在跨境多重伤亡事件的管理中,最低数据集协调. 修改后的德尔菲 (VALKYRIES-H2020项目)
Navid Behzadi Koochani1,2,3,4, Raúl Muñoz Romo1, Ignacio Hernández Palencia5
1Servicio de Urgencias Médicas de la Comunidad de Madrid (SUMMA112), Madrid, Spain.
PloS one
|July 18, 2024
概括
针对跨境多重伤亡事件 (MCI) 制定了一个最小数据集 (MDS). 这种标准化的数据收集确保了有效的实时通信,以改善跨境紧急响应和患者护理.
科学领域:
- 紧急医疗 紧急医疗
- 公共卫生 公共卫生
- 灾害管理 灾害管理
背景情况:
- 跨境多人伤亡事件 (MCI) 需要协调的程序和最低数据集 (MDS).
- 标准化对于有效的管理至关重要,无论地点,语言或机构流程如何.
- 可互操作的模型对于维护患者获得跨境医疗保健的权利至关重要.
研究的目的:
- 通过实时最小数据集 (MDS) 优化跨境MCI的管理.
- 建立有关MCI管理的基本数据点的专家共识.
- 确保对指挥控制链的实时数据通信.
主要方法:
- 修改后的Delphi方法与Utstein技术相结合,以获得专家的共识.
- 代阶段涉及变量定义,聚类,评分和验证.
- 使用SPSS统计软件进行数据分析.
主要成果:
- 建立了一个最终的MDS,包括6个数据实体和31个子实体 (127个项目).
- 专家们达成了高度的共识,特别是在事件识别,地点,日期和时间方面.
- 所有MDS项目都支持数字收集和实时传输到指挥控制链.
结论:
- 一个基于共识的MDS成功地开发了高水平的专家间协议.
- 该MDS为MCI管理提供了数字,实时数据收集和传输.
- 该工具的有效性通过大规模,跨国跨境模拟得到证实.
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