Characteristics and Quality of US Nursing Homes Reporting Cases of Coronavirus Disease 2019 (COVID-19)

Quality of care for older adults in nursing homes: It begins with registered nurses but does not end there!

This editorial comments on the article by Mueller et al.

Drivers of COVID-19 Outcomes in Long-Term Care Facilities Using Multi-Level Analysis: A Systematic Review

This study aimed to identify the individual, organizational, and environmental factors which contributed to COVID-19-related outcomes in long-term care facilities (LTCFs). A systematic review was conducted to summarize and synthesize empirical studies using a multi-level analysis approach to address the identified influential factors. Five databases were searched on 23 May 2023. To be included in the review, studies had to be published in peer-reviewed journals or as grey literature containing relevant statistical data. The Joanna Briggs Institute critical appraisal tool was employed to assess the methodological quality of each article included in this study. Of 2137 citations identified after exclusions, 99 records met the inclusion criteria. The predominant individual, organizational, and environmental factors that were most frequently found associated with the COVID-19 outbreak comprised older age, higher dependency level; lower staffing levels and lower star and subset domain ratings for the facility; and occupancy metrics and co-occurrences of outbreaks in counties and communities where the LTCFs were located, respectively. The primary individual, organizational, and environmental factors frequently linked to COVID-19-related deaths comprised age, and male sex; higher percentages of racial and ethnic minorities in LTCFs, as well as ownership types (including private, for-profit, and chain membership); and higher occupancy metrics and LTCF's size and bed capacity, respectively. Unfolding the risk factors collectively may mitigate the risk of outbreaks and pandemic-related mortality in LTCFs during future endemic and pandemics through developing and improving interventions that address those significant factors.

Changes in institution for mental diseases (IMD) ownership status and insurance acceptance over time

State Medicaid programs are prohibited from using federal dollars to pay institutions for mental diseases (IMDs)-freestanding psychiatric facilities with more than 16 beds. Increasingly, regulatory mechanisms have made payment of treatment in these settings substantially more feasible. This study evaluates if changing financial incentives are associated with increases in for-profit ownership among IMD facilities relative to non-IMD facilities, as well as greater increases in Medicaid acceptance among for-profit IMD facilities relative to for-profit non-IMD facilities. We used data from the 2014-2020 National Mental Health Services Surveys and examined 11 945 facility-years. Relative to non-IMDs, the increase in for-profit ownership among IMDs was 6.6 percentage points greater. The largest proportional change in Medicaid acceptance occurred among for-profit IMD facilities relative to for-profit non-IMDs (18.5 percentage points). Existing research is mixed on the quality of inpatient and residential psychiatric care provided in for-profit vs nonprofit and public facilities, as well as in IMD relative to non-IMD facilities. As payment policy increasingly incentivizes for-profit facilities to enter the psychiatric care space, we should be mindful of the impact of these decisions on patient safety.

Nursing Home Residents' COVID-19 Infections in the United States: A Systematic Review of Personal and Contextual Factors

Background: This mixed methods systemic review synthesizes the evidence about nursing home risks for COVID-19 infections. Methods: Four electronic databases (PubMed, Web of Science, Scopus, and Sage Journals Online) were searched between January 2020 and October 2022. Inclusion criteria were studies reported on nursing home COVID-19 infection risks by geography, demography, type of nursing home, staffing and resident's health, and COVID-19 vaccination status. The Mixed Methods Appraisal Tool (MMAT) was used to assess the levels of evidence for quality, and a narrative synthesis for reporting the findings by theme. Results: Of 579 initial articles, 48 were included in the review. Findings suggest that highly populated counties and urban locations had a higher likelihood of COVID-19 infections. Larger nursing homes with a low percentage of fully vaccinated residents also had increased risks for COVID-19 infections than smaller nursing homes. Residents with advanced age, of racial minority, and those with chronic illnesses were at higher risk for COVID-19 infections. Discussion and implications: Findings suggest that along with known risk factors for COVID-19 infections, geographic and resident demographics are also important preventive care considerations. Access to COVID-19 vaccinations for vulnerable residents should be a priority.

Factors Affecting COVID-19 Incidences and Deaths of Geriatric Hospital Patients in Korea

The current retrospective study aimed to investigate the association between organizational factors and nursing staff in geriatric hospitals and coronavirus disease 2019 (COVID-19) incidences and deaths using secondary data from governments nationwide in Korea. We used data on the number of COVID-19-confirmed cases and deaths among older adults in geriatric hospitals and nursing staff levels in those hospitals. We found that when the RN level was higher than the sample mean, the number of COVID-19-confirmed cases by geriatric hospital was significantly lower (4.3%; p = 0.05) and the number of deaths by geriatric hospital was marginally significantly lower (1.4%; p = 0.05). This study presented the national description of geriatric hospitals during the COVID-19 pandemic in terms of organizational and nursing staff factors. Findings highlight the impact of nursing staff skill mix and number of geriatric hospitals during the COVID-19 pandemic in Korea. It is necessary to allocate a realistic designation of infection control staff and establish a clear standard so infection control activities in geriatric hospitals can proceed systematically. [Research in Gerontological Nursing, 16(6), 302-311.].

The Benefits of Nursing Home Air Purification on COVID-19 Outcomes: A Natural Experiment

OBJECTIVES

Improving indoor air quality is one potential strategy to reduce the transmission of SARS-CoV-2 in any setting, including nursing homes, where staff and residents have been disproportionately and negatively affected by the COVID-19 pandemic.

DESIGN

Single group interrupted time series.

SETTING AND PARTICIPANTS

A total of 81 nursing homes in a multifacility corporation in Florida, Georgia, North Carolina, and South Carolina that installed ultraviolet air purification in their existing heating, ventilation, and air conditioning systems between July 27, 2020,k and September 10, 2020.

METHODS

We linked data on the date ultraviolet air purification systems were installed with the Nursing Home COVID-19 Public Health File (weekly data reported by nursing homes on the number of residents with COVID-19 and COVID-19 deaths), public data on data on nursing home characteristics, county-level COVID-19 cases/deaths, and outside air temperature. We used an interrupted time series design and ordinary least squares regression to compare trends in weekly COVID-19 cases and deaths before and after installation of ultraviolet air purification systems. We controlled for county-level COVID-19 cases, death, and heat index.

RESULTS

Compared with pre-installation, weekly COVID-19 cases per 1000 residents (-1.69; 95% CI, -4.32 to 0.95) and the weekly probability of reporting any COVID-19 case (-0.02; 95% CI, -0.04 to 0.00) declined in the post-installation period. We did not find any difference pre- and post-installation in COVID-19-related mortality (0.00; 95% CI, -0.01 to 0.02).

CONCLUSIONS AND IMPLICATIONS

Our findings from this small number of nursing homes in the southern United States demonstrate the potential benefits of air purification in nursing homes on COVID-19 outcomes. Intervening on air quality may have a wide impact without placing significant burden on individuals to modify their behavior. We recommend a stronger, experimental design to estimate the causal effect of installing air purification devices on improving COVID-19 outcomes in nursing homes.

