| 引用本文：郭一帆,郭森宇.人工智能嵌入医疗卫生服务体系的机制与路径研究基于扎根理论的政策文本分析[J].中国卫生政策研究,2025,18(7):70-77 |
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| 人工智能嵌入医疗卫生服务体系的机制与路径研究基于扎根理论的政策文本分析 |
| 投稿时间：2025-06-19 修订日期：2025-07-15 PDF全文浏览 HTML全文浏览 |
| 郭一帆，郭森宇 |
| 中国人民大学公共管理学院 北京 100872 |
| 摘要:人工智能正加速推动医疗卫生服务体系的数字化转型，政策体系在技术创新与治理变革中的引导作用日益突出。然而，人工智能技术如何在多元政策目标与工具协同下实现深度嵌入，尚缺乏系统性理论解释。本文基于2015—2025年我国人工智能医疗卫生领域的国家级政策文本，运用扎根理论，提出“政策目标—政策工具—嵌入路径”分析框架，系统揭示人工智能医疗技术嵌入路径的阶段性演进及其内在机制。研究发现：一是我国人工智能医疗卫生政策体系经历了战略引导、场景驱动到规范治理的阶段递进，体现出政策对高复杂性技术嵌入的动态适应；二是政策目标与工具之间形成了动态耦合机制，实现了技术创新、风险治理与社会价值的协同平衡；三是技术嵌入路径由外源性的关系型嵌入向内生性的结构型嵌入演进，呈现出“制度赋权—结构耦合—规制内化”的递进机制。本研究深化了对高复杂性技术治理适应性与制度化转型的理论阐释，为优化人工智能医疗卫生政策与提升政府数字治理能力提供了理论借鉴与实践参考。 |
| 关键词:人工智能 医疗卫生服务体系 政策工具 技术嵌入 扎根理论 |
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| Mechanisms and pathways of artificial intelligence embedding into the healthcare service system：A grounded theory-based policy text analysis |
| GUO Yi-fan, GUO Sen-yu |
| School of Public Administration and Policy， Renmin University of China， Beijing 100872， China |
| Abstract:Artificial intelligence （AI） is accelerating the digital transformation of the healthcare service system， with policy systems playing an increasingly prominent role in guiding technological innovation and governance reform. However， there is still a lack of systematic theoretical explanation for how AI technologies achieve deep integration under the collaborative effect of diverse policy objectives and policy tools. Drawing on national-level AI healthcare policy texts in China from 2015 to 2025， this study proposes an analytical framework of "policy goals-policy instruments-embedding pathways". It systematically reveals the staged evolution and underlying mechanisms of AI technology integration in healthcare. The findings show： first， China's AI healthcare policy system has progressed from strategic guidance and scenario-driven development to regulatory governance， demonstrating a dynamic adaptability to the integration of complex technologies； second， a dynamic coupling mechanism has formed between policy goals and instruments， achieving a coordinated balance among technological innovation， risk governance， and social value； third， the embedding pathway has evolved from exogenous， relationship-based integration to endogenous， structure-based integration， characterized by a progressive mechanism of "institutional empowerment-structural coupling-regulatory internalization". This research deepens the theoretical understanding of adaptive governance and institutional transformation for complex technologies， offering theoretical insights and practical references for optimizing AI healthcare policies and enhancing digital governance capacity. |
| Key words:Artificial intelligence Healthcare service system Policy tools Technological embedding Grounded theory |
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