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Compress the curve : a cross sectional study of variations in COVID-19 infections across California nursing homes
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Gopal, Ram D., Han, Xu and Yaraghi, Niam (2021) Compress the curve : a cross sectional study of variations in COVID-19 infections across California nursing homes. BMJ Open, 11 . e042804. doi:10.1136/bmjopen-2020-042804
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Official URL: https://doi.org/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
| Item Type: | Journal Article | ||||||
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| Subjects: | H Social Sciences > HV Social pathology. Social and public welfare R Medicine > RA Public aspects of medicine R Medicine > RC Internal medicine |
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| Divisions: | Faculty of Social Sciences > Warwick Business School | ||||||
| Library of Congress Subject Headings (LCSH): | COVID-19 (Disease) -- Research -- United States, COVID-19 (Disease) -- Patients -- United States, Nursing home patients -- United States, Older people -- Diseases -- United States, COVID-19 (Disease) -- Nursing -- United States, COVID-19 Pandemic, 2020- | ||||||
| Journal or Publication Title: | BMJ Open | ||||||
| Publisher: | BMJ | ||||||
| ISSN: | 2044-6055 | ||||||
| Official Date: | 6 January 2021 | ||||||
| Dates: |
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| Volume: | 11 | ||||||
| Article Number: | e042804 | ||||||
| DOI: | 10.1136/bmjopen-2020-042804 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access | ||||||
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