Complaints, Restraint, and Seclusion in Massachusetts Inpatient Psychiatric Facilities, 2008-2018

There has been limited research on the quality of inpatient psychiatry, yet policies to expand access have increased, such as the use of Medicaid Section 1115 waivers for treatment in "Institutions for Mental Disease" (IMD). Using data from public records requests, we evaluated complaints, restraint, and seclusion from inpatient psychiatric facilities in Massachusetts occurring from 2008 to 2018, and compared differences in the rates of these events by IMD status. There were 17,962 total complaints, with 48.9% related to safety and 19.9% related to abuse (sexual, physical, verbal), and 92,670 episodes of restraint and seclusion. On average, for every 30 census days in a given facility, restraint, and seclusion occurred 7.47 and 1.81 times, respectively, and a complaint was filed 0.94 times. IMDs had 47.8%, 68.3%, 276.9%, 284.8%, 183.6%, and 236.1% greater rates of restraint, seclusion, overall complaints, substantiated complaints, safety-related complaints, and abuse-related complaints, respectively, compared to non-IMDs. This is the first known study to describe complaints from United States inpatient psychiatric facilities. Policies should strengthen the implementation of patients' rights and patient-centeredness, as well as external critical-incident-reporting systems.

Stronger Impact of COVID-19 in Nursing Homes of a French Region During the Second Pandemic Wave

OBJECTIVES

Quantify the effects of characteristics of nursing homes and their surroundings on the spread of COVID-19 outbreaks and assess the changes in resident protection between the first 2 waves (March 1 to July 31 and August 1 to December 31, 2020).

DESIGN

An observational study was carried out on data on COVID-19 outbreaks extracted from a database that monitored the spread of the virus in nursing homes.

SETTING AND PARTICIPANTS

The study concerned all 937 nursing homes with >10 beds in Auvergne-Rhône-Alpes region, France.

METHODS

The rate of nursing homes with at least 1 outbreak and the cumulative number of deaths were modeled for each wave.

RESULTS

During the second (vs the first wave), the proportion of nursing homes that reported at least 1 outbreak was higher (70% vs 56%) and the cumulative number of deaths more than twofold (3348 vs 1590). The outbreak rate was significantly lower in public hospital-associated nursing homes than in private for-profit ones. During the second wave, it was lower in public and private not-for-profit nursing homes than in private for-profit ones. During the first wave, the probability of outbreak and the mean number of deaths increased with the number of beds (P < .001). During the second wave, the probability of outbreak remained stable in >80-bed institutions and, under proportionality assumption, the mean number of deaths was less than expected in >100-bed institutions. The outbreak rate and the cumulative number of deaths increased significantly with the increase in the incidence of hospitalization for COVID-19 in the surrounding populations.

CONCLUSIONS AND IMPLICATIONS

The outbreak in the nursing homes was stronger during the second than the first wave despite better preparedness and higher availabilities of tests and protective equipment. Solutions for insufficient staffing, inadequate rooming, and suboptimal functioning should be found before future epidemics.

Modeling shield immunity to reduce COVID-19 transmission in long-term care facilities

PURPOSE

Nursing homes and long-term care facilities have experienced severe outbreaks and elevated mortality rates of COVID-19. When available, vaccination at-scale has helped drive a rapid reduction in severe cases. However, vaccination coverage remains incomplete among residents and staff, such that additional mitigation and prevention strategies are needed to reduce the ongoing risk of transmission. One such strategy is that of "shield immunity", in which immune individuals modulate their contact rates and shield uninfected individuals from potentially risky interactions.

METHODS

Here, we adapt shield immunity principles to a network context, by using computational models to evaluate how restructured interactions between staff and residents affect SARS-CoV-2 epidemic dynamics.

RESULTS

First, we identify a mitigation rewiring strategy that reassigns immune healthcare workers to infected residents, significantly reducing outbreak sizes given weekly testing and rewiring (48% reduction in the outbreak size). Second, we identify a preventative prewiring strategy in which susceptible healthcare workers are assigned to immunized residents. This preventative strategy reduces the risk and size of an outbreak via the inadvertent introduction of an infectious healthcare worker in a partially immunized population (44% reduction in the epidemic size). These mitigation levels derived from network-based interventions are similar to those derived from isolating infectious healthcare workers.

CONCLUSIONS

This modeling-based assessment of shield immunity provides further support for leveraging infection and immune status in network-based interventions to control and prevent the spread of COVID-19.

Development of morbidity and mortality of SARS-CoV-2 in nursing homes for the elderly in Frankfurt am Main, Germany, 2020-2022: What protective measures are still required?

Introduction

Nursing-home residents are among the highest risk group in the SARS-CoV-2 pandemic. At the onset of the SARS-CoV-2 pandemic, the majority of all deaths from or with SARS-CoV-2 occurred in long-term care facilities (LTCFs), so that maximum protective measures were mandated for these facilities. This study analyzed the impact of the new virus variants and the vaccination campaign on disease severity and mortality among nursing home residents and staff through 2022 as a basis for determining which protective measures remain necessary and appropriate.

Methods

In five homes in Frankfurt am Main, Germany, with a total capacity for 705 residents, all cases occurring in the facility among residents and staff were recorded and documented (date of birth and diagnosis, hospitalization and death, vaccination status) and were descriptively analyzed with SPSS.

Results

By 31^st August 2022, 496 residents tested positive for SARS-CoV-2, 93 in 2020, 136 in 2021, and 267 in 2022; 14 residents presented with a second SARS-CoV-2 infection in 2022, having previously experienced an infection in 2020 or 2021. The percentage of hospitalizations decreased from 24.7% (2020) and 17.6% (2021) to 7.5% (2022), and the percentage of deaths decreased from 20.4% and 19.1% to 1.5%. In 2021, 61.8% of those infected were vaccinated (at least 2x); in 2022, 86.2% of residents had been vaccinated twice, 84% of whom had already had a booster vaccination. Hospitalization and death rates were significantly higher among the unvaccinated than the vaccinated throughout all years (unvaccinated 21.5% and 18.0%; vaccinated 9.8% and 5.5%; KW test p=0.000). However, this difference was no longer significant under the prevalence of the Omicron variant in 2022 (unvaccinated 8.3% and 0%; p=0.561; vaccinated 7.4% and 1.7%; p=0.604). From 2020 to 2022, 400 employees were documented as infected, with 25 having second infections in 2022. Only one employee showed a second infection in 2021 following the first in 2020. Three employees were hospitalized; no deaths occurred.

Discussion and conclusion

Severe COVID-19 courses occurred with the Wuhan Wild type in 2020, with a high death rate among nursing-home residents. In contrast, during the waves in 2022 with the relatively mildly pathogenic Omicron variant, many infections but few severe courses and deaths were observed among the now mostly vaccinated and boostered nursing-home residents. Given the high immunity of the population and the low pathogenicity of the circulating virus - even in nursing-home residents - protective measures in nursing homes that restrict people's right to self-determination and quality of life no longer seem justified. Instead, the general hygiene rules and the recommendations of the KRINKO (German Commission for Hospital Hygiene and Infection Prevention) on infection prevention should be followed, and the recommendations of the STIKO (German Standing Commission on Vaccination) on vaccination not only against SARS-CoV-2 but also against influenza and pneumococci should be observed.

Characteristics of nursing homes and early preventive measures associated with risk of infection from COVID-19 in Lazio region, Italy: a retrospective case-control study

OBJECTIVES

To understand which organisational-structural characteristics of nursing homes-also referred to as long-term care facilities (LTCFs)-and the preventative measures adopted in response to the pandemic are associated with the risk of a COVID-19 outbreak.

