从整合照护到学习型系统
From Integrated Care to Learning Systems.
摘要(中文译文)
整合型医疗正日益受到数字基础设施、数据治理和人工智能赋能分析技术的影响，但相关文献分散于卫生服务研究、数字健康和机器学习等领域。本文报告了一项范围综述，依照PRISMA-ScR指南开展，旨在描绘整合型医疗模式在概念上如何演变、有哪些数字和人工智能赋能的基础设施为其提供支持、如何评估其临床、经济和公平性影响，以及当前实施情况对可持续推广意味着什么。我们检索了PubMed、Scopus、Semantic Scholar和Crossref（检索日期为2025年10月31日；向前筛选至2026年3月31日），并补充了来自指定政策机构的灰色文献。检索共识别出15，189条记录，经来源内和跨来源去重及灰色文献整合后减少至11，789条；评估了620篇全文，最终192篇纳入综合。综合形成四个领域：整合型医疗的概念基础、人工智能与多模态分析、实施障碍以及数字治理基础。我们采用I-V型成熟度方案（疾病、队列、全系统、数字整合、学习型）描绘该领域，并以Rainbow、MacColl、EMRAM/AMAM和NHS ICS模型作为基准。大多数部署集中在数字整合但适应性较弱的IV型；反复出现的失败模式——时间盲区、维护债务、语义漂移和治理缺口——阻碍了向V型的推进，而备受关注的临床人工智能失败案例则说明了在IV型或更差基础设施上尝试V型分析所需付出的代价。对九个世界区域的逐一梳理将各区域映射至其当前的I-V型位置，并表明组织和支付整合——而非仅靠数字精密程度——目前是进步的主导驱动力。COMFORTage整合型医疗模式库被定位为一个由人工智能代理组成的工作流，在整合型医疗全生命周期中协调预测性、预防性和个性化照护，而非作为一个单一的联邦学习项目。本综述将人工智能赋能的整合型医疗定位为并非一个已完成的模式，而是一个新兴的设计空间，需要纵向数据资产、受管理的模型生命周期、可问责的治理以及基于结果的合同，以构建具有临床实用性、公平且可信的学习型系统。
Abstract
Integrated care is increasingly shaped by digital infrastructures, data governance, and AI-enabled analytics, yet the relevant literature remains fragmented across health-services research, digital health, and machine learning. This article reports a scoping review, conducted in line with PRISMA-ScR guidance, that maps how integrated care models have evolved conceptually, what digital and AI-enabled infrastructures support them, how their clinical, economic, and equity impacts can be evaluated, and what current implementations imply for sustainable scaling. We searched PubMed, Scopus, Semantic Scholar, and Crossref (retrieval date 31 October 2025; forward screening to 31 March 2026) and added grey literature from named policy bodies. The searches identified 15,189 records, reducing to 11,789 after intra- and cross-source deduplication and grey-literature integration; 620 full texts were assessed and 192 were included in the synthesis. Four domains were synthesised: conceptual foundations of integrated care, AI and multimodal analytics, implementation barriers, and digital-governance foundations. We chart the field using a Type I-V maturity scheme (disease, cohort, whole-system, digital-integrated, learning), benchmarked against the Rainbow, MacColl, EMRAM/AMAM, and NHS ICS models. Most deployments cluster at digitally integrated but only weakly adaptive Type IV; recurrent failure modes-temporal blind spots, maintenance debt, semantic drift, and governance gaps-block progression to Type V, and high-profile clinical-AI failures illustrate the cost of attempting Type V analytics on Type IV-or-worse infrastructure. A walk through nine world regions maps each to its current Type I-V position and shows that organisational and payment integration-not digital sophistication alone-is currently the dominant driver of progress. The COMFORTage Integrated Care Model Library is positioned as a workflow of AI agents orchestrating predictive, preventive, and personalised care across the integrated-care lifecycle rather than as a single federated-learning programme. The review positions AI-enabled integrated care less as a finished model than as an emerging design space requiring longitudinal data assets, stewarded model lifecycles, accountable governance, and outcome-based contracting for clinically useful, equitable, and trustworthy learning systems.
如何引用
AMA
Aristeidis Tsitiridis, Konstantinos Perakis, Athos Antoniades, George Manias. From Integrated Care to Learning Systems.. Healthcare (Basel, Switzerland). 2026; doi:10.3390/healthcare14121612.
APA
Aristeidis Tsitiridis, Konstantinos Perakis, Athos Antoniades, George Manias (2026). From Integrated Care to Learning Systems.. Healthcare (Basel, Switzerland). https://doi.org/10.3390/healthcare14121612
GB/T 7714
Aristeidis Tsitiridis, Konstantinos Perakis, Athos Antoniades, George Manias. From Integrated Care to Learning Systems.[J]. Healthcare (Basel, Switzerland), 2026 doi:10.3390/healthcare14121612.
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