Artificial Intelligence in the Organization of Nursing Care: A Scoping Review

Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing c...

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Published inNursing reports (Pavia, Italy) Vol. 14; no. 4; pp. 2733 - 2745
Main Authors Ventura-Silva, João, Martins, Maria Manuela, Trindade, Letícia de Lima, Faria, Ana da Conceição Alves, Pereira, Soraia, Zuge, Samuel Spiegelberg, Ribeiro, Olga Maria Pimenta Lopes
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 01.12.2024
MDPI
Subjects
Artificial intelligence
Automation
Decision making
Evidence-based medicine
Medical care
nurse administration
nursing
Nursing care
organization and administration
patient care management
Professional development
Quality management
Review
Portugal
nurse administration
nursing
organization and administration
patient care management
artificial intelligence
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Abstract Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care. Methods: A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus® databases. We used ProQuest—Dissertations and Theses to search gray literature. Results: Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development. Conclusions: AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
AbstractList Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care. Methods: A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus ® databases. We used ProQuest—Dissertations and Theses to search gray literature. Results: Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development. Conclusions: AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care. Methods: A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus[sup.®] databases. We used ProQuest—Dissertations and Theses to search gray literature. Results: Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development. Conclusions: AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care.BACKGROUNDThe integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care.A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus® databases. We used ProQuest-Dissertations and Theses to search gray literature.METHODSA scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus® databases. We used ProQuest-Dissertations and Theses to search gray literature.Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development.RESULTSTen studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development.AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.CONCLUSIONSAI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care. Methods: A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus® databases. We used ProQuest—Dissertations and Theses to search gray literature. Results: Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development. Conclusions: AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to ensure quality of care. The aim is to synthesize the evidence on the use of artificial intelligence in the organization of nursing care. A scoping review was carried out based on the Joanna Briggs Institute methodology, following the PRISMA-ScR guidelines, in the MEDLINE, CINAHL Complete, Business Source Ultimate and Scopus databases. We used ProQuest-Dissertations and Theses to search gray literature. Ten studies were evaluated, identifying AI-mediated tools used in the organization of nursing care, and synthesized into three tool models, namely monitoring and prediction, decision support, and interaction and communication technologies. The contributions of using these tools in the organization of nursing care include improvements in operational efficiency, decision support and diagnostic accuracy, advanced interaction and efficient communication, logistical support, workload relief, and ongoing professional development. AI tools such as automated alert systems, predictive algorithms, and decision support transform nursing by increasing efficiency, accuracy, and patient-centered care, improving communication, reducing errors, and enabling earlier interventions with safer and more efficient quality care.
Audience Academic
Author Martins, Maria Manuela
Faria, Ana da Conceição Alves
Trindade, Letícia de Lima
Pereira, Soraia
Zuge, Samuel Spiegelberg
Ventura-Silva, João
Ribeiro, Olga Maria Pimenta Lopes
AuthorAffiliation 5 Grouping of Health Centers Ave/Famalicão, 4760-412 Vila Nova de Famalicão, Portugal
3 CINTESIS@RISE, 4200-450 Porto, Portugal; olgaribeiro@esenf.pt
4 Department of Nursing, Community University of the Chapecó Region (Unochapecó), Chapecó 89809-900, Brazil; leticia.trindade@udesc.br (L.d.L.T.); samuel.zuge@unochapeco.edu.br (S.S.Z.)
1 Abel Salazar Institute of Biomedical Sciences, 4050-313 Porto, Portugal; mmmartins@icbas.up.pt (M.M.M.); acafaria@ulsmave.min-saude.pt (A.d.C.A.F.); soraia.pereira@essnortecvp.pt (S.P.)
2 Northern Health School of the Portuguese Red Cross, 3720-126 Oliveira de Azeméis, Portugal
6 Nursing School of Porto (ESEP), 4200-072 Porto, Portugal
AuthorAffiliation_xml – name: 5 Grouping of Health Centers Ave/Famalicão, 4760-412 Vila Nova de Famalicão, Portugal
– name: 4 Department of Nursing, Community University of the Chapecó Region (Unochapecó), Chapecó 89809-900, Brazil; leticia.trindade@udesc.br (L.d.L.T.); samuel.zuge@unochapeco.edu.br (S.S.Z.)
– name: 1 Abel Salazar Institute of Biomedical Sciences, 4050-313 Porto, Portugal; mmmartins@icbas.up.pt (M.M.M.); acafaria@ulsmave.min-saude.pt (A.d.C.A.F.); soraia.pereira@essnortecvp.pt (S.P.)
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/39449439$$D View this record in MEDLINE/PubMed
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crossref_primary_10_1016_j_ajic_2025_03_003
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Issue 4
Keywords nurse administration
nursing
organization and administration
patient care management
artificial intelligence
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Snippet Background: The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative...
The integration of artificial intelligence (AI) in the organization of nursing care has continually evolved, driven by the need for innovative solutions to...
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SubjectTerms Artificial intelligence
Automation
Decision making
Evidence-based medicine
Medical care
nurse administration
nursing
Nursing care
organization and administration
patient care management
Professional development
Quality management
Review
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Title Artificial Intelligence in the Organization of Nursing Care: A Scoping Review
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