Evidence map›Paper›PMID 40302210›Full record

ReviewInteractive journal of medical research2025

Ethical Challenges and Opportunities of AI in End-of-Life Palliative Care: Integrative Review.

Abel García Abejas, David Geraldes Santos, Fabio Leite Costa, Aida Cordero Botejara, Helder Mota-Filipe, Àngels Salvador Vergés

Abstract readReview
In one paragraph

Review in Interactive journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
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

6 authors.

Abel García AbejasFaculty of Health Sciences, University of Beira Interior, Lisbon, Portugal.ORCID https://orcid.org/0000-0002-4115-5012
David Geraldes SantosDepartment of Communication, Philosophy and Politics, University of Beira Interior, Lisbon, Portugal.ORCID https://orcid.org/0000-0002-2241-1754
Fabio Leite CostaFaculty of Health Sciences, University of Beira Interior, Lisbon, Portugal.ORCID https://orcid.org/0000-0001-9403-8816
Aida Cordero BotejaraFaculty of Health Sciences, University of Beira Interior, Lisbon, Portugal.ORCID https://orcid.org/0009-0000-6275-3284
Helder Mota-FilipePharmacology and Health Technologies, Faculty of Pharmacy, University of Lisbon, Lisbon, Portugal.ORCID https://orcid.org/0000-0003-3045-2553
Àngels Salvador VergésBoard of Directors, Innohealth.Academy, Barcelona, Spain.ORCID https://orcid.org/0000-0001-5110-8423

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly integrated into palliative medicine, offering opportunities to improve quality, efficiency, and patient-centeredness in end-of-life care. However, its use raises complex ethical issues, including privacy, equity, dehumanization, and decision-making dilemmas.

objectiveWe aim to critically analyze the main ethical implications of AI in end-of-life palliative care and examine the benefits and risks. We propose strategies for ethical and responsible implementation.

methodsWe conducted an integrative review of studies published from 2020 to 2025 in English, Portuguese, and Spanish, identified through systematic searches in PubMed, Scopus, and Google Scholar. Inclusion criteria were studies addressing AI in palliative medicine focusing on ethical implications or patient experience. Two reviewers independently performed study selection and data extraction, resolving discrepancies by consensus. The quality of the papers was assessed using the Critical Appraisal Skills Programme checklist and the Hawker et al tool.

resultsSix key themes emerged: (1) practical applications of AI, (2) communication and AI tools, (3) patient experience and humanization, (4) ethical implications, (5) quality of life perspectives, and (6) challenges and limitations. While AI shows promise for improving efficiency and personalization, consolidated real-world examples of efficiency and equity remain scarce. Key risks include algorithmic bias, cultural insensitivity, and the potential for reduced patient autonomy.

conclusionsAI can transform palliative care, but implementation must be patient-centered and ethically grounded. Robust policies are needed to ensure equity, privacy, and humanization. Future research should address data diversity, social determinants, and culturally sensitive approaches.

Indexed as

artificial intelligence (AI)end-of-life careethical implicationspalliative medicinepatient-centred care

Identifiers

PMID40302210
PMCPMC12120364

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.