在SARS-CoV-2大流行期间重新制定实时随机安全分析
Gonzalo Sirgo1, Manuel A Samper1, Julen Berrueta1
1Hospital Universitari de Tarragona Joan XXIII, Universitat Rovira I Virgili, Institut d'Investigació Sanitària Pere I Virgili, Tarragona, Spain.
Medicina intensiva
|December 29, 2024
概括
实时随机安全分析 (AASTRE) 在高压重症监护环境中是可行的和有用的. 这种安全工具需要最少的时间投入,成功识别并改善了超过10%的不安全临床情况.
科学领域:
- 医疗保健管理的管理
- 患者安全 患者安全
- 关键护理医学 关键护理医学
背景情况:
- 由于COVID-19的流行,造成了不典型的医疗保健动态,导致了显著的临床安全差距.
- 高压的护理环境对维持患者安全标准提出了独特的挑战.
研究的目的:
- 评估实时随机安全分析 (AASTRE) 在高压重症监护环境中的可行性和实用性.
- 确定AASTRE是否能够有效地识别和解决复杂医疗环境中的安全问题.
主要方法:
- 一项前性研究于2022年1月至9月在一所大学医院的两个混合重症监护室 (ICU) 进行.
- 每周进行两次安全审计,以使用AASTRE方法评估32项安全措施.
- 可行性通过审计完成率和花费的时间来衡量,而实用性则通过对护理流程的变化来评估.
主要成果:
- 该研究分析了390个患者日,包括49名COVID-19患者,这些患者的年龄,ICU停留,SAPS 3分数和死亡率都较高.
- 可行性很高,93.8%的计划审计平均在25分钟内完成.
- 实施AASTRE导致11.8%的评估安全措施的流程变化.
结论:
- 实时随机安全分析 (AASTRE) 是一种可行且有用的工具,用于提高高度复杂的护理环境中的患者安全.
- 在短短的两次每周的审计中,AASTRE有效地将超过10%的评估的不安全情况转化为安全实践.
- AASTRE方法提供了一个有价值的框架,用于持续改善ICU的安全性,即使在苛刻的条件下.
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