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Characteristics of U.S. Nursing Homes with COVID ‐19 Cases
Abstract
Background
COVID‐19 has been documented in a large share of nursing homes throughout the United States. This has led to high rates of mortality for residents. In order to understand how to prevent and mitigate future outbreaks, it is imperative that we understand which nursing homes are more likely to experience COVID‐19 cases.
Objective
To examine the characteristics of nursing homes with documented COVID‐19 cases in 30 states reporting individual facilities affected.
Design and setting
We constructed a database of nursing homes with verified COVID‐19 cases as of May 11, 2020 via correspondence with and publicly available reports from state departments of health. We linked this information to nursing home characteristics and used regression analysis to examine association between these characteristics and the likelihood of having a documented COVID‐19 case.
Results
Of 9,395 nursing homes in our sample, 2,949 (31.4%) had a documented COVID‐19 case. Larger facility size, urban location, greater percentage of African American residents, non‐chain status, and state were significantly (p<0.05) related to increased probability of having a COVID‐19 case. Five‐star rating, prior infection violation, Medicaid dependency, and ownership were not significantly related.
Conclusions
COVID‐19 cases in nursing homes are related to facility location and size and not traditional quality metrics such as star rating and prior infection control citations.
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... Among community factors, larger population size or density, urban location, and higher percentage of Black, deprived, or unemployed populations in the community have been related to a higher risk of COVID-19 infection and deaths in NHs. 7e12 In terms of the NH residents' characteristics, NHs with more older, male, non-White, and Medicaid and Medicare residents have been found to be more vulnerable to 7,8,10,12e17 whereas a few studies have reported nonsignificant roles. 8,14 Risk of mortality increased with the percentage of Black residents, age, and cognitive or functional impairment. ...
... Infection control policies have been shown to play significant roles in mitigating COVID-19 within NHs. 18e20 NHs with more prior health deficiencies or complaints were found to be more likely to have a COVID-19 case, 9,16,21 but 2 other studies reported prior infection violations to be insignificant. 7,22 Several studies reported that for-profit NHs have a higher risk compared with nonprofit or government owners, 9,21,23 although nonsignificant relationships have also been reported. 7,24 Furthermore, shortage of nursing staff and lower staff rating have been linked to a higher likelihood of a COVID-19 outbreak in most of the previous studies, 10e12,14,21,23 although a few studies showed insignificant relationships. ...
... 7,22 Several studies reported that for-profit NHs have a higher risk compared with nonprofit or government owners, 9,21,23 although nonsignificant relationships have also been reported. 7,24 Furthermore, shortage of nursing staff and lower staff rating have been linked to a higher likelihood of a COVID-19 outbreak in most of the previous studies, 10e12,14,21,23 although a few studies showed insignificant relationships. 9,22,25 Compared with these 3 domains of variables, the physical environment of NHs (eg, residential density, single-vs. ...
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 datasets about NHs.
Setting and Participants
A total of 7,785 NHs were included in the study, which represent 50.8% of all Medicare and/or Medicaid NH providers in the US.
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 share 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. Increased number of certified beds in the NH is associated with reduced resident cases and deaths, after setting the number of actual residents as the exposure variable and controlling for staff cases. 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.
... Studies of NH COVID-19 cases during 2020 indicated that increases in community rates of COVID-19 were related to increases in COVID-19 cases in the NH (Abrams et al., 2020;Li et al., 2020;Stall et al., 2020). These findings are similar to those found in other studies that reported NHs in urban locations, with more beds, a higher Medicaid occupancy, and greater percentage Black residents were more likely to have COVID cases (Abrams et al., 2020;Chatterjee et al., 2020;Li et al., 2020;Stall et al., 2020;Travers et al., 2021). ...
... Studies of NH COVID-19 cases during 2020 indicated that increases in community rates of COVID-19 were related to increases in COVID-19 cases in the NH (Abrams et al., 2020;Li et al., 2020;Stall et al., 2020). These findings are similar to those found in other studies that reported NHs in urban locations, with more beds, a higher Medicaid occupancy, and greater percentage Black residents were more likely to have COVID cases (Abrams et al., 2020;Chatterjee et al., 2020;Li et al., 2020;Stall et al., 2020;Travers et al., 2021). Findings differ in whether NH ownership, nurse staffing, or quality ratings influenced positive cases or the number of cases (Abrams et al., 2020;Chatterjee et al., 2020;Li et al., 2020). ...
... These findings are similar to those found in other studies that reported NHs in urban locations, with more beds, a higher Medicaid occupancy, and greater percentage Black residents were more likely to have COVID cases (Abrams et al., 2020;Chatterjee et al., 2020;Li et al., 2020;Stall et al., 2020;Travers et al., 2021). Findings differ in whether NH ownership, nurse staffing, or quality ratings influenced positive cases or the number of cases (Abrams et al., 2020;Chatterjee et al., 2020;Li et al., 2020). ...
This study’s aim was to determine nursing home (NH) and county-level predictors of COVID-19 outbreaks in nursing homes (NHs) in the southeastern region of the United States across three time periods. NH-level data compiled from census data and from NH compare and NH COVID-19 infection datasets provided by the Center for Medicare and Medicaid Services cover 2951 NHs located in 836 counties in nine states. A generalized linear mixed-effect model with a random effect was applied to significant factors identified in the final stepwise regression. County-level COVID-19 estimates and NHs with more certified beds were predictors of COVID-19 outbreaks in NHs across all time periods. Predictors of NH cases varied across the time periods with fewer community and NH variables predicting COVID-19 in NH during the late period. Future research should investigate predictors of COVID-19 in NH in other regions of the US from the early periods through March 2021.
... In our study, single-site facilities have a higher attack rate than sites with multiple units that are detached. Isolating residents infected with COVID-19 in traditional dormitorystyle institutional-based care with multiple floors, multipleoccupancy rooms, and narrow corridors is difficult with limited space for single rooms [24,25]. There has been a gradual shift from older designs of ACFs to a smaller and home-based cottage style of care. ...
... Larger facility size and urban location were significantly (P < .001) related to the increased probability of having a COVID-19 case [24]. Although occupancy, related to facility size, had no significant association in our study, higher occupancy rates have been identified as independent risk factors for SARS-CoV-2 infection in other studies [26]. ...
... The physical infrastructure of an ACF presents challenges to the implementation of isolation and social distancing procedure [24]. Sufficient space is required for social distancing; however, shared rooms with multiple occupancy are still prevalent in many facilities around the world [6]. ...
Background
The COVID-19 pandemic has resulted in significant morbidity and mortality in aged care facilities worldwide. The attention of infection control in aged care needs to shift towards the built environment, especially with relation to using the existing space to allow social distancing and isolation. Physical infrastructure of aged care facilities has been shown to present challenges to implementation of isolation procedures. To explore the relationship of the physical layout of aged care facilities on SARS-CoV-2 attack rates among residents, a meta-analysis was conducted.
Methods
Using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocol (PRISMA-P), studies were identified from five databases using a registered search strategy with PROSPERO. Meta-regression analysis for pooled attack rates of SARS-CoV-2 in residents and staff was conducted, with subgroup analysis for physical layout variables such as total number of beds, single rooms, number of floors, number of buildings in facility and staff per 100 beds
Results
We included 41 articles across 11 countries, reporting on 90 657 residents and 6521 staff in 757 facilities. The overall pooled attack rate among residents was 42.0% (95% CI: 38.0-47.0%) and 21.7% (95% CI: 15.0-28.4%) in staff. Attack rates in residents were significantly higher in single-site facilities with standalone buildings than facilities with smaller, detached buildings. Staff-to-bed ratio significantly explains some of the heterogeneity of the attack rate between studies.
