Artificial intelligence in healthcare: a scoping review of perceived threats to patient rights and safety.

IF 3.2 3区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Nkosi Nkosi Botha, Cynthia E Segbedzi, Victor K Dumahasi, Samuel Maneen, Ruby V Kodom, Ivy S Tsedze, Lucy A Akoto, Fortune S Atsu, Obed U Lasim, Edward W Ansah
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Abstract

Background: The global health system remains determined to leverage on every workable opportunity, including artificial intelligence (AI) to provide care that is consistent with patients' needs. Unfortunately, while AI models generally return high accuracy within the trials in which they are trained, their ability to predict and recommend the best course of care for prospective patients is left to chance.

Purpose: This review maps evidence between January 1, 2010 to December 31, 2023, on the perceived threats posed by the usage of AI tools in healthcare on patients' rights and safety.

Methods: We deployed the guidelines of Tricco et al. to conduct a comprehensive search of current literature from Nature, PubMed, Scopus, ScienceDirect, Dimensions AI, Web of Science, Ebsco Host, ProQuest, JStore, Semantic Scholar, Taylor & Francis, Emeralds, World Health Organisation, and Google Scholar. In all, 80 peer reviewed articles qualified and were included in this study.

Results: We report that there is a real chance of unpredictable errors, inadequate policy and regulatory regime in the use of AI technologies in healthcare. Moreover, medical paternalism, increased healthcare cost and disparities in insurance coverage, data security and privacy concerns, and bias and discriminatory services are imminent in the use of AI tools in healthcare.

Conclusions: Our findings have some critical implications for achieving the Sustainable Development Goals (SDGs) 3.8, 11.7, and 16. We recommend that national governments should lead in the roll-out of AI tools in their healthcare systems. Also, other key actors in the healthcare industry should contribute to developing policies on the use of AI in healthcare systems.

医疗保健领域的人工智能:对患者权利和安全所受威胁的范围界定审查。
背景:全球医疗系统仍决心利用一切可行的机会,包括人工智能(AI),提供符合患者需求的医疗服务。不幸的是,虽然人工智能模型在其所训练的试验中通常具有较高的准确性,但它们为未来患者预测和推荐最佳治疗方案的能力却只能听天由命。目的:本综述对 2010 年 1 月 1 日至 2023 年 12 月 31 日期间的证据进行了梳理,这些证据涉及在医疗保健领域使用人工智能工具对患者权利和安全所造成的威胁:我们采用了 Tricco 等人的指导原则,对《自然》、PubMed、Scopus、ScienceDirect、Dimensions AI、Web of Science、Ebsco Host、ProQuest、JStore、Semantic Scholar、Taylor & Francis、Emeralds、世界卫生组织和谷歌学者中的最新文献进行了全面检索。共有 80 篇经同行评审的文章符合条件并被纳入本研究:结果:我们发现,在医疗保健领域使用人工智能技术时,确实有可能出现不可预测的错误、政策和监管制度不完善等问题。此外,在医疗保健领域使用人工智能工具时,医疗家长制、医疗保健成本增加和保险覆盖面不均、数据安全和隐私问题、偏见和歧视性服务等问题迫在眉睫:我们的研究结果对实现可持续发展目标(SDGs)3.8、11.7 和 16 有着至关重要的影响。我们建议,各国政府应率先在其医疗保健系统中推广人工智能工具。此外,医疗保健行业的其他关键参与者也应为制定在医疗保健系统中使用人工智能的政策做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Archives of Public Health
Archives of Public Health Medicine-Public Health, Environmental and Occupational Health
CiteScore
4.80
自引率
3.00%
发文量
244
审稿时长
16 weeks
期刊介绍: rchives of Public Health is a broad scope public health journal, dedicated to publishing all sound science in the field of public health. The journal aims to better the understanding of the health of populations. The journal contributes to public health knowledge, enhances the interaction between research, policy and practice and stimulates public health monitoring and indicator development. The journal considers submissions on health outcomes and their determinants, with clear statements about the public health and policy implications. Archives of Public Health welcomes methodological papers (e.g., on study design and bias), papers on health services research, health economics, community interventions, and epidemiological studies dealing with international comparisons, the determinants of inequality in health, and the environmental, behavioural, social, demographic and occupational correlates of health and diseases.
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