SETTING

LTCFs in Lazio region in Italy.

DESIGN

The study adopts a case-control design.

PARTICIPANTS

We included 141 facilities and 100 provided information for the study. Cases were defined as facilities reporting a COVID-19 outbreak (two or more cases) in March-December 2020; controls were defined as LTCFs reporting one case or zero. The exposures include the structural-organisational characteristics of the LTCFs as reported by the facilities, preventative measures employed and relevant external factors.

RESULTS

Twenty facilities reported an outbreak of COVID-19. In binary logistic regression models, facilities with more than 15 beds were five times more likely to experience an outbreak than facilities with less than 15 beds OR=5.60 (CI 1.61 to 25.12; p value 0.002); admitting new residents to facilities was associated with a substantially higher risk of an outbreak: 6.46 (CI 1.58 to 27.58, p value 0.004). In a multivariable analysis, facility size was the only variable that was significantly associated with a COVID-19 outbreak OR= 5.37 (CI 1.58 to 22.8; p value 0.012) for larger facilities (>15 beds) versus smaller (<15 beds). Other characteristics and measures were not associated with an outbreak.

CONCLUSION

There was evidence of a higher risk of COVID-19 in larger facilities and when new patients were admitted during the pandemic. All other structural-organisational characteristics and preventative measures were not associated with an outbreak. This finding calls into question existing policies, especially where there is a risk of harm to residents. One such example is the restriction of visitor access to facilities, resulting in the social isolation of residents.

Relationship between nursing home COVID-19 outbreaks and staff neighborhood characteristics

The COVID-19 pandemic has been particularly deadly for residents of nursing homes and other long-term care facilities. This paper analyzes COVID-19 deaths at nursing homes during the first wave of the pandemic in the United States during the spring and early summer 2020. By combining data on facility-level COVID-19 deaths during this period with data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics were a large and significant predictor of COVID-19 nursing home deaths. Even after controlling for the county where a facility is located, one standard deviation increases in average staff neighborhood (Census tract) population density, public transportation use, and non-white share were associated with 1.3 (p < .001), 1.4 (p < .001), and 0.9 (p < .001) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home’s own neighborhood characteristics. These results suggest COVID-19 outbreaks in staff communities can have large consequences for the facilities where they work, even in highly-rated facilities, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.

COVID-19 in Long-Term Care Facilities: A Rapid Review of Infection Correlates and Impacts on Mental Health and Behaviors

BACKGROUND

Long-term care facilities (LTCFs) with compact, group-living arrangements have become COVID-19 hot spots during the pandemic. Systematic research is needed to understand factors associated with COVID-19 infections in LTCFs and the inadvertent effects of preventive measures adopted by LTCFs.

OBJECTIVES

This rapid review identifies factors associated with LTCF residents' COVID-19 infections and the impacts of the pandemic and the corresponding preventive measures on residents' mental health and behavioral problems.

METHODS

Following the preferred reporting items for systematic reviews and meta-analyses guidelines, we identified and reviewed relevant literature in Medline, PsycINFO, and AgeLine.

RESULTS

Thirty-seven articles were identified and reviewed, including 30 reporting factors associated with COVID-19 infections in LTCFs and seven reporting the impact of the pandemic and corresponding prevention measures on LTCF residents. Results revealed four domains of factors associated with COVID-19 infections: facility physical environments, resident characteristics, facility management and testing, and community factors. The pandemic and infection control measures increased residents' depression, anxiety, loneliness, and behavioral problems (e.g., agitation, hallucinations). Residents without cognitive impairments were more vulnerable to these adverse effects.

CONCLUSION AND IMPLICATIONS

LTCF managers/policymakers and healthcare designers can help mitigate COVID-19 infections by (1) providing additional resources to vulnerable LTCFs; (2) enhancing the training of personal protective equipment use and guideline compliance; and (3) investing in amenities, such as sinks, quarantine rooms, and outdoor spaces. Digital activities and accessible green spaces can mitigate mental health and behavior issues. Future LTCF design can benefit from flexible spaces, natural ventilation, and reducing crowding.

[The SARS-CoV-2 Pandemic in Long-Term Care Facilities for the Elderly: Analysis of Data from Frankfurt am Main, Germany, March 2020 - September 2021]

BACKGROUND

Residents in long-term care facilities (LTCF) are particularly vulnerable during the SARS-CoV-2 pandemic. In the first wave of the pandemic in many countries, 30-70% of all deaths from or with SARS-CoV-2 were LTCF residents, although their proportion in the population is typically less than 1%. Findings from LTCFs in Frankfurt am Main (March 2020-September 2021) are presented below and discussed in terms of necessary improvements.

MATERIAL AND METHODS

The reports of positive PCR tests for SARS-CoV-2 in residents and staff of the LTCF in Frankfurt am Main and their symptoms were descriptively evaluated. In addition, the total deaths in nursing homes from 2018 to June 2021 were surveyed per quarter.

RESULTS

In the first pandemic wave (March-May 2020), 111 SARS-CoV-2-positive LTCF residents were reported to the Public Health Department in Frankfurt am Main, of whom 40% were asymptomatic, 48% were hospitalized, and 23% died. In the subsequent pandemic phases through September 30, 2021, additional 1196 residents infected with SARS-CoV-2 were reported, with most of them being asymptomatic (70%); they were hospitalized less frequently (27%). Mortality was also lower (17.6%). Overall mortality in LTCF was 7.6% higher in 2020 than in 2019 and 1.1% higher than in the "flu year" of 2018.

DISCUSSION

In contrast to the first wave, when only a few LTCF residents contracted COVID-19, in the second pandemic wave in autumn/winter 2020/21, with high incidences in the general population, SARS-CoV-2 outbreaks in LTCF in Frankfurt could not be prevented, despite extensive hygiene, infection prevention, and contact mitigation measures (including visitor restrictions) that massively limited residents' quality of life and their personal rights. Only when vaccination rates increased among residents and staff from April 2021 onwards, there were no massive outbreaks. To better protect LTCF residents, an appropriate balance was called for between protecting against infection and avoiding collateral damage by maintaining the freedom and quality of life of nursing home residents as best as possible.

The interplay between infection risk factors of SARS-CoV-2 and mortality: a cross-sectional study from a cohort of long-term care nursing home residents

BACKGROUND

Covid-19 pandemic has particularly affected older people living in Long-term Care settings in terms of infection and mortality.

METHODS

We carried out a cross-sectional analysis within a cohort of Long-term care nursing home residents between March first and June thirty, 2020, who were ≥ 65 years old and on whom at least one PCR test was performed. Socio-demographic, comorbidities, and clinical data were recorded. Facility size and community incidence of SARS-CoV-2 were also considered. The outcomes of interest were infection (PCR positive) and death.