Conclusion
The design of aged care facilities should have smaller-sized facilities with adequate space for social distancing.
... Our results are in line with studies of COVID-19 incidence and mortality in NHs, including crowding [19,38], incidence rates in staff [39,40], private ownership [14,41], high occupancy rate [15,36], high residents/staff ratios [42][43][44], large size [45][46][47], severe disability [48,49], urban areas [47], and aging facility building [10,50], which could be a proxy of the NHs physical environment and equipment, and the older could have more deficiencies than the new. In contrast to our results, some studies have found a higher mortality rate in men than women [48]. ...
... Our results are in line with studies of COVID-19 incidence and mortality in NHs, including crowding [19,38], incidence rates in staff [39,40], private ownership [14,41], high occupancy rate [15,36], high residents/staff ratios [42][43][44], large size [45][46][47], severe disability [48,49], urban areas [47], and aging facility building [10,50], which could be a proxy of the NHs physical environment and equipment, and the older could have more deficiencies than the new. In contrast to our results, some studies have found a higher mortality rate in men than women [48]. ...
During the period from March 2020 to January 2021, we performed an analysis of incidence, mortality, and risk factors of COVID-19 in nursing homes (NHs) in two health departments (HDs) of Castellon (Spain) 2021 through epidemiological surveillance and an ecological design. Laboratory-confirmed COVID-19 cases, cumulative incidence rate (CIR), and mortality rate (MR) of 27 NHs were collected. Information of residents, staff, and facilities was obtained by questionnaire. Multilevel Poisson regression models were applied. All NHs in the HDs participated with 2229 residents (median: 83 years old, 67.3% women) and 1666 staff. Among residents, 815 cases (CIR: 34.8 per 100) and 202 deaths (MR: 8.7 per 100, case fatality 21.0%) were reported and, among staff, 296 cases (CIR: 19.2 per 100) without deaths. Residents’ CIR and MR increased with staff CIR, age of the building, residents/staff ratios, occupancy rate, and crowding index; CIR increased with private NH ownership, large NH size, large urban area, and the percentage of women residents; and MR was associated with residents’ severe disabilities. In conclusion, several risk factors of COVID-19 incidence and mortality can be prevented by improving infection and quality controls, ameliorating residents/staff ratios, improving structural facilities, and increasing NH public ownership to avoid new outbreaks.
... In support of the latter hypothesis, several studies have documented the importance of county infection rates in predicting COVID-19 cases and deaths at nursing homes [5,6], while most studies have not found a relationship of outbreaks with star rating or even infection control violations [5,7,8]. However, there has been considerably less evidence on whether and how much geography may matter at finer granularities, particularly as compared to other facility variables such as ownership or star rating. ...
... Are the most exposed facilities also the ones with the lowest wages, or the most non-white residents? If so, these results could offer a mechanism to explain systematically higher deaths at facilities without unions or facilities with fewer white residents that has been documented in other literature [7,10]. Fig 3 shows partial correlations of the staff neighborhood measures with other facility characteristics, controlling for county fixed effects, with a particular focus on measures related to a facility's staffing practices. ...
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.
... This was particularly true in the early stages of the pandemic, when knowledge of the spread and treatment options of the disease was still poor, testing capacity limited, and vaccination unavailable. For example, for the first 5 months of the pandemic, Abrams et al. calculated that 42% of all COVID-19 deaths across 38 U.S. states were reported by nursing homes and other long-term care facilities 4 . In Germany, 681 outbreaks in nursing homes resulting in 12,681 cases were reported during the first wave. ...
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) belongs to the coronavirus family and is characterized by its high transmission competence. Elderly COVID-19 patients are at significantly higher risk of severe course of disease and death. Therefore, outbreaks in nursing homes are particularly challenging for facility managers and health authorities. Here, we report three outbreaks of COVID-19 related to nursing homes (NH01.a, NH02 and NH03) with almost 1000 affected individuals during the first COVID-19 wave in Berlin, Germany. The occurrence of cases and the measures taken were analyzed retrospectively. In all three outbreaks, the index persons were nursing home employees or volunteers. Measures taken were quarantine of contacts, close-meshed tests, separation of the affected housing unit, suspension of admission, ban on visiting, and equipping staff with personal protective equipment, of which there was a shortage in Germany at the beginning of the pandemic. A court-ordered quarantine became necessary for three residents of NH01.a due to cognitive disabilities. In total, 61 persons were tested positive for SARS-CoV-2 in NH01.a, ten persons in NH02, and sixteen persons in NH03. Seventeen patients (27.9%) of NH01.a and three patients (18.8%) of NH03 were referred to hospital. Of all confirmed cases, thirteen (21.3%) related to NH01.a and four (25.0%) related to NH03 died as a result of the infection. Besides one 82 year old volunteer, all deceased persons were residents aged between 66 and 98. Our results emphasize the importance of a previously developed containment and cluster strategy for nursing homes. Due to the particular vulnerability of the residents, immediate action, close cooperation and communication between the facility management, residents, visitors and the health authorities are essential in the case of confirmed COVID-19 cases in healthcare facilities.
... Some exceptions were made for compassionate care, such as end-of-life situations. As of May 2020, FCSs accounted for 42% of COVID-19 deaths despite limiting visitation (Abrams et al., 2020). Beginning in March and updated periodically, the Centers for Medicare and Medicaid Services (CMS) released guidance for visitation restrictions and reopening through a multiphase approach (Quality, Safety and Oversight Group, 2020). ...
... There is growing evidence that urban location and larger facilities increase the risk of infectious disease outbreaks in care homes [40,41]. Larger care home facilities imply managing a greater number of residents including person-to-person contact with a larger number of different residents, staff and visitors, creating opportunities for infectious outbreaks [30]. ...
Background
Infectious disease outbreaks are common in care homes, often with substantial impact on the rates of infection and mortality of the residents, who primarily are older people vulnerable to infections. There is growing evidence that organisational characteristics of staff and facility might play a role in infectious disease outbreaks however such evidence have not previously been systematically reviewed. Therefore, this systematic review aims to examine the impact of facility and staff characteristics on the risk of infectious disease outbreaks in care homes.
Methods
Five databases (MEDLINE, EMBASE, ProQuest, Web of Science, CINAHL) were searched. Studies considered for inclusion were of any design reporting on an outbreak of any infectious disease in one or more care homes providing care for primarily older people with original data on: facility size, facility location (urban/rural), facility design, use of temporary hired staff, staff compartmentalizing, residence of staff, and/or nursing aides hours per resident. Retrieved studies were screened, assessed for quality using CASP, and analysed employing a narrative synthesis.
Results
Sixteen studies (8 cohort studies, 6 cross-sectional studies, 2 case-control) were included from the search which generated 10,424 unique records. COVID-19 was the most commonly reported cause of outbreak ( n = 11). The other studies focused on influenza, respiratory and gastrointestinal outbreaks. Most studies reported on the impact of facility size (n = 11) followed by facility design ( n = 4), use of temporary hired staff ( n = 3), facility location ( n = 2), staff compartmentalizing (n = 2), nurse aides hours (n = 2) and residence of staff (n = 1). Findings suggest that urban location and larger facility size may be associated with greater risks of an infectious disease outbreak. Additionally, the risk of a larger outbreak seems lower in larger facilities. Whilst staff compartmentalizing may be associated with lower risk of an outbreak, staff residing in highly infected areas may be associated with greater risk of outbreak. The influence of facility design, use of temporary staff, and nurse aides hours remains unclear.
