通讯作者: 黄淮裕, huanghuaiyu@mzrmyy.com

DOI：10.12201/bmr.202610.00045

Research on Intelligent Recognition and Intervention Strategies for Quality Control Nodes in the Full Process of Electronic Medical Records from a Data Chain Perspective

• 摘要：〔〕目的/意义针对电子病历全流程质控中数据链断裂、节点管控薄弱等问题,提出智能识别与干预策略,以提升医疗数据质量与患者安全管理水平。方法/过程 基于数据链理论构建电子病历质控分析框架,采用文献研究、专家咨询与案例分析方法,识别关键质控节点并建立智能识别规则；运用自然语言处理与机器学习技术,对病历书写完整性、逻辑一致性、诊疗规范性等进行实时监测与风险预警；构建分层干预策略,实现从自动提醒、智能修正到人工审核的递进式质控管理。结果/结论 该方法可有效提升病历质控覆盖率与缺陷检出率,缩短质控反馈周期,为实现电子病历全流程、智能化、精细化的质量管理提供了可行方案。

  关键词： 电子病历；数据链；全流程质控；智能识别；干预策略；人工智能; ; ; ; ; 

   

  Abstract: 〔〕 Purpose/Significance To address issues such as data chain disruptions and inadequate node management in the comprehensive quality control of electronic medical records (EMRs), this study proposes intelligent recognition and intervention strategies to enhance both medical data quality and patient safety management standards. Method/Process Based on the Data Chain Theory, a quality control analysis framework for electronic medical records was constructed. Utilizing literature review, expert consultation, and case analysis methods, key quality control nodes were identified, and intelligent recognition rules were established. Natural language processing and machine learning technologies were employed to conduct real-time monitoring and risk alerts regarding the completeness of medical record documentation, logical consistency, and diagnostic and treatment standardization. A hierarchical intervention strategy was developed to achieve progressive quality control management, ranging from automatic reminders and intelligent corrections to manual review. Result/Conclusion This method effectively enhances the coverage rate of medical record quality control and the defect detection rate, shortens the quality control feedback cycle, and provides a feasible solution for achieving comprehensive, intelligent, and refined quality management throughout the entire electronic medical record process.

  Key words: Electronic Medical Record; Data Chain; Full-Process Quality Control; Intelligent Recognition; Intervention Strategy; Artificial Intelligence

  提交时间：2026-10-19

  版权声明：作者本人独立拥有该论文的版权，预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。
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• 序号	提交日期	编号	操作
  1	2026-06-11	10.12201/bmr.202610.00045V1	下载

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