目的 本文聚焦DeepSeek这一国产人工智能技术，结合护理临床实践，系统探讨其在护理场景中的应用潜力、现存问题及应对策略。方法 检索国内外相关文献，与现有通用人工智能技术对比，进行综述，并提出思考和建议。结果 预计DeepSeek在护理文书自动化、个性化护理方案生成、临床决策支持、护理质控及教育培训等提供适配应用路径，针对性的服务和解决方案等。结论 DeepSeek可通过多模态技术整合与跨平台互补策略，推动护理服务向智能化、精准化方向发展，为缓解护理人力短缺、优化资源分配提供新思路。
Objective This study focuses on DeepSeek，a domestic artificial intelligence technology，systematically exploring its application potential，existing issues，and targeted strategies in nursing clinical scenarios through integration with practical nursing care contexts．Methods Relevant literatures from both domestic and international sources were collected，compared with existing Artificial General Intelligence（AGI）technologies，to conduct a review，and propose reflections and recommendations．Results Through literature review and technical comparisons，the results proposed specific application paths for DeepSeek in scenarios such as automated nursing documentation，personalized care plan generation，clinical decision support，quality control，and education．It further addressed issues including data privacy，ethical risks，and technical limitations．Conclusions The findings suggest that DeepSeek can integrate multimodal technologies and cross-platform complementary strategies to promote intelligent and precise nursing services，offering innovative solutions to alleviate nursing shortages and optimize resource allocation．
目的 识别医院在医患沟通、服务态度、医疗服务和医疗质量方面存在的问题，研究提升医院医疗质量与安全的对策。方法 通过收集和整理2024年1-6月某三甲医院医患沟通科处理的医疗诉求数据，包括患者投诉、咨询、建议及求助调查结果，采用定性分析和定量分析相结合的方法，对134件医疗诉求数据进行详细分类和统计，深入分析投诉事由，并结合实际有责投诉量与诊疗总人数，计算投诉千人发生率。投诉千人发生率与2023年同期对照。结果 共处理医疗诉求134件，其中投诉116件（占86.56%）、求助11件（8.21%）、咨询5件（3.73%）、建议2件（1.5%）。投诉中，医患沟通不畅和服务态度问题占42%，医疗服务问题32%，医疗质量问题占26%。实际有责投诉量为63件，投诉千人发生率约为0.12‰。通过对诉求数据的深入分析，识别出医疗服务过程中的薄弱环节和改进点。结论 针对分析结果及同期对照，提出相应的对策建议，包括加强医患沟通培训，改善服务态度，优化医疗服务流程，并对投诉高发科室进行特别关注和改进等措施，以提高患者满意度和医院整体医疗质量。
Objective To identify issues in hospital communication, service attitude medical services, and medical quality and to explore strategies for enhancing hospital medical quality and safety. Methods By collecting and organizing medical appeal data processed by the Medical Communication Department of a tertiary hospital from January to June 2024, including patient complaints, inquiries, suggestions, and requests for help. A combined qualitative and quantitative analysis was conducted on 134 medical appeal cases. Detailed classification and statistics were performed on these cases, and an in-depth analysis of the reasons for complaints was carried out. Furthermore, the actual number of responsible complaints was compared with the total number of treated patients to calculate the complaint rate per thousand people. This complaint rate was then compared with the same period in 2023. Results A total of 134 medical appeals were processed including 116 complaints（accounting for 86. 56%）, 11 requests for help（8. 21%）, 5 inquiries（3. 73%）, and 2 suggestions（1. 5%）. Among the complaints, issues related to poor communication between doctors and patients and service attitude accounted for 42%, medical service issues accounted for 32%, and medical quality issues accounted for 26%. The actual number of responsible complaints was 63, and the complaint rate per thousand people was approximately 0. 12‰. Through in-depth analysis of the appeal data, weak links and improvement points in the medical service process were identified. Conclusions Based on the analysis results and comparisons with the same period, corresponding countermeasures and suggestions are proposed, including strengthening communication training between doctors and patients, improving service attitude, optimizing medical service processes, and paying special attention to and improving departments with high complaint rates in order to improve patient satisfaction and overall hospital medical quality.
