人工智能在临终关怀中的伦理挑战和机遇:综合综述。

IF 1.9 Q3 MEDICINE, RESEARCH & EXPERIMENTAL
Abel García Abejas, David Geraldes Santos, Fabio Leite Costa, Aida Cordero Botejara, Helder Mota-Filipe, Àngels Salvador Vergés
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引用次数: 0

摘要

背景:人工智能(AI)越来越多地融入姑息医学,为提高临终关怀的质量、效率和以患者为中心提供了机会。然而,它的使用引发了复杂的伦理问题,包括隐私、公平、非人性化和决策困境。目的:批判性地分析人工智能在临终关怀中的主要伦理影响,并检查其益处和风险。提出合乎道德和负责任的执行策略。方法:我们对发表于2020-2025年的英语、葡萄牙语和西班牙语的研究进行了综合回顾,这些研究是通过PubMed、Scopus和谷歌Scholar的系统搜索确定的。纳入标准是针对姑息医学中人工智能的研究,重点是伦理影响或患者体验。两位审稿人独立进行研究选择和数据提取,通过共识解决差异。使用CASP检查表和Hawker等人的工具评估文章的质量。结果:出现了六个关键主题:1)人工智能的实际应用,2)通信和人工智能工具,3)患者体验和人性化,4)伦理影响,5)生活质量观点,6)挑战和局限性。虽然人工智能有望提高效率和个性化,但在现实世界中,效率和公平的综合例子仍然很少。主要风险包括算法偏差、文化不敏感以及降低患者自主权的可能性。结论:人工智能可以改变姑息治疗,但实施必须以患者为中心,并以伦理为基础。需要强有力的政策来确保公平、隐私和人性化。未来的研究应该解决数据多样性、社会决定因素和文化敏感的方法。临床试验:
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ethical Challenges and Opportunities of AI in End-of-Life Palliative Care: Integrative Review.

Background: Artificial 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.

Objective: We 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.

Methods: We 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.

Results: Six 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.

Conclusions: AI 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.

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来源期刊
Interactive Journal of Medical Research
Interactive Journal of Medical Research MEDICINE, RESEARCH & EXPERIMENTAL-
自引率
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发文量
45
审稿时长
12 weeks
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