Conclusions
This systematic review suggests that larger facilities have greater risks of infectious disease outbreaks, yet the risk of a larger outbreak seems lower in larger facilities. Due to lack of robust findings the impact of facility and staff characteristics on infectious disease outbreaks remain largely unknown.
Prospero
CRD42020213585 .
... The medical facilities in KCF and its patients with severe comorbidities made it such a hard task to manage. In London, the sum of people residing in seven nursing homes (patients and staff) was 718 according to one study and the same goes for USA [13,14]. ...
As the first outbreak of COVID-19 in Wuhan, China, the elder population and those with comorbidities were at higher risk of COVID-19 infection. The mortality rate was also higher in this population. Hence, the management and prevention of this novel disease in nursing homes was of utmost importance. The health management team in Kahrizak Charity Foundation (KCF), a nursing home in Iran with more than 1400 elder or comorbid resident, have tackled the COVID-19 outbreak with a novel approach towards this problem. This commentary aims at sharing the insights and lessons learned in the management of COVID-19 in KCF.
Supplementary information:
The online version contains supplementary material available at 10.1007/s40200-022-01005-3.
... Because routine reporting started in fall 2020, 1.2 million infections among residents and staff nationwide, and >20,000 resident infections and 3000 deaths reported by May 2021 in Georgia alone. 1,2 Nursing homes have high risk of SARS Co-V-2 transmission related somewhat to staffing challenges. 3 Early in the pandemic, several efforts quantified the risk of infection among nursing home staff at roughly 2 times that observed among peers in the community. ...
Objectives
Estimate incidence of and risks for SARS-CoV-2 infection among nursing home staff in the state of Georgia during the 2020/2021 Winter COVID-19 Surge in the U.S.
Design
Serial survey and serologic testing at two time points with 3-month interval exposure assessment.
Setting and Participants
14 nursing homes in the state of Georgia. 203 contracted or employed staff members from 14 participating nursing homes who were seronegative at first timepoint and provided a serology specimen at second timepoint, at which time they reported no COVID-19 vaccination or only very recent vaccination (≤4 weeks).
Methods
Interval infection was defined as seroconversion to antibody presence for both nucleocapsid protein and spike protein. We estimated adjusted odds ratios (aORs) and 95% confidence intervals (95% CIs) by job type, using multivariable logistic regression, accounting for community-based risks including interval community-incidence and interval change in resident infections per bed.
Results
Among 203 eligible staff, 72 (35.5%) had evidence of interval infection. In multivariable analysis among unvaccinated staff, staff SARS-Cov-2 infection induced seroconversion was significantly higher among nurses and certified nursing assistants accounting for race and interval infection incidence in both the community and facility (aOR 5.3, 95% CI 1.0-28.4). This risk persisted but was attenuated when utilizing the full study cohort including those with very recent vaccination.
Conclusions and Implications
Midway through the first year of the pandemic, job type continues to be associated with increased risk for infection despite enhanced infection prevention efforts including routine screening of staff. These results suggest that mitigation strategies, prior to vaccination did not eliminate occupational risk for infection and emphasize critical need to maximize vaccine utilization to eliminate excess risk among front line providers.
... The result has rightly been regarded as a perfect storm [2]. However, more detailed examinations of Covid-19 in LTCF have shown that particular structural factors mediated the impact of the disease, including the size of the facility, the quality of care, and understaffing [3][4][5][6][7][8]. The lack of preparedness as well as short and long-term policy failures also contributed [9,10]. ...
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.
... Similarly, the feedback loops between kin and stranger care are also visible in our COVID-19 responses. During COVID-19, stranger care facilities were initially major conduits of infection [187], with some nations reporting high numbers of infections occurring in hospitals [188][189][190] and care homes [191][192][193][194][195] or among healthcare workers [196][197][198], which can then be seeded back into the community. As stranger care networks become overwhelmed, kin care networks have served a supportive role and absorbed the overflow. ...
The COVID-19 pandemic has revealed an urgent need for a comprehensive, multidisciplinary understanding of how healthcare systems respond successfully to infectious pathogens –and how they fail. This paper contributes a novel perspective that focuses on the selective pressures that shape healthcare systems over evolutionary time. We use a comparative approach to trace the evolution of care-giving and disease control behaviours across species and then map their integration into the contemporary human healthcare system. Self-care and pro-health environmental modification are ubiquitous across animals, while derived behaviours like care for kin, for strangers, and group-level organisational responses have evolved via different selection pressures. We then apply this framework to our behavioural responses to COVID-19 and demonstrate that three types of conflicts are occurring: 1) conflicting selection pressures on individuals, 2) evolutionary mismatches between the context in which our healthcare behaviours evolved and our globalised world of today and 3) evolutionary displacements in which older forms of care are currently dispensed through more derived forms. We discuss the significance of understanding how healthcare systems evolve and change for thinking about the role of healthcare systems in society during and after the time of COVID-19—and for us as a species as we continue to face selection from infectious diseases.
... 10,27 In the United States, mortality in care homes was consistently associated with facility-size, communityincidence of COVID-19, and poverty. 28 We did not have data to identify individuals at the same care homes and the possible clustering of deaths at care homes could not be investigated in our data. Hollinghurst et al 29 analyzed linked primary care and administrative records for the population of Wales and found that care homes showed increased mortality during the first wave of the pandemic. ...
Objective
This study aimed to estimate and compare mortality of care home (CH) residents, and matched community-dwelling controls, during the Covid-19 pandemic from primary care electronic health records in England.
Design
Matched cohort study.
Setting and Participants
Family practices in England in the Clinical Practice Research Datalink Aurum database. There were 83,627 CH residents in 2020, with 26,923 deaths; 80,730 (97%) were matched on age, gender and family practice with 300,445 community-dwelling adults.
Methods
All-cause mortality was evaluated and adjusted rate ratios (RR) by negative binomial regression were adjusted for age, gender, number of long-term conditions, frailty category, region, calendar month or week, and clustering by family practice.
Results
Underlying mortality of care home residents was higher than community controls (RR 5.59, 95% confidence interval 5.23 to 5.99, P<0.001). During April 2020, there was a net increase in mortality of care home residents over that of controls. The mortality rate of CH residents was 27.2 deaths per 1,000 patients per week, compared with 2.31 per 1,000 for controls. Excess deaths for care home residents, above that predicted from pre-pandemic years, peaked between 13th-19th April (men, 27.7, 95% confidence interval 25.1 to 30.3; women, 17.4, 15.9 to 18.8 per 1,000 per week). Compared with CH residents, long-term conditions and frailty were differentially associated with greater mortality in community-dwelling controls.
Conclusions and Implications
Individual-patient data from primary care electronic health records may be used to estimate mortality in care home residents. Mortality is substantially higher than for community-dwelling comparators and showed a disproportionate increase in the first wave of the Covid-19 pandemic. Care home residents require particular protection during periods of high infectious disease transmission.
... These issues make LTCFs particularly vulnerable to fatal COVID-19 outbreaks. In the USA, it was estimated that LTCF residents represented 42% of the total number of COVID deaths [6], with fatality rates reaching up to one-third of residents [7]. ...
