Recognising dying: Will artificial intelligence (AI) help improve clinical accuracy?

The number of people requiring palliative care in the UK is projected to rise significantly, creating an urgent need for earlier and more systematic recognition of those approaching the end of life. Current clinical markers and tools for predicting prognosis are limited in their accuracy, and prone to human and systemic biases. Artificial intelligence (AI) offers potential to improve prediction of deterioration and dying, and early studies suggest that it may support timely interventions and advance care planning. However, integration of AI must prioritise data integrity, accountability and minimising the amplification of existing inequities. Crucially, recognising dying remains a fundamentally human task with ethical, relational and existential dimensions that AI cannot replicate. Successful implementation will depend on thoughtful human–AI collaboration that strengthens clinical insight without compromising the compassionate, person-centred approach that is central to palliative care.

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Publication Details

Journal
Future Healthcare Journal
Published
2026-03-01
DOI
https://doi.org/10.1016/j.fhj.2026.100516
Citations
1
Primary Topic
Palliative Care and End-of-Life Issues
Type
article
Field-Weighted Citation Impact
41.85
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article

Recognising dying: Will artificial intelligence (AI) help improve clinical accuracy?

Simon Tavabie, Nicola White, Eleni Lester, Ollie Minton
1 citations
Future Healthcare Journal
Palliative Care and End-of-Life Issues
41.85
article

Recognising dying: Will artificial intelligence (AI) help improve clinical accuracy?

Simon Tavabie, Nicola White, Eleni Lester, Ollie Minton
article en
1 citations

Abstract

The number of people requiring palliative care in the UK is projected to rise significantly, creating an urgent need for earlier and more systematic recognition of those approaching the end of life. Current clinical markers and tools for predicting prognosis are limited in their accuracy, and prone to human and systemic biases. Artificial intelligence (AI) offers potential to improve prediction of deterioration and dying, and early studies suggest that it may support timely interventions and advance care planning. However, integration of AI must prioritise data integrity, accountability and minimising the amplification of existing inequities. Crucially, recognising dying remains a fundamentally human task with ethical, relational and existential dimensions that AI cannot replicate. Successful implementation will depend on thoughtful human–AI collaboration that strengthens clinical insight without compromising the compassionate, person-centred approach that is central to palliative care.

Future Healthcare JournalVol. 13(1)
University College London Hospitals NHS Foundation Trust (GB), Barts Health NHS Trust (GB), University Hospitals Sussex NHS Foundation Trust (GB), University College London (GB), Marie Curie (GB)
Openalex Percentile: Top 0%
Palliative Care and End-of-Life Issues
41.85
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