New Horizons in artificial intelligence in the healthcare of older people.

ageing artificial intelligence health older people technology

Journal

Age and ageing
ISSN: 1468-2834
Titre abrégé: Age Ageing
Pays: England
ID NLM: 0375655

Informations de publication

Date de publication:
01 Dec 2023
Historique:
received: 12 05 2023
medline: 21 12 2023
pubmed: 21 12 2023
entrez: 21 12 2023
Statut: ppublish

Résumé

Artificial intelligence (AI) in healthcare describes algorithm-based computational techniques which manage and analyse large datasets to make inferences and predictions. There are many potential applications of AI in the care of older people, from clinical decision support systems that can support identification of delirium from clinical records to wearable devices that can predict the risk of a fall. We held four meetings of older people, clinicians and AI researchers. Three priority areas were identified for AI application in the care of older people. These included: monitoring and early diagnosis of disease, stratified care and care coordination between healthcare providers. However, the meetings also highlighted concerns that AI may exacerbate health inequity for older people through bias within AI models, lack of external validation amongst older people, infringements on privacy and autonomy, insufficient transparency of AI models and lack of safeguarding for errors. Creating effective interventions for older people requires a person-centred approach to account for the needs of older people, as well as sufficient clinical and technological governance to meet standards of generalisability, transparency and effectiveness. Education of clinicians and patients is also needed to ensure appropriate use of AI technologies, with investment in technological infrastructure required to ensure equity of access.

Identifiants

pubmed: 38124256
pii: 7479755
doi: 10.1093/ageing/afad219
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Alan Turing Institute
Organisme : National Institute for Health Research Applied Research Collaboration Yorkshire & Humber
Organisme : NIHR Leeds Biomedical Research Centre
Organisme : Health Data Research UK
Organisme : Department of Health and Social Care

Investigateurs

Aseel Abuzour (A)
Joseph Alderman (J)
Atul Anand (A)
Cini Bhanu (C)
Jonathan Bunn (J)
Jemima Collins (J)
Luisa Cutillo (L)
Marlous Hall (M)
Victoria Keevil (V)
Lara Mitchell (L)
Giulia Ogliari (G)
Rose Penfold (R)
James van Oppen (J)
Emma Vardy (E)
Katherine Walesby (K)
Chris Wilkinson (C)
Kieran Zucker (K)

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society.

Auteurs

Taha Shiwani (T)

Academic Unit for Ageing & Stroke Research, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Duckworth Lane, Bradford, West Yorkshire BD9 6RJ, UK.

Samuel Relton (S)

Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.

Ruth Evans (R)

Leeds Institute of Health Sciences, University of Leeds, Leeds, UK.

Aditya Kale (A)

Academic Unit of Ophthalmology, Institute of Inflammation & Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.

Anne Heaven (A)

Academic Unit for Ageing & Stroke Research, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Duckworth Lane, Bradford, West Yorkshire BD9 6RJ, UK.

Andrew Clegg (A)

Academic Unit for Ageing & Stroke Research, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Duckworth Lane, Bradford, West Yorkshire BD9 6RJ, UK.

Oliver Todd (O)

Academic Unit for Ageing & Stroke Research, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Duckworth Lane, Bradford, West Yorkshire BD9 6RJ, UK.

Classifications MeSH