Introduction:
In early 2020, the novel SARS-CoV-2 virus began to spread around the world and claim victims. Initially, in the Western world, COVID-19-related mortality was due to illness in long-term care facilities (LTCFs). To manage the COVID-19 crisis in LTCFs in Israel, the Ministry of Health established a task force named "Senior Shield." The task force executed a screening program of weekly polymerase chain reaction (PCR) SARS-CoV-2 tests for LTCF residents and caregivers, and at a later stage, the task force led the Ministry of Health vaccination program at LTCFs. This study aimed to estimate the effectiveness of the BNT162b2 mRNA COVID-19 (Comirnaty) vaccine in reducing COVID-19 morbidity and mortality in LTCF residents.
Methods:
We designed a nationwide cohort study utilizing data from the Senior Shield task force. Residents had received the vaccines starting December 2020. The study follow-up period was 5 months (ending May 2021). We defined four outcomes: (a) documented SARS-CoV-2 infection, defined by a positive PCR test, (b) COVID-19 death, defined by a positive PCR test followed by death, (c) all-cause mortality, defined as death regardless of the result of a PCR test, and (d) a composite endpoint which included documented SARS-CoV-2 infection or death, the earliest of both. We used Kaplan-Meier curves with a log-rank comparison and Cox regression with a time-dependent covariate model to estimate adjusted hazard ratios for vaccine effectiveness (VE). The index date was the date of the first vaccine dose. In unvaccinated residents, the index date was the first date of vaccination in their LTCF.
Results:
A total of 43,596 residents with a mean age of 83 years living in 454 LTCFs were found eligible for this study. Ninety-one percent of the study population received the first vaccine dose (39,482) and 86% received the second vaccine dose (37,656). Estimated VE 28 days after the first vaccine dose (approximately 7 days after the second vaccine dose) was 81.2% for SARS-CoV-2 infection, 85.3% for COVID-related death, 63.7% for all-cause mortality, and 71.1% for the composite endpoint (SARS-CoV-2 infection or death).
Conclusion:
This study shows that the BNT162b2 mRNA COVID-19 vaccine effectively prevents SARS-CoV-2 infection, COVID-19-related death, and all-cause mortality in LTCF residents. Further research is warranted on the effect of the third vaccine (booster) in this population.
... Além disso, observou-se que a probabilidade de ocorrência de casos de COVID-19 é maior em instituições grandes, sem fins lucrativos e em regiões metropolitanas. Corroborando esses achados, examinaram-se as características das ILPIs norteamericanas com casos documentados de COVID-19 e descobriram que as infecções estavam relacionadas à localização (urbana) e ao tamanho (maior que 50 leitos) das instituições (1) . ...
Objective:
to evaluate the adherence of Brazilian long-term care facilities to the World Health Organization Infection Prevention and Control guidance, and assess the association of their size with the adherence to these recommendations.
Method:
cross-sectional study conducted with facilities' managers. Authors developed a 20-item questionnaire based on this guidance, and a global score of adherence, based on the adoption of these recommendations. Adherence was classified as (1) excellent for those who attended ≥14 out of 20 recommendations; (2) good for 10 to 13 items; and (3) low for those with less than ten items. Facilities' sizes were established as small, intermediate, and large according to a two-step cluster analysis. Descriptive statistics and chi-square tests were used at a 5% significance level.
Results:
among 362 included facilities, 308 (85.1%) adhered to 14 or more recommendations. Regarding its size, adherence to screening COVID-19 symptoms of visitors (p=0.037) and isolating patients until they have had two negative laboratory tests (p=0.032) were lower on larger ones compared to medium and small facilities.
Conclusion:
adherence to COVID-19 mitigation measures in Brazilian facilities was considered excellent for most of the recommendations, regardless of the size of the units.
... Also, in studies in which either cases or outbreaks of COVID-19 reports in NH are based on RT-PCR or self-reports, this variation between NH was seen [27,28]. Former research demonstrated a relation between an increased transmission of the virus in the community and the number of outbreaks in NH, indicating a contribution from outside the facility [27,29,30]. Further, we notice a positive correlation between seroprevalences in staff and residents. ...
Seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG antibodies, using dried blood spots, was determined in October–November 2020, among residents and staff randomly selected from 20 nursing homes (NH) geographically distributed in Flanders, Belgium. Sociodemographic and medical data [including coronavirus disease 2019 (COVID-19) symptoms and results of RT-PCR tests] were retrieved using questionnaires. The overall seroprevalence was 17.1% [95% confidence interval (CI) 14.9–19.5], with 18.9% (95% CI 15.9–22.2) of the residents and 14.9% (95% CI 11.9–18.4) of the staff having antibodies, which was higher than the seroprevalence in blood donors. The seroprevalence in the 20 NH varied between 0.0% and 45.0%. Fourteen per cent of the staff with antibodies, reported no typical COVID-19 symptoms, while in residents, 51.0% of those with antibodies had no symptoms. The generalised mixed effect model showed a positive association between COVID-19 symptoms and positive serology, but this relation was weaker in residents compared to staff. This study shows that NH are more affected by SARS-CoV-2 than the general population. The large variation between NH, suggests that some risk factors for the spread among residents and staff may be related to the NH. Further, the results suggest that infected people, without the typical COVID-19 symptoms, might play a role in outbreaks.
... What is known beyond doubt is that long-term care facilities populations are extremely vulnerable and require special care. (22)(23)(24) In the present experience, measures such as personal hygiene, suspension of visits, and staff screening along with universal testing were effective in containing the pandemic. This is one of the first descriptive papers addressing the issue related to long-term care facilities that reports the results and consequences of universal testing using RT-PCR during the COVID-19 pandemic in Brazil. ...
Objective:
To describe the first COVID-19 pandemic at Casa Ondina Lobo, a philanthropic nursing home in São Paulo city, and the containment measures against the pandemic that proved to be effective.
Methods:
Several preventive measures were taken before and during the pandemic, with emphasis on universal testing by reverse transcription polymerase chain reaction for COVID-19. All residents and employees were tested twice in a D9 period.
Results:
Among the 62 residents and 55 employees, in both testing, eight residents and nine employees tested positive for COVID-19. Of 22% of employees and 75% of residents evolved asymptomatic, emphasizing the importance of universal testing for the detection and isolation of these cases. A quarter of residents evolved without any symptoms, however, with COVID-19 signs, reinforcing the importance of monitoring vital signs. The second testing did not detect any new cases among residents, demonstrating the effectiveness of the containment measures, however, it found four new cases among employees. This emphasized their role in COVID-19 outbreaks in nursing homes. Only one patient died, a 12.5% lethality among those known to be infected and a 1.6% mortality in the total population of residents were seen.
Conclusion:
The adoption of appropriate containment measures enabled to contain an COVID-19 pandemic in studied nursing home. Universal reverse transcription polymerase chain reaction testing for COVID-19 has proved to be particularly important and effective.
... Other researchers have observed quite similar results to those presented in this study for nursing homes [12] and skilled nursing facilities [13]. The associated factors they have observed include number of beds, urban/rural, client ethnic background and state. ...
Aims:
To investigate the differences between Sweden, Denmark, Finland and Norway regarding residential/home care units' and frontline managers' background factors, the resources allocated and measures taken during the initial phases of the COVID-19 pandemic, and whether and how these differences were associated with COVID-19 among older people in residential/home units.
Methods:
Register- and survey-based data. Responses from managers in municipal and private residential/home units. Number of municipal COVID-19 cases from national registries. Multilevel logistic multivariate regression analysis with presence of COVID-19 among older people in residential/home units as the outcome variable.
