalhes bibliográficos
Autor(a) principal: Gonçalves,Luciana Schleder
Data de Publicação: 2020
Outros Autores: Amaro,Maria Luiza de Medeiros, Romero,Andressa de Lima Miranda, Schamne,Fernanda Karoline, Fressatto,Jacson Luiz, Bezerra,Carolina Wrobel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Enfermagem (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672020000300502
Resumo: ABSTRACT Objectives: to present the nurses’ experience with technological tools to support the early identification of sepsis. Methods: experience report before and after the implementation of artificial intelligence algorithms in the clinical practice of a philanthropic hospital, in the first half of 2018. Results: describe the motivation for the creation and use of the algorithm; the role of the nurse in the development and implementation of this technology and its effects on the nursing work process. Final Considerations: technological innovations need to contribute to the improvement of professional practices in health. Thus, nurses must recognize their role in all stages of this process, in order to guarantee safe, effective and patient-centered care. In the case presented, the participation of the nurses in the technology incorporation process enables a rapid decision-making in the early identification of sepsis.
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spelling Implementation of an Artificial Intelligence Algorithm for sepsis detectionGuideline AdherenceNursing InformaticsArtificial IntelligenceSepsisDecision makingABSTRACT Objectives: to present the nurses’ experience with technological tools to support the early identification of sepsis. Methods: experience report before and after the implementation of artificial intelligence algorithms in the clinical practice of a philanthropic hospital, in the first half of 2018. Results: describe the motivation for the creation and use of the algorithm; the role of the nurse in the development and implementation of this technology and its effects on the nursing work process. Final Considerations: technological innovations need to contribute to the improvement of professional practices in health. Thus, nurses must recognize their role in all stages of this process, in order to guarantee safe, effective and patient-centered care. In the case presented, the participation of the nurses in the technology incorporation process enables a rapid decision-making in the early identification of sepsis.Associação Brasileira de Enfermagem2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672020000300502Revista Brasileira de Enfermagem v.73 n.3 2020reponame:Revista Brasileira de Enfermagem (Online)instname:Associação Brasileira de Enfermagem (ABEN)instacron:ABEN10.1590/0034-7167-2018-0421info:eu-repo/semantics/openAccessGonçalves,Luciana SchlederAmaro,Maria Luiza de MedeirosRomero,Andressa de Lima MirandaSchamne,Fernanda KarolineFressatto,Jacson LuizBezerra,Carolina Wrobeleng2020-04-07T00:00:00Zoai:scielo:S0034-71672020000300502Revistahttp://www.scielo.br/rebenhttps://old.scielo.br/oai/scielo-oai.phpreben@abennacional.org.br||telma.garcia@abennacional.org.br|| editorreben@abennacional.org.br1984-04460034-7167opendoar:2020-04-07T00:00Revista Brasileira de Enfermagem (Online) - Associação Brasileira de Enfermagem (ABEN)false
dc.title.none.fl_str_mv Implementation of an Artificial Intelligence Algorithm for sepsis detection
title Implementation of an Artificial Intelligence Algorithm for sepsis detection
spellingShingle Implementation of an Artificial Intelligence Algorithm for sepsis detection
Gonçalves,Luciana Schleder
Guideline Adherence
Nursing Informatics
Artificial Intelligence
Sepsis
Decision making
title_short Implementation of an Artificial Intelligence Algorithm for sepsis detection
title_full Implementation of an Artificial Intelligence Algorithm for sepsis detection
title_fullStr Implementation of an Artificial Intelligence Algorithm for sepsis detection
title_full_unstemmed Implementation of an Artificial Intelligence Algorithm for sepsis detection
title_sort Implementation of an Artificial Intelligence Algorithm for sepsis detection
author Gonçalves,Luciana Schleder
author_facet Gonçalves,Luciana Schleder
Amaro,Maria Luiza de Medeiros
Romero,Andressa de Lima Miranda
Schamne,Fernanda Karoline
Fressatto,Jacson Luiz
Bezerra,Carolina Wrobel
author_role author
author2 Amaro,Maria Luiza de Medeiros
Romero,Andressa de Lima Miranda
Schamne,Fernanda Karoline
Fressatto,Jacson Luiz
Bezerra,Carolina Wrobel
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Gonçalves,Luciana Schleder
Amaro,Maria Luiza de Medeiros
Romero,Andressa de Lima Miranda
Schamne,Fernanda Karoline
Fressatto,Jacson Luiz
Bezerra,Carolina Wrobel
dc.subject.por.fl_str_mv Guideline Adherence
Nursing Informatics
Artificial Intelligence
Sepsis
Decision making
topic Guideline Adherence
Nursing Informatics
Artificial Intelligence
Sepsis
Decision making
description ABSTRACT Objectives: to present the nurses’ experience with technological tools to support the early identification of sepsis. Methods: experience report before and after the implementation of artificial intelligence algorithms in the clinical practice of a philanthropic hospital, in the first half of 2018. Results: describe the motivation for the creation and use of the algorithm; the role of the nurse in the development and implementation of this technology and its effects on the nursing work process. Final Considerations: technological innovations need to contribute to the improvement of professional practices in health. Thus, nurses must recognize their role in all stages of this process, in order to guarantee safe, effective and patient-centered care. In the case presented, the participation of the nurses in the technology incorporation process enables a rapid decision-making in the early identification of sepsis.
publishDate 2020
dc.date.none.fl_str_mv 2020-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672020000300502
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-71672020000300502
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0034-7167-2018-0421
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Associação Brasileira de Enfermagem
publisher.none.fl_str_mv Associação Brasileira de Enfermagem
dc.source.none.fl_str_mv Revista Brasileira de Enfermagem v.73 n.3 2020
reponame:Revista Brasileira de Enfermagem (Online)
instname:Associação Brasileira de Enfermagem (ABEN)
instacron:ABEN
instname_str Associação Brasileira de Enfermagem (ABEN)
instacron_str ABEN
institution ABEN
reponame_str Revista Brasileira de Enfermagem (Online)
collection Revista Brasileira de Enfermagem (Online)
repository.name.fl_str_mv Revista Brasileira de Enfermagem (Online) - Associação Brasileira de Enfermagem (ABEN)
repository.mail.fl_str_mv reben@abennacional.org.br||telma.garcia@abennacional.org.br|| editorreben@abennacional.org.br
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