预测COVID-19的当地医院病床需求,使用按需模拟
Raisa Kociurzynski1, Angelo D'Ambrosio1, Alexis Papathanassopoulos1
1Institute for Infection Prevention and Hospital Hygiene, Freiburg University Hospital, Freiburg Im Breisgau, Germany.
Scientific reports
|December 3, 2023
概括
准确的医院床需求预测在流行病期间至关重要. 一个新的在线工具使用当地数据来准确预测COVID-19病床占用率,帮助医院资源管理.
科学领域:
- 流行病学 流行病学
- 医疗保健管理健康管理
- 公共卫生 公共卫生
背景情况:
- 传染病流行需要准确的医院床需求预测,以防止医疗保健系统过载.
- 现有的预测方法可能缺乏有效的个人医院规划所需的细节性.
研究的目的:
- 为各个医院开发一个直观的在线工具,以预测COVID-19病床需求.
- 评估地理流域选择对预测准确性和精确性的影响.
主要方法:
- 开发一个在线预测工具,利用当地发病率,疫苗接种和床位占用数据.
- 医院采集区的可定制地理分辨率.
- 通过对德国大学医院和地区的ICU病床占用率预测进行绩效评估.
主要成果:
- 当流域与医院的当地流域保持一致时,可以获得最佳的预测准确度.
- 扩大采水区提高了精度,但以牺牲精度为代价.
- 在疫情转折点期间,预测性能下降.
- 纳入关注的变体对整体床位占用预测的影响最小.
结论:
- 对于准确的流行病预测,利用本地数据是非常重要的.
- 与国家或州级数据相比,医院特定的流域预测提供了更高的准确性和精度平衡.
- 这些预测为医院规划提供了可操作的见解,包括对容量管理的选择性手术进行调整.
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