RESULTS

A total of 8021 residents were included from 168 facilities. Mean age was 86.4 years (SD = 7.4). Women represented 74.1%. SARS-CoV-2 infection was detected in 27.7% of participants, and the overall case fatality rate was 11.3% (24.9% among those with a positive PCR test). Epidemiological factors related to risk of infection were larger facility size (pooled aOR 1.73; P < .001), higher community incidence (pooled aOR 1.67, P = .04), leading to a higher risk than the clinical factor of low level of functional dependence (aOR 1.22, P = .03). Epidemiological risk factors associated with mortality were male gender (aOR 1.75; P < .001), age (pooled aOR 1.16; P < .001), and higher community incidence (pooled aOR 1.19, P = < 0.001) whereas clinical factors were low level of functional dependence (aOR 2.42, P < .001), Complex Chronic Condition (aOR 1.29, P < .001) and dementia (aOR 1.33, P <0.001). There was evidence of clustering for facility and health area when considering the risk of infection and mortality (P < .001).

CONCLUSIONS

Our results suggest a complex interplay between structural and individual factors regarding Covid-19 infection and its impact on mortality in nursing-home residents.

Staffing Levels and COVID-19 Infections and Deaths in Korean Nursing Homes

The novel coronavirus disease 2019 (COVID-19) spread rapidly worldwide. Nursing home (NH) residents are the most vulnerable high-risk population to infection. Professional registered nurses' (RNs') infection control is irreplaceable. We used a secondary data analysis method using the government's senior citizen welfare department large data set about all NHs (N = 3,389) across Korea between January 20 and October 20, 2020. Bed size positively associated with the mortality rate (No. of COVID-19 resident deaths / No. of total residents) (p = .048). When the proportion of RNs to total nursing staff was higher, the infection rate was 0.626% lower (p = .049), the mortality rate was 0.088% lower (p = .076), the proportion of confirmed COVID-19 cases per resident out of the total number of NHs was 44.472% lower (p = .041), and the proportion of confirmed COVID-19 deaths per resident out of the total number of NHs was 6.456% lower (p = .055). This study highlighted nurse staffing criteria and suggests that increasing RNs in NHs will reduce infection and mortality rates during the COVID-19 pandemic. We strongly suggest NHs hire at least one RN per day to properly function, and a minimum of four RNs to provide a fully competent RN workforce in long-term care settings in Korean NHs.

Nursing Home Design and COVID-19: Implications for Guidelines and Regulation

OBJECTIVES

Nursing homes (NHs) are important health care and residential environments for the growing number of frail older adults. The COVID-19 pandemic highlighted the vulnerability of NHs as they became COVID-19 hotspots. This study examines the associations of NH design with COVID-19 cases, deaths, and transmissibility and provides relevant design recommendations.

DESIGN

A cross-sectional, nationwide study was conducted after combining multiple national data sets about NHs.

SETTING AND PARTICIPANTS

A total of 7785 NHs were included in the study, which represent 50.8% of all Medicare and/or Medicaid NH providers in the United States.

METHODS

Zero-inflated negative binomial models were used to predict the total number of COVID-19 resident cases and deaths, separately. The basic reproduction number (R0) was calculated for each NH to reflect the transmissibility of COVID-19 among residents within the facility, and a linear regression model was estimated to predict log(R0 - 1). Predictors of these models included community factors and NHs' resident characteristics, management and rating factors, and physical environmental features.

RESULTS

Increased percentage of private rooms, larger living area per bed, and presence of a ventilator-dependent unit are significantly associated with reductions in COVID-19 cases, deaths, and transmissibility among residents. After setting the number of actual residents as the exposure variable and controlling for staff cases and other variables, increased number of certified beds in the NH is associated with reduced resident cases and deaths. It also correlates with reduced transmissibility among residents when other risk factors, including staff cases, are controlled.

CONCLUSIONS AND IMPLICATIONS

Architectural design attributes have significant impacts on COVID-19 transmissions in NHs. Considering the vulnerability of NH residents in congregated living environments, NHs will continue to be high-risk settings for infection outbreaks. To improve safety and resilience of NHs against future health disasters, facility guidelines and regulations should consider the need to increase private rooms and living areas.

County-Level Social Determinants of Health and COVID-19 in Nursing Homes, United States, June 1, 2020-January 31, 2021

OBJECTIVES

Nursing homes are a primary setting of COVID-19 transmission and death, but research has primarily focused only on factors within nursing homes. We investigated the relationship between US nursing home-associated COVID-19 infection rates and county-level and nursing home attributes.

METHODS

We constructed panel data from the Centers for Medicare & Medicaid Services (CMS) minimum dataset, CMS nursing home data, 2010 US Census data, 5-year (2012-2016) American Community Survey estimates, and county COVID-19 infection rates. We analyzed COVID-19 data from June 1, 2020, through January 31, 2021, during 7 five-week periods. We used a maximum likelihood estimator, including an autoregressive term, to estimate effects and changes over time. We performed 3 model forms (basic, partial, and full) for analysis.

RESULTS

Nursing homes with nursing (0.005) and staff (0.002) shortages had high COVID-19 infection rates, and locally owned (-0.007) or state-owned (-0.025) and nonprofit (-0.011) agencies had lower COVID-19 infection rates than privately owned agencies. County-level COVID-19 infection rates corresponded with COVID-19 infection rates in nursing homes. Racial and ethnic minority groups had high nursing home-associated COVID-19 infection rates early in the study. High median annual personal income (-0.002) at the county level correlated with lower nursing home-associated COVID-19 infection rates.

CONCLUSIONS

Communities with low rates of nursing home infections had access to more resources (eg, financial resources, staffing) and likely had better mitigation efforts in place earlier in the pandemic than nursing homes that had access to few resources and poor mitigation efforts. Future research should address the social and structural determinants of health that are leaving racial and ethnic minority populations and institutions such as nursing homes vulnerable during times of crises.

SARS-CoV-2 in Nursing Homes: Analysis of Routine Surveillance Data in Four European Countries

Transmission of SARS-CoV-2 in nursing homes is poorly documented. Using surveillance data of 228 European private nursing homes, we estimated weekly SARS-CoV-2 incidences among 21,467 residents and 14,371 staff members, compared to that in the general population, between August 3, 2020, and February 20, 2021. We studied the outcomes of "episodes of introduction" where one case was first detected and computed attack rates, reproduction ratio (R), and dispersion parameter (k). Out of 502 episodes of SARS-CoV-2 introduction, 77.1% (95%CI, 73.2%-80.6%) led to additional cases. Attack rates were highly variable, ranging from 0.4% to 86.5%. The R was 1.16 (95%CI, 1.11-1.22) with k at 2.5 (95%CI, 0.5-4.5). The timing of viral circulation in nursing homes did not mirror that in the general population (p-values<0.001). We estimated the impact of vaccination in preventing SARS-CoV-2 transmission. Before vaccination's roll-out, a cumulated 5,579 SARS-CoV-2 infections were documented among residents and 2,321 among staff. Higher staffing ratio and previous natural immunization reduced the probability of an outbreak following introduction. Despite strong preventive measures, transmission likely occurred, regardless of building characteristics. Vaccination started on January 15, 2021, and coverage reached 65.0% among residents, and 42.0% among staff by February 20, 2021. Vaccination yielded a 92% reduction (95%CI, 71%-98%) of outbreak probability, and lowered R to 0.87 (95%CI, 0.69-1.10). In the post-pandemic era, much attention will have to be paid to multi-lateral collaboration, policy making, and prevention plans.

