ORCID

Abstract

The NHS faces a crisis of increasing demand, staff shortages, and limited resources, while an ageing population places mounting pressure on acute services.1 Many experts agree that moving from a reactive “diagnose and treat” model to a more proactive “predict and prevent” model is essential.2 Predictive prevention, which applies artificial intelligence (AI) to remotely monitored data from sensors and wearables to anticipate and address early signs of decline, could shift the balance of care from hospital to community for older adults. However, these innovations carry ethical and practical risks, such as algorithmic bias, data privacy breaches, and the potential to undermine the human dimension of healthcare.The UK government has committed to move from an analogue to a digital NHS, shift more care from hospitals to communities, and be much bolder in moving from sickness to prevention.3 Achieving this ambition will require the NHS to unlock the potential of digital health technologies to support proactive, anticipatory care. Applying this technology successfully at scale will require innovative evaluation approaches to ensure that technology meets the needs of users and their carers as well as work to overcome barriers such as interoperability challenges and workforce concerns.

Publication Date

2025-04-29

Publication Title

BMJ

Volume

389

ISSN

0959-8146

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