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[1]刘梦蝶柴春燕陆彩萍陆亚青.数智化护理不良事件全流程辅助管理系统构建与应用[J].中国卫生质量管理,2026,33(8):59-63.[doi:10.13912/j.cnki.chqm.2026.33.8.12]
　LIU Mengdie,CHAI Chunyan,LU Caiping.Construction and Application of the Digital-Intelligent Full-Process Auxiliary Management System for Nursing Adverse Events[J].Chinese Health Quality Management,2026,33(8):59-63.[doi:10.13912/j.cnki.chqm.2026.33.8.12]

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数智化护理不良事件全流程辅助管理系统构建与应用

《中国卫生质量管理》[ISSN:1006-7515/CN:CN 61-1283/R] 卷: 33 期数: 2026年8期页码: 59-63 栏目: 护理质量出版日期: 2026-08-15

Title:: Construction and Application of the Digital-Intelligent Full-Process Auxiliary Management System for Nursing Adverse Events

作者:: 刘梦蝶柴春燕陆彩萍陆亚青; 南京医科大学附属苏州医院（苏州市立医院）

Author(s):: LIU Mengdie; CHAI Chunyan; LU Caiping; The Affiliated Suzhou Hospital of Nanjing Medical University(Suzhou Municipal Hospital)

关键词:: 护理不良事件; 数智化; 人工智能; 护理管理; 患者安全

Keywords:: Nursing Adverse Event; Digital Intelligence; Artificial Intelligence; Nursing Management; Patient Safety

分类号:: R47

DOI:: 10.13912/j.cnki.chqm.2026.33.8.12

文献标志码:: B

摘要:: 目的基于数智化技术，构建护理不良事件全流程辅助管理系统并应用，提升患者安全管理水平。方法组建多学科团队，基于循证科学构建决策支持库，融合多源数据建立患者动态资源库，研发涵盖“事件填报-分析决策-追踪优化”的全流程辅助管理系统并初步应用。比较系统应用后（2025年12月-2026年2月）和应用前（2025年9-11月）不良事件上报时间、填报规范率及发生率的差异，并通过定量与定性相结合的方法评价系统可用性。结果系统应用后不良事件上报时间缩短（P＜0.05）、填报规范率提升（P=0.028），多数事件发生率下降。系统可用性量表得分为（93.65±2.87）分，系统存在卡顿、推送通知不明显等问题。结论数智化护理不良事件全流程辅助管理系统能够有效提升填报效率与规范率，助力不良事件管理。

Abstract:: ObjectiveTo construct and apply a full-process auxiliary management system for nursing adverse events based on digital-intelligent technologies, so as to improve the level of patient safety management. MethodsA multidisciplinary team was established to build an evidence-based decision support library, integrate multi-source data to construct a dynamic patient resource pool, and develop a full-process auxiliary management system covering "event reporting - analysis and decision-making - tracking and optimization" for preliminary application. Differences in adverse event reporting time, reporting standardization rate and incidence were compared between the pre-system period (December 2025 to February 2026) and post-system period (September to November 2025), and system usability was evaluated via a combined quantitative and qualitative method.ResultsAfter system application, the adverse event reporting time was shortened (P<0.05), the reporting standardization rate was improved (P=0.028), and the incidence of various events decreased. The system usability score was (93.65±2.87), while issues such as system lag and inconspicuous push notifications were identified.Conclusion The digital-intelligent full-process auxiliary management system for nursing adverse events can effectively enhance reporting efficiency and standardization rate, and facilitate adverse event management.

参考文献/References:

［1］仇铁英,黄金.护理不良事件概念与管理研究现状［J］.中国护理管理,2014,14(9):1004-1008.［2］秦丽丽,严婷,徐宇红,等.基于医院信息系统的结构化护理不良事件管理系统的研发及应用［J］.解放军护理杂志,2020,37(8):83-86.［3］OU YQ,ZHANG G,XIE Y,et al.Effects of a special continuous quality improvement in nursing on the management of adverse care events: a retrospective study［J］.BMC Health Serv Res,2024,24(1):692.［4］王婷婷,方洁,陈叶,等.国外护理不良事件分析方法研究现状［J］.护理管理杂志,2022,22(8):575-579.［5］BERGER S,SAUT AM,BERSSANETI FT.Using patient feedback to drive quality improvement in hospitals:a qualitative study［J］.BMJ Open,2020,10(10):e037641.［6］王颖,熊晓云,刘梦蝶,等.数智化干预技术在冠心病患者心理障碍中的应用进展［J］.中华护理杂志,2024,59(16):1956-1961.［7］席祖洋,李茶香,刘静兰,等.基于清单管理的护理风险管理信息化平台的构建及应用［J］.中国护理管理,2025,25(1):101-106.［8］宋佳雪,吴英,彭程,等.机器学习法在护理不良事件管理中的应用研究进展［J］.护理研究,2023,37(23):4251-4256.［9］曲超然,王青,韩琳,等.机器学习算法在压力性损伤管理中的应用进展［J］.中华护理杂志,2021,56(2):212-217.［10］杨楠楠,蒋慧萍,史婷奇.基于机器学习构建住院患者深静脉血栓风险预测模型的系统评价［J］.护理学报,2023,30(23):44-50.［11］孙萌,骆金铠,王露露,等.基于患者360视图的护理不良事件管理系统构建与应用［J］.中国卫生质量管理,2024,31(4):54-58.［12］陈杰,鞠梅,赖静,等.基于临床知识库的智能学习型不良事件管理系统的构建与应用［J］.护理学杂志,2023,38(5):87-91.［13］WANG YH,XIE YH,QIAO Y,et al.Chinese CSUQ:cross-cultural adaptation and evaluation of measurement properties［J］.Int J Hum-Comput Int,2023,40(22):7623-7641. ［14］ZHANG D,YIN C,ZENG J,et al.Combining structured and unstructured data for predictive models: a deep learning approach［J］.BMC Med Inform Decis Mak,2020,20(1):280. ［15］王静,青秋琼,左慧,等.一院多区双重视角下护理不良事件风险的管理及成效［J］.护理研究,2024,38(23):4222-4227.［16］王静,黄有红,方萍萍,等.数据监测驱动下医院护理不良事件链的回顾性分析［J］.护理研究,2024,38(21):3941-3945.［17］鞠鑫,姚永刚,赵芯蕊.医疗健康领域人工智能应用安全框架研究［J］.中国卫生质量管理,2026,33(5):7-11.［18］邱阳阳,刘宗燕,闫冬勤,等.不良事件上报障碍与患者安全文化的相关性研究［J］.中国卫生质量管理,2022,29(9):34-38.

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更新日期/Last Update: 2026-08-15