Core Viewpoint - The launch of the public hospital reform and high-quality development demonstration project in Xicheng District, Beijing aims to enhance healthcare services through the integration of artificial intelligence and digital technologies in medical practices [1][2] Group 1: Project Overview - The demonstration project will be implemented over three years, focusing on collaborative governance in healthcare, hierarchical diagnosis and treatment, comprehensive reform of public hospitals, and the empowerment of digital technology [1] - The project aims to create replicable and promotable "Xicheng experience" to improve regional healthcare service levels [1] Group 2: Key Tasks and Measures - The implementation plan includes four major tasks and 13 reform measures, emphasizing the sharing of medical resources and the establishment of four centers: medical imaging, testing, pathology, and telemedicine [1] - A "one bed for the entire district" sharing mechanism will be explored, along with pilot programs for unified procurement of drugs, consumables, and equipment to achieve cost reduction and efficiency [1] Group 3: Hospital Development - The project will clarify the functional positioning of district hospitals through "one hospital, one policy" and promote key renovation projects like the revitalization of hospitals and standardized construction of community health service centers [1] - There will be a focus on strengthening specialties in traditional Chinese medicine, rehabilitation, and addressing shortages in geriatrics, pediatrics, psychiatry, and infectious diseases [1] Group 4: Digital Integration - The initiative will deepen the integration of digital technologies, establishing a unified platform for district hospitals, community health, public health, and health information to eliminate information barriers [2] - The project will provide smart health monitoring devices for the elderly and key chronic disease populations, facilitating proactive and continuous health management [2]

习近平总书记强调，"要加强人工智能同保障和改善民生的结合，从保障和改善民生、为人民创造 美好生活的需要出发，推动人工智能在人们日常工作、学习、生活中的深度运用，创造更加智能的工作 方式和生活方式"。这意味着要抓住民生领域痛点问题，加强人工智能在医疗、教育、养老等关系群众 切身利益的重点领域深度应用，促进全体人民共享人工智能发展成果。这不仅体现了以人民为中心的发 展思想，也对更好利用人工智能提高人民生活品质、打造更有温度的智能社会具有重要意义。 当前，人工智能正迈入与经济社会深度融合的新阶段。其发展成效不仅取决于技术突破，更关键在 于是否符合社会需求、能否真正增进人民福祉。同时，智能社会亦是推动现代化建设的重要支撑。在伦 理导向、安全可控与人机协同的框架下，唯有坚守"温度"底色，避免技术异化，才能更好确保智能社会 发展始终沿着正确方向前进。 坚持人工智能发展与民生紧密融合，打造更具温度的智能社会，既有技术基础，也有现实需求。一 是有助于推动人工智能的技术价值真正落地。前沿技术的重要价值，在于其对现实需求的响应与满足。 推动人工智能与民生结合，本质上是引导技术从实验室和研究前沿走向民生现场，在解决教育、医疗、 养 ...

智通财经APP获悉，国金证券发布研报称，2025年部分左侧板块如眼科及齿科等景气度有所改善，随着 医药健康行业价格战及集采风险的逐步出清，2026年医疗服务板块景气度有望迎来反转，建议关注板块 整体的估值修复机会。 国金证券主要观点如下： 近年，行业进入了以内涵式增长和格局优化为特征的成熟发展期 宏观层面，国家《关于促进服务消费高质量发展的意见》等顶层设计，为行业的长足发展提供了坚实的 政策土壤。在中观产业层面，供需关系的再平衡成为了主旋律。供给侧，经过近几年的市场洗牌，大量 抗风险能力较弱的中小医疗机构逐渐退出，行业集中度被动提升，这为头部企业在存量市场中获取更多 份额创造了机遇。微观业绩层面，2025年头部企业的增长更多来自于经营效率的提升和市场份额的巩 固。该行维持对连锁医疗业态的成长空间与发展逻辑的看好判断。后资本扩张时代下，该行持续看好优 质资产属性突出，内生增长优秀，品牌力强，上下游议价能力突出，扩张战略清晰，具有持续强化竞争 壁垒能力的公司。 风险提示 集采风险、居民消费意愿复苏不及预期风险、医疗事故及突发舆情风险、并购整合不及预期的风险、 AI技术商业化落地不及预期风险等。 细分领域上，核心赛 ...

