New Horizons in artificial intelligence in the healthcare of older people

Author:

Shiwani Taha12ORCID,Relton Samuel3,Evans Ruth3,Kale Aditya4,Heaven Anne12,Clegg Andrew12,Abuzour Aseel,Alderman Joseph,Anand Atul,Bhanu Cini,Bunn Jonathan,Collins Jemima,Cutillo Luisa,Hall Marlous,Keevil Victoria,Mitchell Lara,Ogliari Giulia,Penfold Rose,van Oppen James,Vardy Emma,Walesby Katherine,Wilkinson Chris,Zucker Kieran,Todd Oliver12,

Affiliation:

1. Academic Unit for Ageing & Stroke Research , Bradford Institute for Health Research, , Duckworth Lane, Bradford, West Yorkshire BD9 6RJ , UK

2. Bradford Teaching Hospitals NHS Foundation Trust , Bradford Institute for Health Research, , Duckworth Lane, Bradford, West Yorkshire BD9 6RJ , UK

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

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

Abstract

Abstract 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.

Funder

Alan Turing Institute

National Institute for Health Research Applied Research Collaboration Yorkshire & Humber

NIHR Leeds Biomedical Research Centre

Health Data Research UK

Department of Health and Social Care

Publisher

Oxford University Press (OUP)

Subject

Geriatrics and Gerontology,Aging,General Medicine

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