Results:
The proportions of residential/home units with client COVID-19 cases, mid-March-April 2020 were Denmark 22.7%, Finland 9.0%, Norway 9.7% and Sweden 38.8%, most cases found in clusters. The proportions were similar among employees. Client likelihood of having COVID-19 was six-fold higher if the employees had COVID-19. Mean client cases per residential/home unit were Denmark 0.78, Finland 0.46, Norway 0.22 and Sweden 1.23. For the same municipal infection incidence class, Sweden's mean client infection levels were three-fold those of other countries. The regression analysis variables country, municipal COVID-19 incidence proportion, and care type were associated with client cases at p ⩽ .001. Compared with Denmark, the odds ratios (ORs) for Sweden, Norway and Finland were 1.86, 0.41 and 0.35 respectively. The variable difficulties in preventive testing had an OR of 1.56, p ⩽ .05.
Conclusions:
Municipal COVID-19 incidence, employee cases, and the lack of testing resources somewhat explained the confirmed COVID-19 cases among older people in residential/home units. A two- to five-fold unexplained inter-country difference in ORs in the multivariate analyses was notable. The level of protection of vulnerable older clients in municipal and private residential/home units differed between the included countries.
... People with disabilities who require assistance with activities of daily living (ADLs) may live in a long-term care facility or independently with some form of caregiving support [17,18]. Although extensive epidemiological and modeling studies have identified risk factors and mitigation strategies for COVID-19 outbreaks in long-term care facilities [19][20][21][22][23][24][25], there have not been similar studies of independently-housed disabled people and their caregivers. Caregivers are often indispensable for the health and independence of disabled people because they [29]. ...
A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to determine which interventions can best prevent infections of disabled people and their caregivers. To accomplish this, we simulate COVID-19 transmission with a compartmental model that includes susceptible, exposed, asymptomatic, symptomatically ill, hospitalized, and removed/recovered individuals. The networks on which we simulate disease spread incorporate heterogeneity in the risk levels of different types of interactions, time-dependent lockdown and reopening measures, and interaction distributions for four different groups (caregivers, disabled people, essential workers, and the general population). Of these groups, we find that the probability of becoming infected is largest for caregivers and second largest for disabled people. Consistent with this finding, our analysis of network structure illustrates that caregivers have the largest modal eigenvector centrality of the four groups. We find that two interventions—contact-limiting by all groups and mask-wearing by disabled people and caregivers—most reduce the number of infections in disabled and caregiver populations. We also test which group of people spreads COVID-19 most readily by seeding infections in a subset of each group and comparing the total number of infections as the disease spreads. We find that caregivers are the most potent spreaders of COVID-19, particularly to other caregivers and to disabled people. We test where to use limited infection-blocking vaccine doses most effectively and find that (1) vaccinating caregivers better protects disabled people from infection than vaccinating the general population or essential workers and that (2) vaccinating caregivers protects disabled people from infection about as effectively as vaccinating disabled people themselves. Our results highlight the potential effectiveness of mask-wearing, contact-limiting throughout society, and strategic vaccination for limiting the exposure of disabled people and their caregivers to COVID-19.
... 17 18 From our in-depth analysis of studies included in this review, it is apparent that findings are mixed: for example, there is evidence for an association between ownership of the facility (private, public or no-profit) in four out of eight studies that explored this characteristic 16 19-25 ; the number of beds in a facility or facility size were associated with COVID-19 outbreak in three of six studies, 16 19-21 23-25 bed occupancy in two of the studies which assessed it, 19 22 and the presence of disadvantaged individuals in three out of five studies were associated with a COVID-19 outbreak. 16 19 21-23 25 As such, there is no clear evidence on the relationship between characteristics of the LTCFs and the risk of a COVID-19 outbreak from the existing literature. The lack of consistency in study findings raises questions about the reliability of measures employed in each of the studies and any global differences in the effectiveness of these findings. ...
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.
... To date, many studies have focused on the structural or administrative characteristics of the longterm care home itself, identifying larger home size, 3 lower quality ratings, 4 for-profit status (vs. public), 5 and higher resident-to-staff ratios 6 as being predictors of SARS-CoV-2 infection. ...
Background
SARS-Cov-2 infection rates are high among residents of long-term care (LTC) homes. We used machine learning to identify resident and community characteristics predictive of SARS-Cov-2 infection.
Methods
We linked 26 population-based health and administrative databases to identify the population of all LTC residents tested for SARS-Cov-2 infection in Ontario, Canada. Using ensemble-based algorithms, we examined 484 factors, including individual-level demographics, healthcare use, comorbidities, functional status, and laboratory results; and community-level characteristics to identify factors predictive of infection. Analyses were performed separately for January to April (early wave 1) and May to August (late wave 1).
Findings
Among 80,784 LTC residents, 64,757 (80.2%) were tested for SARS-Cov-2 (median age 86 (78–91) years, 30.6% male), of whom 10.2% of 33,519 and 5.2% of 31,238 tested positive in early and late wave 1, respectively. In the late phase (when restriction of visitors, closure of communal spaces, and universal masking in LTC were routine), regional-level characteristics comprised 33 of the top 50 factors associated with testing positive, while laboratory values and comorbidities were also predictive. The c-index of the final model was 0.934, and sensitivity was 0.887. In the highest versus lowest risk quartiles, the odds ratio for infection was 114.3 (95% CI 38.6–557.3). LTC-related geographic variations existed in the distribution of observed infection rates and the proportion of residents at highest risk.
Interpretation
Machine learning informed evaluation of predicted and observed risks of SARS-CoV-2 infection at the resident and LTC levels, and may inform initiatives to improve care quality in this setting.
Funding
Funded by a Canadian Institutes of Health Research, COVID-19 Rapid Research Funding Opportunity grant (# VR4 172736) and a Peter Munk Cardiac Centre Innovation Grant. Dr. D. Lee is the Ted Rogers Chair in Heart Function Outcomes, University Health Network, University of Toronto. Dr. Austin is supported by a Mid-Career investigator award from the Heart and Stroke Foundation. Dr. McAlister is supported by an Alberta Health Services Chair in Cardiovascular Outcomes Research. Dr. Kaul is the CIHR Sex and Gender Science Chair and the Heart & Stroke Chair in Cardiovascular Research. Dr. Rochon holds the RTO/ERO Chair in Geriatric Medicine from the University of Toronto. Dr. B. Wang holds a CIFAR AI chair at the Vector Institute.
... Additionally, 34% of patients in the sample acquired their COVID-19 infection in a nursing home prior to hospitalization. These associations have been consistently reported in the literature [19][20][21][22]. ...
Different pharmacotherapeutics have been introduced, and then stopped or continued, for the treatment of SARS-CoV-2. We evaluated the risks associated with mortality from SARS-CoV-2 infection. METHODS: Data was concurrently or retrospectively captured on COVID-19 hospitalized patients from 6 regional hospitals within the health system. Demographic details, the source of SARS-CoV-2 infection, concomitant disease status, as well as the therapeutic agents used for treating SARS-CoV-2 (e.g., antimicrobials, dexamethasone, convalescent plasma, tocilizumab, and remdesivir) were recorded. Discrete and continuous variables were analyzed using SPSS (ver. 27). Logistic regression identified variables significantly correlated with mortality. RESULTS: 471 patients (admitted from 1 March 2020 through 15 July 2020) were reviewed. Mean (±SD) age and body weight (kg) were 62.5 ± 17.7 years and 86.3 ± 27.1 kg, respectively. Patients were Caucasian (50%), Hispanic (34%), African-American (10%), or Asian (5%). Females accounted for 52% of patients. Therapeutic modalities used for COVID-19 illness included remdesivir (16%), dexamethasone (35%), convalescent plasma (17.8%), and tocilizumab (5.8%). The majority of patients returned home (62%) or were transferred to a skilled nursing facility (23%). The overall mortality from SARS-CoV-2 was 14%. Logistic regression identified variables significantly correlated with mortality. Intubation, receipt of dexamethasone, African-American or Asian ethnicity, and being a patient from a nursing home were significantly associated with mortality (x2 = 86.36 (13) p < 0.0005). CONCLUSIONS: SARS-CoV-2 infected hospitalized patients had significant mortality risk if they were intubated, received dexamethasone, were of African-American or Asian ethnicity, or occupied a nursing home bed prior to hospital admission.