A Multistate Comparison Study of COVID-19 Cases Among Accredited and Nonaccredited Nursing Homes

Widely acknowledged is the disproportionate number of COVID-19 cases among nursing home residents. This observational study examined the relationship between accreditation status and COVID-19 case rates in states where the numbers and proportions of Joint Commission accredited facilities made such comparisons possible (Illinois (IL), Florida (FL), and Massachusetts (MA)). COVID-19 data were accessed from the Centers for Medicare & Medicaid Services (CMS) Nursing Home Compare Public Use File, which included retrospective COVID-19 data submitted by nursing homes to the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network. The outcome variable was the total number of nursing home-identified COVID-19 cases from June 2020 to January 2021. Joint Commission accreditation status was the independent variable. Mediating factors included state, and county-level case rates. Increases in the county rate had a significant association with higher nursing home COVID-19 case rates (p < .001). After adjusting for county case rates, no differences were observed in the mean group case rates for accredited and nonaccredited nursing homes. However, comparing predicted case rates to actual case rates revealed that accredited nursing homes were more closely aligned with their predicted rates. Performance of the nonaccredited nursing homes was more variable and had proportionally more outliers compared to accredited nursing homes. Community prevalence of COVID-19 is the strongest predictor of nursing home cases. While accreditation status did not have an impact on overall mean group performance, nonaccredited nursing homes had greater variation in performance and a higher proportion of negative outliers. Accreditation was associated with more consistent performance during the COVID-19 pandemic, despite being located in counties with a higher prevalence of COVID-19.

Impact of excluding nursing home COVID-19 cases when assessing the relationship between county-level social distancing behavior and COVID-19 cases across the US during the early phase of the pandemic, February 2020-May 2020

OBJECTIVES

To conduct a cross-sectional nationwide study examining how exclusion of nursing home COVID-19 cases influences the association between county level social distancing behavior and COVID-19 cases throughout the US during the early phase of the pandemic (February 2020-May 2020).

METHODS

Using county-level COVID-19 data and social distancing metrics from tracked mobile devices, we investigated the impact social distancing had on a county's total COVID-19 cases (cases/100,000 people) between when the first COVID-19 case was confirmed in a county and May 31st, 2020 when most statewide social distancing measures were lifted, representing the pandemic's exponential growth phase. We created a mixed-effects negative binomial model to assess how implementation of social distancing measures when they were most stringent (March 2020-May 2020) influenced total COVID-19 cases while controlling for social distancing and COVID-19 related covariates in two scenarios: (1) when COVID-19 nursing home cases are not excluded from total COVID-19 cases and (2) when these cases are excluded. Model findings were compared to those from February 2020, a baseline when social distancing measures were not in place. Marginal effects at the means were generated to further isolate the influence of social distancing on COVID-19 from other factors and determine total COVID-19 cases during March 2020-May 2020 for the two scenarios.

RESULTS

Regardless of whether nursing home COVID-19 cases were excluded from total COVID-19 cases, a 1% increase in average % of mobile devices leaving home was significantly associated with a 5% increase in a county's total COVID-19 cases between March 2020-May 2020 and about a 2.5% decrease in February 2020. When the influence of social distancing was separated from other factors, the estimated total COVID-19 cases/100,000 people was comparable throughout the range of social distancing values (25%-45% of mobile phone devices leaving home between March 2020-May 2020) when nursing home COVID-19 cases were not excluded (25% of mobile phones leaving home: 163.84 cases/100,000 people (95% CI: 121.81, 205.86), 45% of mobile phones leaving home: 432.79 cases/100,000 people (95% CI: 256.91, 608.66)) and when they were excluded (25% of mobile phones leaving home: 149.58 cases/100,000 people (95% CI: 111.90, 187.26), 45% of mobile phones leaving home: 405.38 cases/100,000 people (95% CI: 243.14, 567.62)).

CONCLUSIONS

Exclusion of nursing home COVID-19 cases from total COVID-19 case counts has little impact when estimating the relationship between county-level social distancing and preventing COVID-19 cases with additional research needed to see whether this finding is also observed for COVID-19 growth rates and mortality.

Factors associated with transmission of COVID-19 in long-term care facility outbreaks

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a disproportionate impact on residents in long-term care facilities (LTCFs).

Aim

To identify risk factors associated with outbreak severity to inform current outbreak management and future pandemic preparedness planning efforts.

Methods

A retrospective cohort study design was used to evaluate the association between non-modifiable factors (facility building, organization level, and resident population characteristics), modifiable factors (measured through an assessment tool for infection prevention and control (IPC) and pandemic preparedness), and severity of COVID-19 outbreaks (attack rate) in LTCFs.

Findings

From March 1^st, 2020 to January 10^th, 2021, a total of 145 exposures to at least one confirmed case of COVID-19 in 82 LTCFs occurred. Risk factors associated with increased outbreak severity were older facility age, a resident (vs staff) index case, and poorer assessment tool performance. Specifically, for every item not met in the assessment tool, a 22% increase in the adjusted rate ratio was observed (1.2; 95% confidence interval: 1.1–1.4) after controlling for other risk factors.

Conclusion

Scores from an assessment tool, older building age, and the index case being a resident were associated with severity of COVID-19 outbreaks in our jurisdiction. The findings reinforce the importance of regularly assessing IPC measures and outbreak preparedness in preventing large outbreaks. Regular, systematic assessments incorporating IPC and outbreak preparedness measures may help mitigate impacts of future outbreaks and inform future pandemic preparedness planning.

SARS-CoV-2 and Wisconsin Nursing Homes: Temporal Dynamics During the COVID-19 Pandemic

OBJECTIVES

Evidence suggests that quality, location, and staffing levels may be associated with COVID-19 incidence in nursing homes. However, it is unknown if these relationships remain constant over time. We describe incidence rates of COVID-19 across Wisconsin nursing homes while examining factors associated with their trajectory during 5 months of the pandemic.

DESIGN

Retrospective cohort study.

SETTING/PARTICIPANTS

Wisconsin nursing homes.

METHODS

Publicly available data from June 1, 2020, to October 31, 2020, were obtained. These included facility size, staffing, 5-star Medicare rating score, and components. Nursing home characteristics were compared using Pearson chi-square and Kruskal-Wallis tests. Multiple linear regressions were used to evaluate the effect of rurality on COVID-19.

RESULTS

There were a total of 2459 COVID-19 cases across 246 Wisconsin nursing homes. Number of beds (P < .001), average count of residents per day (P < .001), and governmental ownership (P = .014) were associated with a higher number of COVID-19 cases. Temporal analysis showed that the highest incidence rates of COVID-19 were observed in October 2020 (30.33 cases per 10,000 nursing home occupied-bed days, respectively). Urban nursing homes experienced higher incidence rates until September 2020; then incidence rates among rural nursing homes surged. In the first half of the study period, nursing homes with lower-quality scores (1-3 stars) had higher COVID-19 incidence rates. However, since August 2020, incidence was highest among nursing homes with higher-quality scores (4 or 5 stars). Multivariate analysis indicated that over time rural location was associated with increased incidence of COVID-19 (β = 0.05, P = .03).

CONCLUSIONS AND IMPLICATIONS

Higher COVID-19 incidence rates were first observed in large, urban nursing homes with low-quality rating. By October 2020, the disease had spread to rural and smaller nursing homes and those with higher-quality ratings, suggesting that community transmission of SARS-CoV-2 may have propelled its spread.

