Construction and practice of the sensitive data grading control system in nursing management
护理管理中敏感数据分级管控体系的构建与实践

摘要

目的 本研究旨在构建适用于1400张床位医院的护理管理敏感数据分级管控体系，明确体系运行效果，降低数据泄露风险，提升护理数据管理规范性，为医疗机构护理敏感数据安全管理提供实践参考。方法 采用随机对照试验设计。将120名护理人员按1:1随机分为对照组（传统统一管理模式）与实验组（分级管控体系）。对照组接受无差异的数据管理策略，实验组实施基于数据敏感度（核心级、重要级、普通级）的分级管控与动态监督。主要结局指标为18个月内的数据泄露发生率（采用Kaplan-Meier生存分析）与管理合规率，次要指标为数据查询响应时间。选取2023年3月-2025年8月本院护理管理涉及的敏感数据及120名护理人员为研究对象，按随机数字表法分为对照组（60人，采用传统数据管理模式）与实验组（60人，应用构建的分级管控体系）。比较两组数据泄露发生率、护理人员数据管理合规率及数据查询响应时间，持续跟踪18个月。结果 实验组数据泄露发生率显著低于对照组（χ2=6.982，P=0.008）；实验组护理人员数据管理合规率显著高于对照组（χ2=8.538，P=0.003）；实验组数据查询响应时间显著短于对照组（t=32.654，P<0.001）。结论 构建的护理管理敏感数据分级管控体系，在1400张床位医院实践中可有效降低数据泄露风险，提升管理合规性与效率，且适配敏感数据量不大的场景，具有较高的临床应用价值。

Abstract

Objective This study aims to construct a sensitivity data grading control system applicable to a 1400-bed hospital, clarify the operation effect of the system, reduce the risk of data leakage, improve the standardization of nursing data management, and provide practical references for the security management of nursing sensitive data in medical institutions.
Methods A randomized controlled trial design was adopted. 120 nurses were randomly divided 1:1 into the control group (traditional unified management model) and the experimental group (grading control system). The control group received a non-differentiated data management strategy, while the experimental group implemented a graded control and dynamic supervision based on the data sensitivity (core level, important level, and ordinary level). The main outcome indicators were the data leakage rate within 18 months (using Kaplan-Meier survival analysis) and the management compliance rate, and the secondary indicators were the data query response time. From March 2023 to August 2025, the sensitive data involved in nursing management and 120 nurses of the hospital were selected as the research subjects. They were divided into the control group (60 people, using the traditional data management model) and the experimental group (60 people, applying the constructed grading control system) according to the random number table method. The data leakage rate, nursing staff data management compliance rate, and data query response time of the two groups were compared, and continuous tracking was conducted for 18 months.
Results The data leakage rate of the experimental group was significantly lower than that of the control group (χ2 = 6.982, P = 0.008); the nursing staff data management compliance rate of the experimental group was significantly higher than that of the control group (χ2 = 8.538, P = 0.003); the data query response time of the experimental group was significantly shorter than that of the control group (t = 32.654, P < 0.001).
Conclusion   The constructed nursing management sensitivity data grading control system can effectively reduce the risk of data leakage, improve management compliance and efficiency in a 1400-bed hospital, and is suitable for scenarios with a small amount of sensitive data, having high clinical application value.