... Indeed, the analyses showed a strong positive correlation between the ranks of the outbreak probability peaks in the nursing homes of the Départements and the ranks of the hospitalization probability peaks in the same Départements (the latter being indirect measurements of incidence peaks). This correlation was already mentioned in other studies [5,6,[24][25][26]. In a study by Sun et al. [6], in 1,146 nursing homes of Massachusetts, Georgia, and New Jersey, the strongest predictors of the probability of presence of at least one COVID-19 case were the infection rate in the county and the number of care units in the nursing homes. ...
... Indeed, the analyses showed a strong positive correlation between the ranks of the outbreak probability peaks in the nursing homes of the Départements and the ranks of the hospitalization probability peaks in the same Départements (the latter being indirect measurements of incidence peaks). This correlation was already mentioned in other studies [5,6,[24][25][26]. In a study by Sun et al. [6], in 1,146 nursing homes of Massachusetts, Georgia, and New Jersey, the strongest predictors of the probability of presence of at least one COVID-19 case were the infection rate in the county and the number of care units in the nursing homes. ...
Background
Worldwide, COVID-19 outbreaks in nursing homes have often been sudden and massive. The study investigated the role SARS-CoV-2 virus spread in nearby population plays in introducing the disease in nursing homes.
Material and methods
This was carried out through modelling the occurrences of first cases in each of 943 nursing homes of Auvergne-Rhône-Alpes French Region over the first epidemic wave (March-July, 2020). The cumulative probabilities of COVID-19 outbreak in the nursing homes and those of hospitalization for the disease in the population were modelled in each of the twelve Départements of the Region over period March-July 2020. This allowed estimating the duration of the active outbreak period, the dates and heights of the peaks of outbreak probabilities in nursing homes, and the dates and heights of the peaks of hospitalization probabilities in the population. Spearman coefficient estimated the correlation between the two peak series.
Results
The cumulative proportion of nursing homes with COVID-19 outbreaks was 52% (490/943; range: 22–70% acc. Département). The active outbreak period in the nursing homes lasted 11 to 21 days (acc. Département) and ended before lockdown end. Spearman correlation between outbreak probability peaks in nursing homes and hospitalization probability peaks in the population (surrogate of the incidence peaks) was estimated at 0.71 (95% CI: [0.66; 0.78]).
Conclusion
The modelling highlighted a strong correlation between the outbreak in nursing homes and the external pressure of the disease. It indicated that avoiding disease outbreaks in nursing homes requires a tight control of virus spread in the surrounding populations.
... The pandemic of coronavirus disease 2019 (COVID- 19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a severe threat to global public health [1]. Due to the advanced age of the residents, nursing homes/assisted living facilities were the most affected places in this pandemic [2][3][4]. ...
Background:
Due to elderly residents, nursing homes/assisted living facilities were the most affected places in COVID-19 pandemic. Besides symptomatic patients, asymptomatic patients were detected during routine screening.
Aim:
This study aims to determine the factors that affect antibody response and viral shedding in stool samples after natural exposure to the virus in residents and staff who recovered from COVID-19 before the vaccine was available.
Methods:
This prospective cross-sectional study was conducted at the nation's highest-capacity Residential and Nursing Home. Blood samples were collected between December 15, 2020 and January 15, 2021 from participating residents and staff for anti-SARS-CoV-2 antibody testing. Stool samples were obtained for SARS-CoV-2 PCR testing 2 months after COVID-19. The Social Sciences (SPSS) program version 15.0 was used for statistical analysis. The Mann-Whitney U test compared SARS-CoV-2 antibody concentration between two groups.
Results:
Four hundred sixty-four (52.3%) residents and 424 (47.7%) staff participated. Entirely 259 (29.2%) participants were anti-SARS-CoV-2 IgG (+) and 255 (28.7%) were SARS-CoV-2 PCR (+). Both antibody and PCR positivity was detected in 196 (76.9%). In PCR (-) group, 63 (10.0%) participants were SARS-CoV-2 IgG (+). Antibody titers were found highest in SARS-CoV-2 PCR (+) male residents. SARS-CoV-2 IgG titers were significantly high in SARS-CoV-2 PCR (+) and hospitalized participants regardless of age. Stool samples were obtained from 61(23.9%) participants and were found negative.
Conclusion:
A durable SARS-CoV-2 IgG antibody response was monitored at least 9 months after the participants were diagnosed with COVID-19. SARS-CoV-2 antibody positivity was detected 76.9% in PCR (+) and 10.0% in PCR (-) participants. Knowing the duration of detectable antibodies is an important finding for developing disease prevention and public health strategies.
... 5 In the United States, by May 21, 2021, over 35,000 deaths have been reported in LTCF´s, representing 42% of total deaths due to COVID-19; LTCF´s with more than 50 residents are the most affected. 6 A study published in September 2020 reported that the mortality in 12 member countries of the Organization for Economic Cooperation and Development (OECD) was 47.3% in LTCF´s and 44.7% in older adults living in the community. 7 In addition to the greater risk in the elderly population, it is extremely important to consider the frailty syndrome in this population, since mortality reaches up to 33.7% in frail adults infected by Literature on COVID-19 infections at LCTF´s and their postinfection impact on the elderly measured by the comprehensive geriatric assessment (CGA) in Mexico is scarce. ...
... However, the differences appear when we analyse the results according to age and the population's area of residence, given that among the non-IOP population the increase in age is significantly associated with a greater probability of death, while this is not true in the case of the IOP; and the opposite occurs in the case of belonging to an urban area, which is significantly associated with a greater probability of death only among the IOP. This association had already been detected in previous studies [43]. The data from our study confirm this fact, which is not significant among non-IOPs. ...
Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.
The COVID-19 pandemic in the US has been particularly devastating for nursing home residents. A key question is how have some nursing homes been able to effectively protect their residents, while others have not? Using data on the universe of US nursing homes, we examine whether establishment quality is predictive of COVID-19 mortality. Higher-quality nursing homes, as measured by CMS overall five-star rating, have substantially lower COVID-19 mortality through September of 2020. Quality does not predict the ability to prevent any COVID-19 resident or staff cases, but higher-quality establishments prevent the spread of resident infections conditional on having one. Preventing COVID-19 cases and deaths may come at some cost, as high-quality homes have substantially higher non-COVID deaths. The positive correlation between establishment quality and non-COVID mortality is strong enough that high-quality homes also have more total deaths than their low-quality counterparts and this relationship has grown with time. As of late April 2021, five-star homes have experienced 8.4 percent more total deaths than one-star homes.