报告导读： 国家医保局印发《病理类医疗服务价格项目立项指南（试行）》，有望规范人 工智能辅助诊断市场。 12 月 19 日，国家医保局印发《病理类医疗服务价格项目立项指南（试行）》，我们认为人工智能辅助诊断市场有望更加规范，给予所处医疗器械行业增持 评级。 为贯彻落实《深化医疗服务价格改革试点方案》，推进全国医疗服务价格项目规范编制工作，按照"成熟一批、发布一批"的工作思路， 2025 年 12 月 19 日，国家医保局编制印发了《病理类医疗服务价格项目立项指南（试行）》，将已有价格项目规范整合为 28 项、加收项 3 项、扩展项 2 项。下一步，国家 医保局将指导各省医保局参考《病理类医疗服务价格项目立项指南（试行）》，制定全省统一的价格基准，由具有价格管理权限的统筹地区对照全省价格基 准，上下浮动确定实际执行的价格水平。 《病理类医疗服务价格项目立项指南（试行）》中的第一项及第二项，病理诊断费及病理诊断费（远程）中，明确规定扩展项【人工智能辅助诊断】，价格构 成为所定价格涵盖病理样本接收、判读、诊断、人工智能辅助诊断、出具报告并上传等步骤所需的人力资源和基本物质资源消耗。 以上内容节选自国泰海通证券已发布 ...

Investment Rating - The report assigns an "Accumulate" rating to the medical device industry, indicating a positive outlook for investment opportunities [4]. Core Insights - The National Healthcare Security Administration (NHSA) issued the "Guidelines for the Project Establishment of Pathology Medical Service Pricing (Trial)," which is expected to standardize the artificial intelligence-assisted diagnosis market [2][4]. - The guidelines consolidate existing pricing projects into 28 items, with 3 additional charges and 2 expansion items, aiming to create a unified pricing standard across provinces [4]. - The inclusion of "AI-assisted diagnosis" as an expansion item in the pricing guidelines is anticipated to regulate the market and stimulate research and development in the industry [4]. Summary by Sections - **Policy Implementation**: The NHSA's guidelines are part of a broader initiative to reform medical service pricing, promoting a structured approach to pricing in pathology services [4]. - **Pricing Structure**: The guidelines specify that the pricing for pathology diagnosis includes costs associated with sample reception, interpretation, diagnosis, AI assistance, and report generation [4]. - **Digital Transformation**: The requirement for medical institutions to upload pathology reports and digital images is expected to drive the adoption of digital technologies and facilitate nationwide sharing of diagnostic results [4].

（来源：新安晚报） 转自：新安晚报 国家医保局12月19日发布《病理类医疗服务价格项目立项指南（试行）》，明确将"人工智能辅助诊 断"列为病理诊断的扩展项，将人工智能辅助诊断纳入病理诊断价格项目的价格构成。 为推动人工智能在病理领域的应用，立项指南指导各地在定价时关注人工智能辅助诊断的相关资源投入 成本，在价格水平上进行整体调节和引导，为人工智能辅助诊断技术应用理顺收费路径。医疗机构可自 行决定是否选用人工智能辅助诊断技术、自行决定选用哪家企业的产品，具体收益分配由医疗机构与企 业自行协商确定。 临床检查中，影像、检验、病理是患者最常接触的三类检查方式。其中，病理被认为是医学诊断的"金 标准"，依托细胞病理、组织病理及分子病理等技术平台，通过对病变组织与细胞的精准分析，明确疾 病类型、肿瘤分型及关键基因突变，为临床诊疗方案的制定提供关键依据。 下一步，国家医保局将指导各省医保局参考此次立项指南，制定全省统一的价格基准，由具有价格管理 权限的统筹地区对照全省价格基准，上下浮动确定实际执行的价格水平。据新华社电 聚焦活检取样、样本处理、切片复制、病理染色、病理诊断等环节，立项指南将已有价格项目规范整合 为28项、 ...

新华社北京12月19日电（记者彭韵佳）国家医保局12月19日发布《病理类医疗服务价格项目立项指南 （试行）》，明确将"人工智能辅助诊断"列为病理诊断的扩展项，将人工智能辅助诊断纳入病理诊断价 格项目的价格构成。 ...

