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一个用于识别影响医院容量的因素并预测未来医院需求的县级综合模型。

A comprehensive county level model to identify factors affecting hospital capacity and predict future hospital demand.

作者信息

Bhowmik Tanmoy, Eluru Naveen

机构信息

Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, USA.

出版信息

Sci Rep. 2021 Nov 29;11(1):23098. doi: 10.1038/s41598-021-02376-y.

Abstract

The sustained COVID-19 case numbers and the associated hospitalizations have placed a substantial burden on health care ecosystem comprising of hospitals, clinics, doctors and nurses. However, as of today, only a small number of studies have examined detailed hospitalization data from a planning perspective. The current study develops a comprehensive framework for understanding the critical factors associated with county level hospitalization and ICU usage rates across the US employing a host of independent variables. Drawing from the recently released Department of Health and Human Services weekly hospitalization data, we study the overall hospitalization and ICU usage-not only COVID-19 hospitalizations. Developing a framework that examines overall hospitalizations and ICU usage can better reflect the plausible hospital system recovery path to pre-COVID level hospitalization trends. The models are subsequently employed to generate predictions for county level hospitalization and ICU usage rates in the future under several COVID-19 transmission scenarios considering the emergence of new COVID-19 variants and vaccination rates. The exercise allows us to identify vulnerable counties and regions under stress with high hospitalization and ICU rates that can be assisted with remedial measures. Further, the model will allow hospitals to understand evolving displaced non-COVID hospital demand.

摘要

持续的新冠病毒病例数以及相关的住院治疗给由医院、诊所、医生和护士组成的医疗保健生态系统带来了沉重负担。然而,截至目前,只有少数研究从规划角度审视了详细的住院治疗数据。本研究构建了一个综合框架,运用一系列自变量来理解与美国各县住院率和重症监护病房(ICU)使用率相关的关键因素。依据美国卫生与公众服务部最近公布的每周住院治疗数据,我们研究的是总体住院情况和ICU使用情况——而非仅新冠病毒相关的住院治疗。构建一个能审视总体住院情况和ICU使用情况的框架,能更好地反映医院系统恢复到新冠疫情前住院趋势水平的合理路径。随后,这些模型被用于在考虑新冠病毒新变种出现和疫苗接种率的几种新冠病毒传播情形下,预测未来各县的住院率和ICU使用率。这项工作使我们能够识别出那些因高住院率和ICU使用率而面临压力的脆弱县和地区,以便采取补救措施对其加以援助。此外,该模型将使医院能够了解不断变化的非新冠住院需求。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e62/8630121/aa6a5fab38c4/41598_2021_2376_Fig1_HTML.jpg

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