The impact of specific risk factors for SARS-CoV-2 infection spread was investigated among the 215 municipalities in north-eastern Italy. SARS-CoV-2 incidence was gathered fortnightly since April 1, 2020 (21 consecutive periods) to depict three indicators of virus spreading from hierarchical Bayesian maps. Eight explanatory features of the municipalities were obtained from official databases (urbanicity, population density, active population on total, hosting schools or nursing homes, proportion of commuting workers or students, and percent of > 75 years population on total). Multivariate Odds Ratios (ORs), and corresponding 95% Confidence Intervals (CIs), quantified the associations between municipality features and virus spreading. The municipalities hosting nursing homes showed an excess of positive tested cases (OR = 2.61, ever versus never, 95% CI 1.37;4.98), and displayed repeated significant excesses: OR = 5.43, 3–4 times versus 0 (95% CI 1.98;14.87) and OR = 6.10, > 5 times versus 0 (95% CI 1.60;23.30). Municipalities with an active population > 50% were linked to a unique statistical excess of cases (OR = 3.06, 1 time versus 0, 95% CI 1.43;6.57) and were inversely related to repeated statistically significant excesses (OR = 0.25, > 5 times versus 0; 95% CI 0.06;0.98). We highlighted specific municipality features that give clues about SARS-CoV-2 prevention.
Rampant COVID-19 outbreaks in US nursing homes have presented a massive biosecurity problem for the nation, bringing into stark relief the racialized stratification of eldercare administration and long-term care. This paper, by foregrounding the ways racial capitalism drives the chronic devaluation of nursing home residents and staff, provides an overview of how racism and ageism operate geographically through political ecologies of COVID in relation to the organization of the nursing home industry, medical scarcity, long-term care labor, and pandemic response to elderly populations. The inventory tracks some of the ways nursing homes condition race-based futures by arranging eldercare populations, workers, and spaces for extraction, abandonment, and blame for the pandemic. In doing so, it demonstrates the need for more equitable forms of aging and more just institutions of eldercare that put the social welfare of the aged, especially that of BIPOC elders and caregivers, above corporate compliance and financial performance that reproduce racial hierarchy and white supremacy in US healthcare. The article concludes by engaging with Black feminist data analytics and several policy efforts that challenge the structurally racist conditions of caregiving, pandemic response, and securitized segregation of the aged.
This article provides an updated picture of the enormous consequences that the first wave of the COVID-19 pandemic (March–June 2020) had for older adults living in Spanish care homes. It aims to describe the regional variation in deaths among home care residents through a methodological triangulation of descriptive quantitative, ecological and documentary analysis. Figures of five different indicators of care home mortality are provided and some factors related to higher mortality rates are presented and analysed in the descriptive ecological analysis in order to depict trends and, in a linear regression, to determine their statistical significance. The clearest trend reflected by the data is that the higher the cumulative incidence and the number of care home beds in the surrounding area, the higher the COVID-19 care home mortality. We argue that the pandemic has brought to light the historical fragility and underdevelopment of the Spanish LTC sector, and that these factors have exacerbated the consequences of the pandemic. Finally, we conclude that publicly available and disaggregated data would allow a deeper and more accurate analysis of potentially explanatory factors such as the type of care home ownership and management, and that further qualitative research would shed more light on people’s experiences.
The past year amplified inequities in the care of older adults. Milestones focused on social determinants of health (SDOH) are lacking within Geriatric fellowship training. A virtual learning collaborative GERIAtrics Fellows Learning Online And Together (GERI-A-FLOAT) was developed to connect trainees nationwide. To address gaps in education around SDOH, a needs assessment was conducted to inform a curricular thread. A voluntary, anonymous survey was distributed to fellows through a broad network. We sought to understand prior curricula trainees had that were specifically focused on SDOH and older adults. Respondents prioritized topic areas for the curriculum. Seventy-five respondents completed the survey. More than 50% of participants indicated no training on homelessness, immigration, racism, or LGBTQ+ health at any level of medical training, with more than 70% having no training in sexism or care of formerly incarcerated older adults. The most commonly taught concepts were ableism, ageism, and poverty. Respondents prioritized the topic of racism, ageism, and ableism. There is a lack of consistent SDOH curricula pertaining to older adults across all levels of training. This needs assessment is guiding a curricular thread for GERI-A-FLOAT and ideally larger milestones for fellowships. The time is now to prepare future geriatricians to serve as change agents.
Introduction:
Nursing homes for older adults have been hot spots for SARS-CoV-2 infections and mortality. Factors that facilitate COVID-19 outbreaks in these settings need to be assessed.
Methods:
A retrospective cross-sectional study of a cohort of residents and workers in nursing homes taking occasion of a point seroprevalence survey was done in the Community of Madrid. Factors related to outbreaks in these facilities were analyzed.
Results:
A total of 369 nursing homes for older adults, making a population of 23,756 residents and 20,795 staff members, were followed from July to December 2020. There were 54.2% SARS-CoV-2 IgG+ results in residents and in 32.2% of workers. Sixty-two nursing homes (16.8%) had an outbreak during the follow-up. Nursing homes with outbreaks had more residents than those without (median number of 81 [IQR, 74] vs. 50 [IQR, 56], p < 0.001). Seropositivity for SARS-CoV-2 was lower in facilities with versus without outbreaks, for residents (42.2% [IQR, 55.7] vs. 58.7% [IQR, 43.4], p = 0.002) and for workers (23.9% [IQR, 26.4] vs. 32.8% [IQR, 26.3], p = 0.01). For both residents and staff, the number of infections in outbreaks was larger in centers with lower, as compared with intermediate or high seroprevalence. The size of the facility did not correlate with the number of cases in the outbreak. Taking the incidence of cases in the community as a time-dependent variable (p = 0.03), a Cox analysis (HR [95% CI], p) showed that intermediate or high seroprevalence among residents in the facility was related to a reduction of 55% (0.45 [0.25-0.80], p = 0.007) and 78% (0.22 [0.10-0.48], p < 0.001) in the risk of outbreaks, respectively, as compared with low sero-prevalence. Also, as compared with smaller, medium (1.91 [1.00-3.65], p = 0.05) or large centers (4.57 [2.38-8.75], p < 0.001) had more respective risk of outbreaks.
Conclusions:
The size of the facility and the seroprevalence among residents in nursing homes, and the incidence of infections in the community, are associated with the risk of outbreaks of COVID-19. Facilities with greater proportion of seropositives had smaller number of cases. Monitoring of immunity in nursing homes may help detect those at a greater risk of future cases.
Although many long-term care (LTC) facilities have implemented measures to isolate infectious residents from the general population, most are not designed for airborne infection control, and guidance for retrofitting existing LTC spaces for airborne isolation is limited. The purpose of this study was to evaluate the effect of ventilation, negative pressure, airflow barriers, and other retrofit measures on bioaerosol concentration and movement within long-term care LTC environments. To that end, a series of bioaerosol measurements was performed in an LTC facility under various pressurization and airflow configurations. We arranged active air sampling of DNA-tagged solutions release in the LTC environment, followed by quantitative polymerase chain reaction (qPCR) techniques to measure the released DNA in various spatial locations. Results from aerosol testing in an actual LTC facility suggest that increasing both total and outside ventilation rate had a modest and disproportional effect on the containment of bioaerosols, yet it significantly reduced the time necessary to remove 99% of aerosols from 3 h to approximately 40 min. Significant reductions in aerosol mobility between resident rooms, corridors, and common spaces were also observed with respect to negative room pressurization and anterooms.
As the late Robert Kane observed, the term nursing home is often a misnomer. Most U.S. nursing homes lack adequate nursing staff, and they are typically not very homelike in either their physical structure or culture. These problems were magnified during the pandemic. The underlying reasons for these longstanding issues are that most state Medicaid payment systems reimburse nursing homes at a relatively low level and the government does not hold nursing homes accountable for spending dollars on direct resident care. To encourage increased staffing and more homelike models of care, policymakers need to reform how nursing homes are paid and hold facilities accountable for how they spend government dollars. With these reforms, the term nursing home will become more appropriate in the United States.