Quality of Care and Outcomes Among a Diverse Group of Long-Term Care Residents With Alzheimer's Disease and Related Dementias

ObjectivesThis article assessed whether disparities among ADRD Medicare beneficiaries existed in five different long-stay quality measures. Methods: We linked individual-level data and facility-level characteristics. The main quality outcomes included whether residents: 1) were assessed/appropriately given the seasonal influenza vaccine; 2) received an antipsychotic medication; 3) experienced one/more falls with major injury; 4) were physically restrained; and 5) lost too much weight. Results: In 2016, there were 1,005,781 Medicare Advantage and fee-for-service long-term residents. About 78% were White, 13% Black, 2% Asian/Pacific Islander (Asian/PI), 6% Hispanic, and 0.4% American Indian/Alaska Native (AI/AN). Whites reported higher use of antipsychotic medications along with Hispanics and AI/AN (28%, 28%, and 27%, respectively). Similarly, Whites and AIs/ANs reported having one/more falls compared to the other groups (9% and 8%, respectively). Discussion: Efforts to understand disparities in access and quality of care among American Indians/Alaska Natives are needed, especially post-pandemic.

Risk factors for COVID-19 deaths among elderly nursing home Medicare beneficiaries in the pre-vaccine period

BACKGROUND

Evaluate pre-vaccine pandemic period COVID-19 death risk factors among nursing home (NH) residents.

METHODS

Retrospective cohort study covering Medicare fee-for-service beneficiaries ages ≥65 residing in U.S. NHs. We estimated adjusted hazard ratios (HRs) using multivariate Cox proportional hazards regressions.

RESULTS

Among 608,251 elderly NH residents, 57,398 (9.4%) died of COVID-related illness April 1 to December 22, 2020. About 46.9% (26,893) of these COVID-19 deaths occurred without prior COVID-19 hospitalizations. We observed a consistently increasing age trend for COVID-19 deaths. Racial/ethnic minorities generally shared a similarly high risk of NH COVID-19 deaths with Whites. NH facility characteristics including for-profit ownership and low health inspection ratings were associated with higher death risk. Resident characteristics, including male (HR 1.69), end-stage renal disease (HR 1.42), cognitive impairment (HR 1.34), and immunocompromised status (HR 1.20) were important death risk factors. Other individual-level characteristics were less predictive of death than they were in community-dwelling population.

CONCLUSIONS

Low NH health inspection ratings and private ownership contributed to COVID-19 death risks. Nearly half of NH COVID-19 deaths occurred without prior COVID-19 hospitalization and older residents were less likely to get hospitalized with COVID-19. No substantial differences were observed by race/ethnicity and socioeconomic status for NH COVID-19 deaths.

A systematic review of the associations between care home ownership and COVID-19 outbreaks, infections and mortality

Social care markets often rely on the for-profit sector to meet service demand. For-profit care homes have been reported to suffer higher rates of coronavirus disease 2019 (COVID-19) infections and deaths, but it is unclear whether these worse outcomes can be attributed to ownership status. To address this, we designed and prospectively registered a living systematic review protocol ( CRD42020218673 ). Here we report on the systematic review and quality appraisal of 32 studies across five countries that investigated ownership variation in COVID-19 outcomes among care homes. We show that, although for-profit ownership was not consistently associated with a higher risk of a COVID-19 outbreak, there was evidence that for-profit care homes had higher rates of COVID-19 infections and deaths. We also found evidence that for-profit ownership was associated with personal protective equipment (PPE) shortages. Variation in COVID-19 outcomes is not driven by ownership status alone, and factors related to staffing, provider size and resident characteristics were also linked to poorer outcomes. However, this synthesis finds that for-profit status and care home characteristics associated with for-profit status are linked to exacerbated COVID-19 outcomes.

A systematic review of long-term care facility characteristics associated with COVID-19 outcomes

BACKGROUND/OBJECTIVES

The coronavirus disease 2019 (COVID-19) pandemic has taken a disproportionate toll on long-term care facility residents and staff. Our objective was to review the empirical evidence on facility characteristics associated with COVID-19 cases and deaths.

DESIGN

Systematic review.

SETTING

Long-term care facilities (nursing homes and assisted living communities).

PARTICIPANTS

Thirty-six empirical studies of factors associated with COVID-19 cases and deaths in long-term care facilities published between January 1, 2020 and June 15, 2021.

MEASUREMENTS

Outcomes included the probability of at least one case or death (or other defined threshold); numbers of cases and deaths, measured variably.

RESULTS

Larger, more rigorous studies were fairly consistent in their assessment of risk factors for COVID-19 outcomes in long-term care facilities. Larger bed size and location in an area with high COVID-19 prevalence were the strongest and most consistent predictors of facilities having more COVID-19 cases and deaths. Outcomes varied by facility racial composition, differences that were partially explained by facility size and community COVID-19 prevalence. More staff members were associated with a higher probability of any outbreak; however, in facilities with known cases, higher staffing was associated with fewer deaths. Other characteristics, such as Nursing Home Compare 5-star ratings, ownership, and prior infection control citations, did not have consistent associations with COVID-19 outcomes.

CONCLUSION

Given the importance of community COVID-19 prevalence and facility size, studies that failed to control for these factors were likely confounded. Better control of community COVID-19 spread would have been critical for mitigating much of the morbidity and mortality long-term care residents and staff experienced during the pandemic. Traditional quality measures such as Nursing Home Compare 5-Star ratings and past deficiencies were not consistent indicators of pandemic preparedness, likely because COVID-19 presented a novel problem requiring extensive adaptation by both long-term care providers and policymakers.

Estimates of COVID-19 Cases and Deaths Among Nursing Home Residents Not Reported in Federal Data

Importance

Federal data underestimate the impact of COVID-19 on US nursing homes because federal reporting guidelines did not require facilities to report case and death data until the week ending May 24, 2020.

Objective

To assess the magnitude of unreported cases and deaths in the National Healthcare Safety Network (NHSN) and provide national estimates of cases and deaths adjusted for nonreporting.

Design, Setting, and Participants

This is a cross-sectional study comparing COVID-19 cases and deaths reported by US nursing homes to the NHSN with those reported to state departments of health in late May 2020. The sample includes nursing homes from 20 states, with 4598 facilities in 12 states that required facilities to report cases and 7401 facilities in 19 states that required facilities to report deaths. Estimates of nonreporting were extrapolated to infer the national (15 397 facilities) unreported cases and deaths in both May and December 2020. Data were analyzed from December 2020 to May 2021.

Exposures

Nursing home ownership (for-profit or not-for-profit), chain affiliation, size, Centers for Medicare & Medicaid Services star rating, and state.

Main Outcomes and Measures

The main outcome was the difference between the COVID-19 cases and deaths reported by each facility to their state department of health vs those reported to the NHSN.

Results

Among 15 415 US nursing homes, including 4599 with state case data and 7405 with state death data, a mean (SE) of 43.7% (1.4%) of COVID-19 cases and 40.0% (1.1%) of COVID-19 deaths prior to May 24 were not reported in the first NHSN submission in sample states, suggesting that 68 613 cases and 16 623 deaths were omitted nationwide, representing 11.6% of COVID-19 cases and 14.0% of COVID-19 deaths among nursing home residents in 2020.

