坦桑尼亚将生成式人工智能集成到电子病历系统中的伦理和隐私挑战:从政策角度进行范围审查。

IF 2.9 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
DIGITAL HEALTH Pub Date : 2025-05-20 eCollection Date: 2025-01-01 DOI:10.1177/20552076251344385
Augustino Mwogosi
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引用次数: 0

摘要

目的:本研究考察了将生成式人工智能(AI)集成到电子健康记录(EHR)系统中的伦理和隐私挑战,重点关注坦桑尼亚的医疗保健环境。它批判性地分析了坦桑尼亚卫生部门人工智能政策框架(2022年)在多大程度上应对这些挑战,并为负责任的生成人工智能部署提出了监管和实际保障措施。方法:系统检索PubMed、IEEE explore、Scopus和谷歌Scholar,检索2014 - 2024年间发表的相关研究。系统评价和荟萃分析扩展范围评价(PRISMA-ScR)指南的首选报告项目为搜索和选择过程提供了信息。14项研究符合纳入标准,并进行了主题分析,以确定医疗保健中生成式人工智能的关键伦理和隐私问题。此外,还对坦桑尼亚的人工智能框架进行了政策分析,以评估其与全球最佳实践和监管准备的一致性。结果:该审查确定了与EHR系统中生成人工智能相关的六个关键伦理和隐私挑战:数据隐私和安全风险、算法偏见和公平问题、透明度和问责制问题、同意和自主性挑战、人为监督差距和数据重新识别风险。政策分析显示,虽然坦桑尼亚的人工智能框架符合国家卫生优先事项,并促进了能力建设和道德治理,但它缺乏针对人工智能的衍生性指导方针、监管清晰度和卫生保健环境所需的资源调动战略。结论:将生成式人工智能集成到坦桑尼亚的电子病历系统中带来了变革机会和重大的道德和隐私风险。坦桑尼亚的政策框架应纳入特定于人工智能的道德准则,实施监管机制,通过参与式共同设计促进利益相关者的参与,并加强基础设施投资。这些措施将促进道德诚信,增强患者信任,并使坦桑尼亚成为负责任的人工智能在医疗保健领域使用方面的区域领导者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ethical and privacy challenges of integrating generative AI into EHR systems in Tanzania: A scoping review with a policy perspective.

Objectives: This study examines the ethical and privacy challenges of integrating generative artificial intelligence (AI) into electronic health record (EHR) systems, focusing on Tanzania's healthcare context. It critically analyses the extent to which Tanzania's Policy Framework for Artificial Intelligence in the Health Sector (2022) addresses these challenges and proposes regulatory and practical safeguards for responsible generative AI deployment.

Methods: A systematic scoping review was conducted using PubMed, IEEE Xplore, Scopus and Google Scholar to identify relevant studies published between 2014 and 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines informed the search and selection process. Fourteen studies met the inclusion criteria and were thematically analysed to identify key ethical and privacy concerns of generative AI in healthcare. Moreover, a policy analysis of Tanzania's AI framework was conducted to assess its alignment with global best practices and regulatory preparedness.

Results: The review identified six key ethical and privacy challenges associated with generative AI in EHR systems: data privacy and security risks, algorithmic bias and fairness concerns, transparency and accountability issues, consent and autonomy challenges, human oversight gaps and risks of data re-identification. The policy analysis revealed that while Tanzania's AI framework aligns with national health priorities and promotes capacity building and ethical governance, it lacks generative AI-specific guidelines, regulatory clarity and resource mobilisation strategies necessary for healthcare settings.

Conclusion: Integrating generative AI into Tanzania's EHR systems presents transformative opportunities and significant ethical and privacy risks. Tanzania's policy framework should incorporate AI-specific ethical guidelines, operationalise regulatory mechanisms, foster stakeholder engagement through participatory co-design and strengthen infrastructural investments. These measures will promote ethical integrity, enhance patient trust and position Tanzania as a regional leader in responsible AI use in healthcare.

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来源期刊
DIGITAL HEALTH
DIGITAL HEALTH Multiple-
CiteScore
2.90
自引率
7.70%
发文量
302
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