主管:国家卫生健康委员会
主办:国家卫生健康委医院管理研究所
中国科技核心期刊(中国科技论文统计源期刊)
中国科学引文数据库(CSCD)核心库期刊
《中文核心期刊要目总览》核心期刊

中国护理管理 ›› 2026, Vol. 26 ›› Issue (1): 14-18.doi: 10.3969/j.issn.1672-1756.2026.01.004

• 特别策划·人工智能护理应用 • 上一篇    下一篇

骨科人工智能护理随访系统的构建与应用

金姬延 蒋雨婷 邵红琳 宋恺 张景涵 许蕊凤 李葆华   

  1. 北京大学第三医院骨科,100191 北京市(金姬延,宋恺,张景涵,许蕊凤);信息管理与大数据中心(邵红琳);护理部(李葆华);北京大学护理学院(蒋雨婷)
  • 出版日期:2026-01-15 发布日期:2026-01-15
  • 通讯作者: 李葆华,硕士,主任护师,护理部主任,E-mail:lianglbh@126.com
  • 作者简介:金姬延,硕士,副主任护师,科护士长

Development and application of an Artificial Intelligence nursing follow-up system in orthopedics

JIN Jiyan, JIANG Yuting, SHAO Honglin, SONG Kai, ZHANG Jinghan, XU Ruifeng, LI Baohua   

  1. Department of Orthopedics, Peking University Third Hospital, Beijing, 100191, China
  • Online:2026-01-15 Published:2026-01-15
  • Contact: E-mail:lianglbh@126.com

摘要: 目的:评价骨科人工智能(Artificial Intelligence,AI)护理随访系统在手术患者出院后管理中应用的可行性与有效性,为提高随访效率提供参考。方法:以健康行为互动模式为理论框架,围绕健康信息、情感支持、决策控制与专业指导4个维度设计随访内容,采用AI自动随访与人工干预双轨机制,实现患者闭环管理。结果:2024年12月1日至2025年9月30日期间,从北京市某三级甲等医院大数据平台共提取11 126例出院患者数据,系统总体随访9 214例(82.8%)。以颈椎手术为例,3 857例出院患者中随访3 727例(96.6%),系统自动生成异常预警工单4 982条,主要涉及疼痛、功能锻炼等方面。结论:AI护理随访系统在骨科术后患者出院后管理中具有较好的可行性与应用价值,可有效提高随访率,促进出院后风险早期识别。

关键词: 骨科;人工智能;智慧随访;护理信息化;患者管理

Abstract: Objective: To examine the feasibility and effectiveness of an orthopedic Artificial Intelligence nursing follow-up system in the post-discharge management of surgical patients, to provide a reference for improving the efficiency of follow-up. Methods: Guided by the Interaction Model of Client Health Behavior, follow-up content was designed across four dimensions: health information, emotional support, decision control, and professional guidance. A dual-track mechanism integrating AI-driven automated follow-up and manual intervention was adopted to achieve closed-loop post-discharge management. Results: From December 1, 2024, to September 30, 2025, a total of 11,126 discharged patients in a tertiary grade A hospital in Beijing were included. The system successfully completed follow-up for 9214 cases (82.8%). Using cervical spine surgery as an example, among 3857 discharged patients, 3727 cases (96.6%) were successfully followed up. The system automatically generated 4982 alerts for abnormal findings, primarily related to pain and functional exercise. Conclusion: The Artificial Intelligence nursing follow-up system demonstrates high feasibility and practical value in the post-discharge management of orthopedic surgical patients. It effectively improves follow-up coverage and facilitates the early identification of post-discharge risks.

Key words: orthopedics; Artificial Intelligence; smart follow-up; nursing informatization; patient management

中图分类号:  R47;R197