Conclusions and Relevance

These findings suggest that federal NHSN data understated total cases and deaths in nursing homes. Failure to account for this issue may lead to misleading conclusions about the role of different facility characteristics and state or federal policies in explaining COVID outbreaks.

U.S. Nursing Home Quality Ratings Associated with COVID-19 Cases and Deaths

Objectives

To inform future policies and disaster preparedness plans in the vulnerable nursing home setting, we need greater insight into the relationship between nursing homes’ (NHs’) quality and the spread and severity of COVID-19 in NH facilities. We therefore extend current evidence on the relationships between NH quality and resident COVID-19 infection rates and deaths, taking into account NH structural characteristics and community characteristics.

Design

Cross-sectional study.

Setting and Participants

15,390 Medicaid- and Medicare-certified NHs.

Methods

We obtained and merged the following data sets: (1) COVID-19 weekly data reported by each nursing home to the Centers for Disease Control and Prevention’s National Healthcare Safety Network, (2) Centers for Medicare & Medicaid Services Five Star Quality Rating System, (3) county-level COVID-19 case counts, (4) county-level population data, and (5) county-level sociodemographic data.

Results

Among 1-star NHs, there were an average of 13.19 cases and 2.42 deaths per 1000 residents per week between May 25 and December 20, 2020. Among 5-star NHs, there were an average of 9.99 cases and 1.83 deaths per 1000 residents per week. The rate of confirmed cases of COVID-19 was 31% higher among 1-star NHs compared with 5-star NHs [model 1: incidence rate ratio (IRR) 1.31, 95% confidence interval (CI) 1.23-1.39], and the rate of COVID-19 deaths was 30% higher (IRR 1.30, 95% CI 1.20, 1.41). These associations were only partially explained by differences in community spread of COVID-19, case mix, and the for-profit status and size of NHs.

Conclusions and Implications

We found that COVID-19 case and death rates were substantially higher among NHs with lower star ratings, suggesting that NHs with quality much below average are more susceptible to the spread of COVID-19. This relationship, particularly with regard to case rates, can be partially attributed to external factors: lower-rated NHs are often located in areas with greater COVID-19 community spread and serve more socioeconomically vulnerable residents than higher-rated NHs.

Risk Factors Associated with Nursing Home COVID-19 Outbreaks: A Retrospective Cohort Study

Background: The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on nursing homes/long-term care facilities. This study examined the relationship between geography, size, design, organizational characteristics, and implementation of infection prevention and control (IPC) measures and the extent of COVID-19 outbreaks in nursing homes in the Autonomous Province of Trento (Italy) during the time frame of March-May 2020. Methods: The analysis included 57 nursing homes (5145 beds). The association between median cumulative incidence of COVID-19 cases among residents and characteristics of nursing homes was assessed by Mann–Whitney U test, Kruskal–Wallis test or Spearman rho. To evaluate the potential confounding of geographical area, a 2-level random intercept logistic model was fitted, with level 1 units (patients in nursing homes) nested into level 2 units (nursing homes), and “being a COVID-19 case” as the dependent variable. Results: Median cumulative incidence was not significantly associated with any of the variables, except for geographical region (p = 0.002). COVID-19 cases clustered in the part of the province bordering the Italian region most affected by the pandemic (Lombardy) (45.2% median cumulative incidence). Conclusions: Structural/organizational factors and standard IPC measures may not predict the epidemiology of COVID-19 outbreaks and be sufficient alone to protect nursing homes against them.

A Proactive Nursing Home Risk Stratification Model for Disaster Response: Lessons Learned from COVID-19 to Optimize Resource Allocation

A coordinated emergency management response to disaster management in nursing homes is desperately needed globally. During the most recent COVID-19 pandemic, aside from a few exemplary countries, most countries have struggled to protect their nursing home populations. Timely and appropriate allocation of resources to nursing homes during disaster response is a challenging yet crucial task to prevent morbidity and mortality of residents. The responsibility for the management of nursing homes during the pandemic was multifaceted, and responsibilities lay at the national, jurisdictional, and regional levels. Success in managing COVID-19 in nursing homes required all these levels to be aligned and supportive, ideally through management by an emergency response leadership team. However, globally there is a paucity of effective management strategies. This article uses the example of the COVID-19 pandemic to propose a risk stratification system to ensure timely and appropriate allocation of resources to nursing homes during disaster preparation and management. Nursing homes should be risk-stratified according to 4 domains: risk of intrusion, capability for outbreak containment, failure in organizational capability, and failure in the availability of community and health care supports. Risk stratification should also consider factors such as current levels of community transmission, if applicable, and geographic location of nursing homes and services. Early identification of nursing homes at risk for infectious disease, or disasters, and targeted allocation of resources might help reduce the number of outbreaks, lower the mortality, and preserve community supports such as acute hospital services. The next step is to debate this concept to validate the selected variables and then develop and pilot test a risk stratification tool for use.

Management of diabetes in elderly patients during the COVID-19 pandemic: current and future perspectives

Introduction: The COVID-19 pandemic has affected the entire population with the most deleterious effects in elders. Elders, especially those with diabetes, are at the highest risk of COVID-19 related adverse outcomes and mortality. This is usually linked to the comorbidities that accumulate with age, diabetes-related chronic inflammation, and the pandemic's psychosocial effects.Areas covered: We present some approaches to manage these complicated elderly patients with diabetes during the COVID-19 pandemic. In the inpatient setting, we suggest similar (pre-pandemic) glycemic targets and emphasize the importance of using IV insulin and possible use of continuous glucose monitoring to reduce exposure and PPE utilization. Outside the hospital, we recommend optimal glycemic control within the limits imposed by considerations of safety. We also describe the advantages and challenges of using various technological platforms in clinical care.Expert opinion: The COVID-19 pandemic has lifted the veil off serious deficiencies in the infrastructures for care at both the individual level and the population level and also highlighted some of the strengths, all of which affect individuals with diabetes and COVID-19. We anticipate that things will not return to 'normal' after the COVID-19 pandemic has run its course, but rather they will be superseded by 'New Normal.'

COVID-19 Cases and Death in Nursing Homes: The Role of Racial and Ethnic Composition of Facilities and Their Communities

OBJECTIVES

To examine the extent to which the racial and ethnic composition of nursing homes (NHs) and their communities affects the likelihood of COVID-19 cases and death in NHs, and whether and how the relationship between NH characteristics and COVID-19 cases and death varies with the racial and ethnic composition of the community in which an NH is located.

METHODS AND DESIGN

Centers for Medicare & Medicare Services Nursing Home COVID-19 data were linked with other NH- or community-level data (eg, Certification and Survey Provider Enhanced Reporting, Minimum Data Set, Nursing Home Compare, and the American Community Survey).

SETTING AND PARTICIPANTS

NHs with more than 30 occupied beds (N=13,123) with weekly reported NH COVID-19 records between the weeks of June 7, 2020, and August 23, 2020. Measurements and model: Weekly indicators of any new COVID-19 cases and any new deaths (outcome variables) were regressed on the percentage of black and Hispanic residents in an NH, stratified by the percentage of blacks and Hispanics in the community in which the NH was located. A set of linear probability models with NH random effects and robust standard errors were estimated, accounting for other covariates.

