Cargando…

Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths

RESEARCH OBJECTIVE: Although emerging research has identified facility‐level or community‐level risk factors for nursing home COVID‐19 infection cases, little research has been conducted to understand the risk factors for nursing home COVID‐19 death rates. This study has two aims: 1) identify geogra...

Descripción completa

Detalles Bibliográficos
Autor principal: Wang, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441353/
http://dx.doi.org/10.1111/1475-6773.13841
_version_ 1783752852846411776
author Wang, Xiao
author_facet Wang, Xiao
author_sort Wang, Xiao
collection PubMed
description RESEARCH OBJECTIVE: Although emerging research has identified facility‐level or community‐level risk factors for nursing home COVID‐19 infection cases, little research has been conducted to understand the risk factors for nursing home COVID‐19 death rates. This study has two aims: 1) identify geographic clusters with high nursing home COVID‐19 death rates; 2) understand facility‐level and community‐level risk factors for facilities residing within the hot spots versus those not in the hot spots. STUDY DESIGN: This is a cross‐sectional research design. We utilized nursing home COVID data from Centers for Medicare & Medicaid Services (as of November 13th, 2020) linked with Brown University's LTCfocus data and Nursing Home Compare, along with zip code‐level data from American Community Survey. Geospatial hot spot analysis (Getis‐Ord Gi*) was applied to identify statistically significant hot spots of COVID‐19 death rates in nursing homes. We compared facility‐level and community‐level factors associated with COVID death rates by performing multivariate regressions stratified by whether the nursing home was located in the hot spot area identified. POPULATION STUDIED: The sample included 15,341 nursing homes. PRINCIPAL FINDINGS: 322 zip code areas were identified as having a significantly high level of nursing home COVID death rates at the 95% confidence level. We found statistically significant clustering of COVID‐19 death rates in nursing homes in Northeastern United States (New Jersey, Massachusetts, Connecticut, and New York), South Carolina, Georgia, Florida, Kentucky, and parts of Texas, Mississippi and Louisiana. The hot spot areas tend to be communities with lower household income, higher household sizes, and higher unemployed rates. Regression results indicated common facility‐level risk factors as low total nursing staffing levels, high proportion of Medicaid residents, and low deficiency/quality ratings. Significant zip code‐level factors included household income, average household size, unemployed rate, and proportion of Hispanic residents. However, among nursing homes residing in hot spot zip code areas, total nursing staffing levels (β = −0.04, p < 0.001) and proportion of Medicaid residents (β = 0.03, p < 0.001) had greater effects on death rates. CONCLUSIONS: Nursing homes located in communities of lower social‐economic status were hit the hardest in terms of having high death rates. Among nursing homes located in hot spot communities, nurse staffing and facility resources (i.e. proportion of Medicaid) play more critical roles in preventing further damage to residents. IMPLICATIONS FOR POLICY OR PRACTICE: Policymakers should target resources to nursing homes in the hot spot areas identified, particularly nursing homes with low staffing and high Medicaid census in those areas.
format Online
Article
Text
id pubmed-8441353
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Blackwell Publishing Ltd
record_format MEDLINE/PubMed
spelling pubmed-84413532021-12-08 Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths Wang, Xiao Health Serv Res Special Issue Abstract RESEARCH OBJECTIVE: Although emerging research has identified facility‐level or community‐level risk factors for nursing home COVID‐19 infection cases, little research has been conducted to understand the risk factors for nursing home COVID‐19 death rates. This study has two aims: 1) identify geographic clusters with high nursing home COVID‐19 death rates; 2) understand facility‐level and community‐level risk factors for facilities residing within the hot spots versus those not in the hot spots. STUDY DESIGN: This is a cross‐sectional research design. We utilized nursing home COVID data from Centers for Medicare & Medicaid Services (as of November 13th, 2020) linked with Brown University's LTCfocus data and Nursing Home Compare, along with zip code‐level data from American Community Survey. Geospatial hot spot analysis (Getis‐Ord Gi*) was applied to identify statistically significant hot spots of COVID‐19 death rates in nursing homes. We compared facility‐level and community‐level factors associated with COVID death rates by performing multivariate regressions stratified by whether the nursing home was located in the hot spot area identified. POPULATION STUDIED: The sample included 15,341 nursing homes. PRINCIPAL FINDINGS: 322 zip code areas were identified as having a significantly high level of nursing home COVID death rates at the 95% confidence level. We found statistically significant clustering of COVID‐19 death rates in nursing homes in Northeastern United States (New Jersey, Massachusetts, Connecticut, and New York), South Carolina, Georgia, Florida, Kentucky, and parts of Texas, Mississippi and Louisiana. The hot spot areas tend to be communities with lower household income, higher household sizes, and higher unemployed rates. Regression results indicated common facility‐level risk factors as low total nursing staffing levels, high proportion of Medicaid residents, and low deficiency/quality ratings. Significant zip code‐level factors included household income, average household size, unemployed rate, and proportion of Hispanic residents. However, among nursing homes residing in hot spot zip code areas, total nursing staffing levels (β = −0.04, p < 0.001) and proportion of Medicaid residents (β = 0.03, p < 0.001) had greater effects on death rates. CONCLUSIONS: Nursing homes located in communities of lower social‐economic status were hit the hardest in terms of having high death rates. Among nursing homes located in hot spot communities, nurse staffing and facility resources (i.e. proportion of Medicaid) play more critical roles in preventing further damage to residents. IMPLICATIONS FOR POLICY OR PRACTICE: Policymakers should target resources to nursing homes in the hot spot areas identified, particularly nursing homes with low staffing and high Medicaid census in those areas. Blackwell Publishing Ltd 2021-09-15 2021-09 /pmc/articles/PMC8441353/ http://dx.doi.org/10.1111/1475-6773.13841 Text en © 2021 Health Research and Educational Trust
spellingShingle Special Issue Abstract
Wang, Xiao
Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title_full Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title_fullStr Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title_full_unstemmed Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title_short Mapping and Identifying Community Risk Factors for COVID‐19 Nursing Home Deaths
title_sort mapping and identifying community risk factors for covid‐19 nursing home deaths
topic Special Issue Abstract
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441353/
http://dx.doi.org/10.1111/1475-6773.13841
work_keys_str_mv AT wangxiao mappingandidentifyingcommunityriskfactorsforcovid19nursinghomedeaths