Artificial intelligence for falls management in older adult care: A scoping review of nurses' role.
artificial intelligence
falls
machine learning
natural language processing
nursing
Journal
Journal of nursing management
ISSN: 1365-2834
Titre abrégé: J Nurs Manag
Pays: England
ID NLM: 9306050
Informations de publication
Date de publication:
Nov 2022
Nov 2022
Historique:
revised:
29
08
2022
received:
02
06
2022
accepted:
30
09
2022
pubmed:
6
10
2022
medline:
30
12
2022
entrez:
5
10
2022
Statut:
ppublish
Résumé
This study aims to synthesize evidence on nurses' involvement in artificial intelligence research for managing falls in older adults. Artificial intelligence techniques are used to analyse health datasets to aid clinical decision making, patient care and service delivery but nurses' involvement in this area of research for managing falls in older adults remains unknown. A scoping review was conducted. CINAHL, the Cochrane Library, Embase, MEDLI and PubMed were searched. Results were screened against inclusion criteria. Relevant data were extracted, and studies summarized using a descriptive approach. The evidence shows many artificial intelligence techniques, particularly machine learning, are used to identify falls risk factors and build predictive models that could help prevent falls in older adults, with nurses leading and participating in this research. Further rigorous experimental research is needed to determine the effectiveness of algorithms in predicting aspects of falls in older adults and how to implement artificial intelligence tools in gerontological nursing practice. Nurses should pursue interdisciplinary collaborations and educational opportunities in artificial intelligence, so they can actively contribute to research on falls management. Nurses should facilitate the collection of digital falls datasets to support this emerging research agenda and the care of older adults.
Sections du résumé
AIM
OBJECTIVE
This study aims to synthesize evidence on nurses' involvement in artificial intelligence research for managing falls in older adults.
BACKGROUND
BACKGROUND
Artificial intelligence techniques are used to analyse health datasets to aid clinical decision making, patient care and service delivery but nurses' involvement in this area of research for managing falls in older adults remains unknown.
EVALUATION
RESULTS
A scoping review was conducted. CINAHL, the Cochrane Library, Embase, MEDLI and PubMed were searched. Results were screened against inclusion criteria. Relevant data were extracted, and studies summarized using a descriptive approach.
KEY ISSUES
RESULTS
The evidence shows many artificial intelligence techniques, particularly machine learning, are used to identify falls risk factors and build predictive models that could help prevent falls in older adults, with nurses leading and participating in this research.
CONCLUSION
CONCLUSIONS
Further rigorous experimental research is needed to determine the effectiveness of algorithms in predicting aspects of falls in older adults and how to implement artificial intelligence tools in gerontological nursing practice.
IMPLICATIONS FOR NURSING MANAGEMENT
CONCLUSIONS
Nurses should pursue interdisciplinary collaborations and educational opportunities in artificial intelligence, so they can actively contribute to research on falls management. Nurses should facilitate the collection of digital falls datasets to support this emerging research agenda and the care of older adults.
Identifiants
pubmed: 36197748
doi: 10.1111/jonm.13853
pmc: PMC10092211
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
3787-3801Informations de copyright
© 2022 The Authors. Journal of Nursing Management published by John Wiley & Sons Ltd.
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