Contributions of Artificial Intelligence to Decision Making in Nursing: A Scoping Review Protocol.

artificial intelligence decision making nursing protocol review

Journal

Nursing reports (Pavia, Italy)
ISSN: 2039-4403
Titre abrégé: Nurs Rep
Pays: Switzerland
ID NLM: 101592662

Informations de publication

Date de publication:
06 Jan 2023
Historique:
received: 22 11 2022
revised: 29 12 2022
accepted: 03 01 2023
entrez: 17 1 2023
pubmed: 18 1 2023
medline: 18 1 2023
Statut: epublish

Résumé

Artificial intelligence (AI) techniques and methodologies for problem solving are emerging as formal tools essential to assist in nursing care. Given their potential to improve workflows and to guide decision making, several studies have been developed; however, little is known about their impact, particularly on decision making. The aim of this study was to map the existing research on the use of AI in decision making in nursing. With this review protocol, we aimed to map the existing research on the use of AI in nursing decision making. A scoping review was conducted following the framework proposed by the Joanna Briggs Institute (JBI). The search strategy was tailored to each database/repository to identify relevant studies. The contained articles were the targets of the data extraction, which was conducted by two independent researchers. In the event of discrepancies, a third researcher was consulted. This review included quantitative, qualitative and mixed method studies. Primary studies, systematic reviews, dissertations, opinion texts and gray literature were considered according to the three steps that the JBI has defined for scoping reviews. This scoping review synthesized knowledge that could help advance new scientific developments and find significant and valuable outcomes for patients, caregivers and leaders in decision making. This review was also intended to encourage the development of research lines that may be useful for the development of AI tools for decision making.

Sections du résumé

BACKGROUND BACKGROUND
Artificial intelligence (AI) techniques and methodologies for problem solving are emerging as formal tools essential to assist in nursing care. Given their potential to improve workflows and to guide decision making, several studies have been developed; however, little is known about their impact, particularly on decision making.
OBJECTIVE OBJECTIVE
The aim of this study was to map the existing research on the use of AI in decision making in nursing. With this review protocol, we aimed to map the existing research on the use of AI in nursing decision making.
METHODS METHODS
A scoping review was conducted following the framework proposed by the Joanna Briggs Institute (JBI). The search strategy was tailored to each database/repository to identify relevant studies. The contained articles were the targets of the data extraction, which was conducted by two independent researchers. In the event of discrepancies, a third researcher was consulted.
RESULTS RESULTS
This review included quantitative, qualitative and mixed method studies. Primary studies, systematic reviews, dissertations, opinion texts and gray literature were considered according to the three steps that the JBI has defined for scoping reviews.
CONCLUSIONS CONCLUSIONS
This scoping review synthesized knowledge that could help advance new scientific developments and find significant and valuable outcomes for patients, caregivers and leaders in decision making. This review was also intended to encourage the development of research lines that may be useful for the development of AI tools for decision making.

Identifiants

pubmed: 36648981
pii: nursrep13010007
doi: 10.3390/nursrep13010007
pmc: PMC9844284
doi:

Types de publication

Journal Article

Langues

eng

Pagination

67-72

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Auteurs

Filipe Fernandes (F)

Institute of Health Sciences, Center for Interdisciplinary Research in Health (CIIS), Escola Superior de Saúde do Vale do Ave-Instituto Politécnico de Saúde do Norte, Vila Nova de Famalicão, Universidade Católica Portuguesa, 4169-005 Porto, Portugal.

Paulo Santos (P)

Institute of Health Sciences, Center for Interdisciplinary Health Research (CIIS), Escola Superior de Saúde da Cruz Vermelha Portuguesa, 1300-125 Lisboa, Portugal.

Luís Sá (L)

Institute of Health Sciences, Center for Interdisciplinary Research in Health (CIIS), Universidade Católica Portuguesa, 4169-005 Porto, Portugal.

José Neves (J)

Research Unit on Artificial Intelligence & Health, Algoritmi Centre, University of Minho, 4710-057 Braga, Portugal.

Classifications MeSH