RESULTS

The racial and ethnic composition of NHs and their communities were both associated with the likelihood of having COVID-19 cases and death in NHs. The racial and ethnic composition of the community played an independent role in the likelihood of COVID-19 cases and death in NHs, even after accounting for the COVID-19 infection rate in the community (ie, daily cases per 1000 people in the county). Moreover, the racial and ethnic composition of a community modified the relationship between NH characteristics (eg, staffing) and the likelihoods of COVID-19 cases and death.

CONCLUSIONS AND IMPLICATIONS

To curb the COVID-19 outbreaks in NHs and protect vulnerable populations, efforts may be especially needed in communities with a higher concentration of racial and ethnic minorities. Efforts may also be needed to reduce structural racism and address social risk factors to improve quality of care and population health in communities of color.

A retrospective cohort study of risk factors for mortality among nursing homes exposed to COVID-19 in Spain

Long-term care (LTC) facilities have shown remarkably high mortality rates during the coronavirus disease 2019 (COVID-19) outbreak in many countries¹, and different risk factors for mortality have been identified in this setting^2-5. Using facilities as the unit of analysis, we investigated multiple variables covering facility characteristics and socioeconomic characteristics of the geographic location to identify risk factors for excess mortality from a comprehensive perspective. Furthermore, we used a clustering approach to detect patterns in datasets and generate hypotheses regarding potential relationships between types of nursing homes and mortality trends. Our retrospective analysis included 167 nursing homes providing LTC to 8,716 residents during the COVID-19 outbreak in Catalonia (northeast Spain). According to multiple regression analysis, COVID-19-related and overall mortality at the facility level were significantly associated with a higher percentage of patients with complex diseases, lower scores on pandemic preparedness measures and higher population incidence of COVID-19 in the surrounding population. When grouping nursing homes into eight clusters based on common features, we found higher mortality rates in four clusters, mainly characterized by a higher proportion of residents with complex chronic conditions or advanced diseases, lower scores on pandemic preparedness, being located in rural areas and larger capacity, respectively.

The Association of Nursing Home Characteristics and Quality with Adverse Events After a Hospitalization

BACKGROUND/OBJECTIVES

We previously found high rates of adverse events (AEs) for long-stay nursing home residents who return to the facility after a hospitalization. Further evidence about the association of AEs with aspects of the facilities and their quality may support quality improvement efforts directed at reducing risk.

DESIGN

Prospective cohort analysis.

SETTING AND PARTICIPANTS

32 nursing homes in the New England states. A total of 555 long-stay residents contributed 762 returns from hospitalizations.

METHODS

We measured the association between AEs developing in the 45 days following discharge back to long-term care and characteristics of the nursing homes including bed size, ownership, 5-star quality ratings, registered nurse and nursing assistant hours, and the individual Centers for Medicare & Medicaid Services (CMS) quality indicators. We constructed Cox proportional hazards models controlling for individual resident characteristics that were previously found associated with AEs.

RESULTS

We found no association of AEs with most nursing home characteristics, including 5-star quality ratings and the composite quality score. Associations with individual quality indicators were inconsistent and frequently not monotonic. Several individual quality indicators were associated with AEs; the highest tertile of percentage of residents with depression (4%-25%) had a hazard ratio (HR) of 1.65 [95% confidence interval (CI) 1.16, 2.35] and the highest tertile of the percentage taking antipsychotic medications (18%-35%) had an HR of 1.58 (CI 1.13, 2.21). The percentage of residents needing increased assistance with activities of daily living was statistically significant but not monotonic; the middle tertile (13% to <20%) had an HR of 1.69 (CI 1.16, 2.47).

CONCLUSIONS AND IMPLICATIONS

AEs occurring during transitions between nursing homes and hospitals are not explained by the characteristics of the facilities or summary quality scores. Development of risk reduction approaches requires assessment of processes and quality beyond the current quality measures.

Short-Stay Admissions Associated With Large COVID-19 Outbreaks in Maryland Nursing Homes

At the beginning of the COVID-19 pandemic, some nursing homes (NHs) in Maryland suffered larger outbreaks than others. This study examined how facility characteristics influenced outbreak size. We conducted a retrospective analysis of secondary data from Maryland NHs to identify characteristics associated with large outbreaks, defined as when total resident cases exceeded 10% of licensed beds, from January 1, 2020, through July 1, 2020. Our dataset was unique in its inclusion of short-stay residents as a measure of resident type and family satisfaction as a measure of quality. Facility characteristics were collected prior to 2020. Like other studies, we found that large outbreaks were more likely to occur in counties with high cumulative incidence of COVID-19, and in NHs with more licensed beds or fewer daily certified nursing assistant (CNA) hours. We also found that NHs with a greater proportion of short-stay residents were more likely to have large outbreaks, even after adjustment for other facility characteristics. Lower family satisfaction was not significantly associated with large outbreaks after adjusting for CNA hours. Understanding the characteristics of NHs with large COVID-19 outbreaks can guide facility re-structuring to prevent the spread of respiratory infections in future pandemics.

COVID-19 in long-term care facilities in Frankfurt am Main, Germany: incidence, case reports, and lessons learned

Abstract: As of August 30, 2020, the World Health Organisation (WHO) reported 24,822,800 COVID-19 infections world wide. Severe disease and deaths occur especially in older people with chronic illnesses. Residents of nursing homes are considered to be the most vulnerable group. In this paper, the experiences with COVID-19 in nursing homes in Frankfurt will be presented and discussed.

Materials and methods: Based on the data of the statutory reporting obligation, the reported COVID-19 cases are presented and incidences are calculated in different age groups and among residents of nursing homes. Outbreaks in various homes are described in detail based on the documentation from the public health department.

Results: By August 28, 2020, 2,665 COVID-19 infections were reported in Frankfurt am Main (incidence 351/100,000 inhabitants), including 116 (4.3%) residents of nursing homes (2,416/100,000 residents). Almost half (39%) of all deaths in Frankfurt (n=69; incidence 9.1/100,000) were among nursing home residents (n=27; incidence 558/100,000 nursing home residents), with 22 of them in just one long-term care facility (LTCF). Compared to previous years, the mortality rate in nursing homes did not increase in the first half of 2020. In one home, 75% of residents tested positive for SARS-CoV-2 and 25% died; in two other homes, 6.7% and 14.1% of the residents became infected, and the mortality rate was 0.5% and 1%, resp. In the other 42 homes in the city (3,906 beds), the infection rate remained below 1% and the death rate was 0.1%.

Discussion: In many countries, 30–70% of all deaths occur among nursing home residents, including Frankfurt (39%). An increase in overall mortality compared to previous years was not observed in Frankfurt as a whole or in the nursing homes in the city specifically. Due to the measures taken (monitoring of residents and staff, nursing care in protective clothing, prohibition or restriction of visits, physical distancing, isolation of infected people and quarantining of contact persons), only individual cases of COVID-19 illnesses occurred in nursing home residents in most homes and the outbreaks in the three homes could be stopped. We do not recommend regular nontargeted testing in nursing homes, but rather vigilance and the implementation of good hygiene as well as immediate targeted testing if COVID-19 is suspected in residents or staff. In order to mitigate the considerable negative effects of these measures on the residents, a good balance should be sought between infection prevention and the goal of ensuring self-determination and the residents’ quality of life.

Reply to Comment on COVID-19 Deaths in Long Term Care Facilities - A Critical Piece of the Puzzle

This letter comments on the letter by Tak-kwan Kong.