Digital Healthcare Ethics Laboratory (Digit-HeaL), Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia; School of Medicine, Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia.
Digital Healthcare Ethics Laboratory (Digit-HeaL), Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia.
Int J Med Inform. 2022 May;161:104738. doi: 10.1016/j.ijmedinf.2022.104738. Epub 2022 Mar 14.
Recent developments in the field of Artificial Intelligence (AI) applied to healthcare promise to solve many of the existing global issues in advancing human health and managing global health challenges. This comprehensive review aims not only to surface the underlying ethical and legal but also social implications (ELSI) that have been overlooked in recent reviews while deserving equal attention in the development stage, and certainly ahead of implementation in healthcare. It is intended to guide various stakeholders (eg. designers, engineers, clinicians) in addressing the ELSI of AI at the design stage using the Ethics by Design (EbD) approach.
The authors followed a systematised scoping methodology and searched the following databases: Pubmed, Web of science, Ovid, Scopus, IEEE Xplore, EBSCO Search (Academic Search Premier, CINAHL, PSYCINFO, APA PsycArticles, ERIC) for the ELSI of AI in healthcare through January 2021. Data were charted and synthesised, and the authors conducted a descriptive and thematic analysis of the collected data.
After reviewing 1108 papers, 94 were included in the final analysis. Our results show a growing interest in the academic community for ELSI in the field of AI. The main issues of concern identified in our analysis fall into four main clusters of impact: AI algorithms, physicians, patients, and healthcare in general. The most prevalent issues are patient safety, algorithmic transparency, lack of proper regulation, liability & accountability, impact on patient-physician relationship and governance of AI empowered healthcare.
The results of our review confirm the potential of AI to significantly improve patient care, but the drawbacks to its implementation relate to complex ELSI that have yet to be addressed. Most ELSI refer to the impact on and extension of the reciprocal and fiduciary patient-physician relationship. With the integration of AIbased decision making tools, a bilateral patient-physician relationship may shift into a trilateral one.
人工智能（AI）在医疗保健领域的最新发展有望解决在提高人类健康和应对全球健康挑战方面存在的许多现有问题。本次全面综述的目的不仅在于揭示在最近的综述中被忽视的潜在伦理、法律和社会影响（ELSI），还在于在发展阶段，当然也在医疗保健实施之前，需要对这些影响给予同等关注。本综述旨在指导各利益攸关方（如设计师、工程师、临床医生）在设计阶段通过设计伦理（EbD）方法解决 AI 的 ELSI 问题。
作者遵循系统的范围界定方法，在 2021 年 1 月前在以下数据库中搜索了有关 AI 在医疗保健中的 ELSI 的文献：Pubmed、Web of science、Ovid、Scopus、IEEE Xplore、EBSCO Search（Academic Search Premier、CINAHL、PSYCINFO、APA PsycArticles、ERIC）。数据被制成图表并进行综合分析，作者对收集的数据进行了描述性和主题分析。
在审查了 1108 篇论文后，最终有 94 篇论文被纳入分析。我们的研究结果表明，学术界对 AI 领域 ELSI 的兴趣日益浓厚。我们分析中确定的主要关注问题分为四大影响集群：AI 算法、医生、患者和医疗保健整体。最常见的问题是患者安全、算法透明度、缺乏适当监管、责任和问责制、对医患关系的影响以及 AI 赋能医疗保健的治理。
我们的综述结果证实了 AI 具有显著改善患者护理的潜力，但实施 AI 面临的缺点涉及尚未解决的复杂 ELSI。大多数 ELSI 涉及到对医患互惠和信任关系的影响和扩展。随着基于 AI 的决策工具的整合，双边医患关系可能会转变为三边关系。
