Evidence map›Paper›PMID 42624655›Full record

ArticleBMJ supportive & palliative care2026

Ethics of artificial intelligence prognostication in palliative care: perspectives from a national survey of palliative care physicians.

Ahmed Y Alasmar, Lauren Gunn-Sandell, Stacy M Fischer, Regina M Fink, Elizabeth Juarez-Colunga, Eric G Campbell, Matthew DeCamp

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In one paragraph

Article in BMJ supportive & palliative care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ahmed Y AlasmarCenter for Bioethics and Humanities, University of Colorado Anschutz, Aurora, Colorado, USA.ORCID http://orcid.org/0000-0002-0657-7455
Lauren Gunn-SandellColorado School of Public Health, Department of Biostatistics and Informatics, University of Colorado Anschutz, Aurora, Colorado, USA.
Stacy M FischerDivision of General Internal Medicine, University of Colorado Anschutz School of Medicine, Aurora, Colorado, USA.
Regina M FinkUniversity of Colorado Anschutz School of Medicine, Aurora, Colorado, USA.
Elizabeth Juarez-ColungaColorado School of Public Health, Department of Biostatistics and Informatics, University of Colorado Anschutz, Aurora, Colorado, USA.
Eric G CampbellCenter for Bioethics and Humanities, University of Colorado Anschutz, Aurora, Colorado, USA.
Matthew DeCampCenter for Bioethics and Humanities, University of Colorado Anschutz, Aurora, Colorado, USA matthew.decamp@cuanschutz.edu.

Funding

Palliative Care Research Cooperative Group (PCRC): Refinement and ExpansionU2CNR014637 · NINR · UNIVERSITY OF COLORADO DENVER · PI HANSON, LAURA C · 2018 to 2022
$8.6M
A mixed-methods study of the nature, extent and consequences of artificial intelligence (AI) for individualized treatment planning in end-of-life and palliative care (EOLPC)R01NR019782 · NINR · UNIVERSITY OF COLORADO DENVER · PI DECAMP, MATTHEW WAYNE · 2022 to 2025
$2.6M
NINR NIH HHS R01 NR019782NINR NIH HHS U2C NR014637
6 · The paper itself

Abstract

objectivesArtificial intelligence (AI) tools have the potential to transform access to and delivery of palliative care globally-an urgent unmet need-in part by early identification of patients experiencing serious illness-related suffering. Although global consensus is emerging about the importance of ethical principles for AI, such as respecting autonomous choice, promoting patient well-being, reducing bias, trust, and more, little is known about how palliative care physicians perceive these issues. This study aims to improve understanding of palliative care physicians' perspectives about the ethics of AI-based prognostication.

methodsA national, cross-sectional survey of palliative care physicians in the USA between January 2024 and March 2025 (N=2500; overall response rate=32.6%).

resultsOverall, 64% (n=342/534) of physicians felt use of AI-based prognostication was at least somewhat ethically challenging; female physicians had 2.06 times the odds of feeling that way (95% CI 1.34 to 3.19; p=0.001). Most physicians (81.4%, 429/527) were at least a little concerned that AI-based prognostication could lead to an overemphasis on time until death in decision-making; older physician age was associated with this concern. Physicians reported moderate levels of concern with individual ethics issues, but 32.3% (170/527) thought AI could positively affect patient trust and 56.0% (294/525) thought AI could help them practise the way they see best.

conclusionPalliative care physicians see the potential of AI-based prognostication to improve palliative care and also express ethical concerns. Implementation of AI requires context-specific ethical guidance responsive to palliative care, where relationships and communication are paramount.

Indexed as

EthicsPalliative CarePrognosisTerminal Care

Identifiers

PMID42624655
PMCPMC13592454

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.