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压缩曲线:加利福尼亚州疗养院新冠病毒感染情况变化的横断面研究

Compress the curve: a cross-sectional study of variations in COVID-19 infections across California nursing homes.

作者信息

Gopal Ram, Han Xu, Yaraghi Niam

机构信息

Warwick Business School, University of Warwick, Coventry, UK.

Gabelli School of Business, Fordham University, New York, New York, USA.

出版信息

BMJ Open. 2021 Jan 6;11(1):e042804. doi: 10.1136/bmjopen-2020-042804.

Abstract

OBJECTIVE

Nursing homes' residents and staff constitute the largest proportion of the fatalities associated with COVID-19 epidemic. Although there is a significant variation in COVID-19 outbreaks among the US nursing homes, we still do not know why such outbreaks are larger and more likely in some nursing homes than others. This research aims to understand why some nursing homes are more susceptible to larger COVID-19 outbreaks.

DESIGN

Observational study of all nursing homes in the state of California until 1 May 2020.

SETTING

The state of California.

PARTICIPANTS

713 long-term care facilities in the state of California that participate in public reporting of COVID-19 infections as of 1 May 2020 and their infections data could be matched with data on ratings and governance features of nursing homes provided by Centers for Medicare & Medicaid Services (CMS).

MAIN OUTCOME MEASURE

The number of reported COVID-19 infections among staff and residents.

RESULTS

Study sample included 713 nursing homes. The size of outbreaks among residents in for-profit nursing homes is 12.7 times larger than their non-profit counterparts (log count=2.54; 95% CI, 1.97 to 3.11; p<0.001). Higher ratings in CMS-reported health inspections are associated with lower number of infections among both staff (log count=-0.19; 95% CI, -0.37 to -0.01; p=0.05) and residents (log count=-0.20; 95% CI, -0.27 to -0.14; p<0.001). Nursing homes with higher discrepancy between their CMS-reported and self-reported ratings have higher number of infections among their staff (log count=0.41; 95% CI, 0.31 to 0.51; p<0.001) and residents (log count=0.13; 95% CI, 0.08 to 0.18; p<0.001).

CONCLUSIONS

The size of COVID-19 outbreaks in nursing homes is associated with their ratings and governance features. To prepare for the possible next waves of COVID-19 epidemic, policy makers should use these insights to identify the nursing homes who are more likely to experience large outbreaks.

摘要

目的

疗养院的居民和工作人员在与新冠疫情相关的死亡病例中占比最大。尽管美国各疗养院的新冠疫情爆发情况存在显著差异,但我们仍不清楚为何有些疗养院的疫情规模更大、爆发可能性更高。本研究旨在了解为何有些疗养院更容易发生大规模新冠疫情。

设计

对加利福尼亚州所有疗养院进行观察性研究,截至2020年5月1日。

地点

加利福尼亚州。

参与者

加利福尼亚州713家参与新冠感染情况公开报告的长期护理机构,截至2020年5月1日,其感染数据可与医疗保险和医疗补助服务中心(CMS)提供的疗养院评级及管理特征数据相匹配。

主要观察指标

工作人员和居民中报告的新冠感染病例数。

结果

研究样本包括713家疗养院。营利性疗养院居民中的疫情规模是非营利性疗养院的12.7倍(对数计数=2.54;95%置信区间,1.97至3.11;p<0.001)。CMS报告的健康检查评分较高与工作人员(对数计数=-0.19;95%置信区间,-0.37至-0.01;p=0.05)和居民(对数计数=-0.20;95%置信区间,-0.27至-0.14;p<0.001)感染人数较少相关。CMS报告的评级与自我报告的评级差异较大的疗养院,其工作人员(对数计数=0.41;95%置信区间,0.31至0.51;p<0.001)和居民(对数计数=0.13;95%置信区间,0.08至0.18;p<0.001)的感染人数较多。

结论

疗养院新冠疫情的规模与其评级及管理特征相关。为应对可能到来的下一波新冠疫情,政策制定者应利用这些见解来识别更有可能发生大规模疫情的疗养院。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c509/7789209/cea1f0a82475/bmjopen-2020-042804f01.jpg

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