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赋予紧急护士在危机响应中的权力 - - 为加强准备和决策的质量改进框架
Hesam Seyedin1, Shandiz Moslehi2, Sajjad Narimani3
1Department of Health in Disasters and Emergencies, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
International emergency nursing
|November 18, 2025
概括
紧急护士通过模拟,人工智能和协议改革改善了危机应对. 这种多模式的方法显著提高了风险感知,决策速度和自我有效性,从而改善了患者的护理.
科学领域:
- 紧急医疗 紧急医疗
- 提高护理质量 提高护理质量
- 医疗保健技术整合 医疗保健技术整合
背景情况:
- 在应对危机期间,急诊护士面临着认知过载和机构障碍.
- 质量改善举措对于提高紧急情况下患者的治疗结果至关重要.
- 风险感知,决策和自我效能方面的差距会影响急救护士的准备.
研究的目的:
- 通过基于证据的干预措施,增强紧急护士的危机准备能力.
- 解决和改善急诊护士的风险感知,决策和自我效能.
- 评估多式联运质量改进计划对应急部门 (ED) 危机响应的影响.
主要方法:
- 一项干预前后研究,涉及两个学术医疗中心的150名急诊护士.
- 干预措施包括基于模拟的培训,人工智能 (AI) 驱动的决策支持工具和协议改革.
- 在基线,干预后和6个月后期收集的数据;使用t测试,ANCOVA,对照图表和千平方测试进行分析.
主要成果:
- 观察到显著的改善:风险感知精度增加32% (p < 0.01),决策延迟减少26% (p < 0.05).
- 自我有效性得分几乎翻了一番 (45%至89%);ED过程结果在AI支持下得到改善 (40%减少分选错误,35%减少错过的恶化).
- 改善在统计学上是显著的,并在6个月的随访中持续.
结论:
- 结合模拟,人工智能和协议改革的多模式方法显著提高了急救护士的危机准备能力.
- 与单次干预研究相比,这种策略产生了更好的结果.
- 广泛采用需要机构支持技术和政策改革,以赋予护士在危机情况下的权力.
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