Core Insights - The World Health Organization (WHO) warns about the rapid adoption of artificial intelligence (AI) in healthcare, highlighting significant gaps in legal and ethical safeguards [1][2] Group 1: AI Adoption in Healthcare - Nearly all countries recognize the potential of AI in diagnosis, disease monitoring, and personalized medicine [1] - 32 out of 50 surveyed European countries have adopted AI-assisted diagnostics, and half have introduced chatbots for patient support [1] - Over half of the countries have identified priority application areas for AI in healthcare, driven by the need to improve patient care quality, alleviate workforce pressure, and enhance efficiency and productivity [1] Group 2: Challenges and Barriers - 86% of the surveyed countries view "legal uncertainty" as the primary barrier to AI application in healthcare, while 78% cite "insufficient funding" as a major issue [1] - Only 25% of the countries provide dedicated funding for healthcare AI, and less than 8% have established "responsibility standards" for AI-related errors or harm [1] Group 3: Recommendations for Policy and Strategy - The report emphasizes the need for countries to develop national strategies for healthcare AI that align with public health goals [2] - It calls for investments in capacity building, strengthening legal and ethical safeguards, and improving cross-border data governance [2]

Core Insights - The AI medical industry in China has reached a scale of 97.3 billion yuan in 2023 and is projected to grow to 159.8 billion yuan by 2028, with a compound annual growth rate (CAGR) of 10.5% from 2022 to 2028 [1][2][6] Industry Overview - AI is widely applied across the entire medical process, including health management, diagnostic assistance, imaging analysis, drug development, and surgical robotics, enhancing efficiency and patient experience [2][3] - The medical field has historically embraced technology, with digital healthcare laying the groundwork for the current AI advancements [2] Challenges and Risks - A significant challenge is the lack of high-quality training data, which increases the risk of errors in large model applications, leading to issues such as "hallucinations" and opaque reasoning processes [3][4] - The inability to effectively process multimodal data limits the application of large models in complex clinical scenarios [4] - The rise of domestic large models introduces security risks, including potential malicious attacks and single-point failures [5] - Local hardware deployment of large models results in wasted computational resources and inefficiencies due to dispersed computing power [5] Solutions and Initiatives - Experts advocate for the collection, anonymization, and annotation of clinical data to build high-quality datasets, which are essential for driving AI development and improving model accuracy [6] - Successful examples include the establishment of high-quality datasets for cardiac diseases, integrating extensive clinical data to ensure accuracy and comprehensiveness [6] - Companies are encouraged to collaborate in building a medical data governance framework and a service system to facilitate the large-scale application of AI in healthcare [7]

Core Viewpoint - The medical technology industry is at a crossroads of breakthrough and reconstruction, with advancements in AI-assisted diagnosis, high-end intelligent diagnostic equipment, innovative medical materials, and regenerative medicine reshaping disease discovery, treatment, and management [1] Group 1: Conference Overview - The Second Global MedTech Conference will be held on July 17, 2025, at the Zhongguancun Exhibition Center in Beijing, aiming to promote the collaborative development of the global medical technology industry chain, innovation chain, and clinical application [1][4] - The first conference, Global MedTech Conference 2024, was organized by Siyu [2] Group 2: Awards and Recognition - The conference will present several awards to recognize breakthroughs in medical technology, including the 2025 Global MedTech Innovation Award and the 2025 Global MedTech Innovation Application Award [3][7] - The awards aim to honor cutting-edge technological advancements, successful results transformation, and outstanding services in the medical technology field [3] Group 3: Conference Agenda - Proposed agenda topics include analysis of global medical technology development trends and policy environments, research and transformation paths for imaging platforms, new consumables, brain-computer interfaces, interventional devices, and diagnostic equipment [5] - Other topics will cover experiences in the intersection of medicine and engineering, breakthroughs in AI-assisted diagnosis and digital therapy, and insights into technology directions and company profiles attracting domestic and foreign capital [5] Group 4: Participation and Submission Guidelines - The awards are open to medical device and digital medical technology companies with innovative products or platform technologies that demonstrate originality, advancement, and potential for large-scale industrialization [6] - Submission for the awards is open until May 31, 2025, with a review phase from June 1 to June 15, 2025, and results to be announced between June 16 and June 22, 2025 [10]