在COVID-19大流行之前和期间评估医院内护理过渡结构:网络分析研究
Yubo Feng1, Jiayi Fu1, Mayur Patel2
1Vanderbilt University, Nashville, TN.
概括
在COVID-19大流行期间,护理过渡 (TOC) 结构保持稳定. 网络分析显示,在疫情前和期间的患者护理过渡中,存在着一致的分类,同型和小世界特征.
科学领域:
- 医疗保健服务研究 医疗服务研究
- 网络科学 网络科学
- 流行病学 流行病学
背景情况:
- 护理过渡 (TOC) 对患者的连续性至关重要,特别是对于那些有复杂需求的人来说.
- COVID-19大流行对医疗保健系统产生了重大影响,可能会破坏TOC等常规护理过程.
- 了解大流行对TOC结构的影响对于保持医疗保健质量至关重要.
研究的目的:
- 评估和量化COVID-19大流行之前和期间TOC结构的变化.
- 分析TOC系统在与流行病有关的压力下的弹性.
- 利用网络分析来评估护理过渡的结构性质.
主要方法:
- 范德比尔特大学医学中心 (VUMC) 的创伤登记册的回顾性分析.
- 包括2019年1月至2021年5月期间5674例住院护理过渡 (COVID-19前和内).
- 应用网络指标 (分类性,同类性,小世界性) 来描述TOC结构.
主要成果:
- 在COVID-19之前和之后,TOC结构在COVID-19之前和期间都表现出不合类,同型和小世界特征.
- 网络指标表明COVID-19大流行对这些核心TOC结构性质的影响有限.
- 不分类性促进了分类和接收单位之间的高效患者转移;同类性表明连接单位的患者种群相似;小世界性建议短转移路径.
结论:
- 这项研究表明,尽管COVID-19大流行带来的压力,TOC结构的稳定性仍然很强.
- 这些发现表明,已建立的TOC网络具有固有的弹性.
- 保持分类,同型和小世界特征是有效的病人护理过渡的关键.
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