Organisation for Economic Co-operation and Development, Directorate for Employment Labour and Social Affairs, Paris, France.
Organisation for Economic Co-operation and Development, Directorate for Employment Labour and Social Affairs, Paris, France.
Value Health. 2022 Mar;25(3):368-373. doi: 10.1016/j.jval.2021.11.1369. Epub 2022 Jan 14.
This study aimed to showcase the potential and key concerns and risks of artificial intelligence (AI) in the health sector, illustrating its application with current examples, and to provide policy guidance for the development, assessment, and adoption of AI technologies to advance policy objectives.
Nonsystematic scan and analysis of peer-reviewed and gray literature on AI in the health sector, focusing on key insights for policy and governance.
The application of AI in the health sector is currently in the early stages. Most applications have not been scaled beyond the research setting. The use in real-world clinical settings is especially nascent, with more evidence in public health, biomedical research, and "back office" administration. Deploying AI in the health sector carries risks and hazards that must be managed proactively by policy makers. For AI to produce positive health and policy outcomes, 5 key areas for policy are proposed, including health data governance, operationalizing AI principles, flexible regulation, skills among health workers and patients, and strategic public investment.
AI is not a panacea, but a tool to address specific problems. Its successful development and adoption require data governance that ensures high-quality data are available and secure; relevant actors can access technical infrastructure and resources; regulatory frameworks promote trustworthy AI products; and health workers and patients have the information and skills to use AI products and services safely, effectively, and efficiently. All of this requires considerable investment and international collaboration.
本研究旨在展示人工智能（AI）在卫生领域的潜力和主要关注点及风险，通过当前实例说明其应用，并为 AI 技术的开发、评估和采用提供政策指导，以推进政策目标。
对卫生领域人工智能的同行评议和灰色文献进行非系统性扫描和分析，重点关注对政策和治理的关键见解。
人工智能在卫生领域的应用仍处于早期阶段。大多数应用尚未在研究环境之外得到推广。在实际临床环境中的应用尤其不成熟，在公共卫生、生物医学研究和“后台”管理方面有更多证据。在卫生部门部署人工智能存在风险和危害，政策制定者必须积极主动地加以管理。为了使人工智能产生积极的健康和政策成果，提出了 5 个政策重点领域，包括卫生数据治理、人工智能原则的实施、灵活监管、卫生工作者和患者的技能以及战略性公共投资。
人工智能不是万灵药，而是解决特定问题的工具。其成功的开发和采用需要数据治理，以确保高质量的数据可用且安全；相关参与者可以访问技术基础设施和资源；监管框架促进值得信赖的人工智能产品；卫生工作者和患者具有安全、有效和高效使用人工智能产品和服务的信息和技能。所有这一切都需要大量的投资和国际合作。