Background and objectives
COVID-19 disproportionally affects older adults living in nursing homes. The purpose of this review was to explore and map the scientific literature on the health impact of COVID-19 and related restrictive measures during the first and second wave among nursing home residents. A specific focus was placed on health data collected among nursing home residents themselves.
Research design and methods
In this study, best practices for scoping reviews were followed. Five databases were systematically searched for peer-reviewed empirical studies published up until December 2020 in which data were collected among nursing home residents. Articles were categorized according to the type of health impact (physical, social and/or psychological) and study focus (impact of COVID-19 virus or related restrictive measures). Findings were presented using a narrative style.
Results
Of 60 included studies, 57 examined the physical impact of COVID-19. All of these focused on the direct impact of the COVID-19 virus. These studies often used an observational design and quantitative data collection methods, such as swab testing or reviewing health records. Only three studies examined the psychological impact of COVID-19 of which one study focused on the impact of COVID-19-related restrictive measures. Findings were contradictory; both decreased and improved psychological wellbeing was found during the pandemic compared with before. No studies were found that examined the impact on social wellbeing and one study examined other health-related outcomes, including preference changes of nursing home residents in Advanced Care planning following the pandemic.
Discussion and implications
Studies into the impact of the first and second wave of the COVID-19 pandemic among nursing home residents predominantly focused on the physical impact. Future studies into the psychological and social impact that collect data among residents themselves will provide more insight into their perspectives, such as lived experiences, wishes, needs and possibilities during later phases of the pandemic. These insights can inform policy makers and healthcare professionals in providing person-centered care during the remaining COVID-19 pandemic and in future crisis periods.
The number of Americans aged 65 years or older is expected to increase in the coming decades. Because the risk for disability increases with age, more persons will need long-term services and supports (LTSS) to help with bathing, eating, dressing, and other everyday tasks. Long-term services and supports are delivered in nursing homes, assisted living facilities, the person's home, and other settings. However, the LTSS sector faces several challenges, including keeping patients and staff safe during the COVID-19 pandemic, workforce shortages, quality problems, and fragmented coverage options. In this position paper, the American College of Physicians offers policy recommendations on LTSS coverage, financing, workforce, safety and quality, and emergency preparedness and calls on policymakers and other stakeholders to reform and improve the LTSS sector so that care is high quality, accessible, equitable, and affordable.
Older adults in nursing homes are at greatest risk of morbidity and mortality from SARS-CoV-2 infection. Nursing home residents constituted one-third to over half of all deaths during the early waves of the COVID-19 pandemic. Following this, widespread adaptation of Infection Prevention and Control measures and the supply and use of Personal Protective Equipment resulted in a significant decrease in nursing home infections and deaths. For nursing homes, the most important determinant of experiencing a SARS-CoV-2 outbreak in the first instance appears to be community-transmission levels (particularly with Variants-of-Concern), although nursing home size/quality, “for profit” status, and sociodemographic characteristics are also important. Use of visitation bans, imposed to reduce the impact of COVID-19 on residents must be delicately balanced against their impact on resident, friend/family and staff wellbeing. The successful rollout of primary vaccination has resulted in a sharp decrease in morbidity and mortality from SARS-CoV-2 in nursing homes. However, emerging evidence suggests that vaccine efficacy may wane over time, and the use of a third or additional vaccine “booster” doses in nursing home residents restores protection afforded by primary vaccination. Ongoing monitoring of vaccine efficacy in terms of infection, morbidity and mortality is crucial in this vulnerable group in informing ongoing SARS-CoV-2 vaccine boosting strategies. Here, we detail the impact of SARS-CoV-2 on nursing home residents and discuss important considerations in the management of nursing home SARS-CoV-2 outbreaks. We additionally examine the use of testing strategies, non-pharmacological outbreak control measures and vaccination strategies in this cohort. Finally, the impact of SARS-CoV-2 on the sector is reflected on as we emphasise the need for adoption of universal standards of medical care and integration with wider public health infrastructure in nursing homes in order to provide a safe and effective long-term care sector.
Background
Residents of Nursing Homes (NHs) have suffered greater impacts from the COVID-19 pandemic. However, the rates of COVID-19 in these institutions are heterogeneously distributed. Describing and understanding the structural, functional, and socioeconomic differences between NHs is extremely important to avoid new outbreaks.
Objectives
Analyze inequalities in the cumulative incidences (CIs) and in the mortality rates (MRs) due to COVID-19 in the NHs of Barcelona based on the characteristics of the NHs.
Methods
Exploratory ecological study of 232 NHs. The dependent variables were the cumulative incidence and mortality rate due to COVID-19 in NHs between March and June 2020. Structural variables of the NHs were evaluated such as neighborhood socioeconomic position (SEP), isolation and sectorization capacity, occupancy, overcrowding and ownership.
Results
The cumulative incidence and mortality rate were higher in the low SEP neighborhoods and lower in those of high SEP neighborhoods. Regarding the isolation and sectorization capacity, Type B NHs had a higher risk of becoming infected and dying, while Type C had a lower risk of dying than Type A. Greater overcrowding was associated with greater morbidity and mortality, and higher occupancy was associated with higher incidence. The risk of becoming infected and dying in public NHs was significantly higher than for-profit NH.
Conclusions
The social components together with the functional and infrastructure characteristics of the NHs influence the cumulative incidence and the mortality rate by COVID-19. It is necessary to redefine the care model in the NHs to guarantee the health of the residents.
Medicaid Home- and Community-Based Services (HCBS) 1915(c) waivers are the largest funding mechanism for Long-Term Supports and Services (LTSS) for people with intellectual and developmental disabilities (IDD) in the United States. This study’s aim was to examine telehealth service provision in Medicaid HCBS waivers for people with IDD. We analyzed fiscal year 2021 Medicaid HCBS waivers for people with IDD and emergency Appendix K authorizations (2020-2022) to examine permanent and temporary use of telehealth, respectively. The overwhelming majority of waivers (98.1%) temporarily permitted the use of telehealth service delivery for people with IDD. However, only a fraction (27.6%) permanently included the use of telehealth for people with IDD. The most prevalent types of services that permitted telehealth service delivery were: employment, day, and prevocational services; clinical and therapeutic services; and in-home and residential supports. When developing and implementing telehealth, it is important to consider the needs of people with IDD.
The number of Older Adults (OA) in Ontario will double in two decades. The COVID-19 pandemic demonstrated that the model of subsidized Long-Term Care (LTC) homes does not reflect the care needs of OAs. Many nations have implemented LTC models as a continuum of care for OAs promoting independent home/community living. These models help delay admission to LTC homes and achieve a higher quality-of-life for OAs. Current financial pressure on the healthcare system and inadequacies of LTC homes necessitate a broader social welfare policy. One viable option for sustainable LTC is implementing Ontario’s mandatory public long-term care insurance policy.
Objectives
The novel coronavirus disease 2019 (COVID-19) deeply affected all forms of long-term care for older adults, highlighting infection control issues, provider and staff shortages, and other challenges. As a comparatively new, community-based long-term care option, the Program of All-Inclusive Care for the Elderly (PACE) faced unique challenges. This project investigated the impact of COVID-19 on operations in all PACE programs in one U.S. state.
Design
Qualitative study.
Setting and Participants
Structured interviews with administrators of all 12 PACE programs in North Carolina.
Methods
Interviews were conducted December 2020-January 2021 by trained interviewers over Zoom; they were transcribed, coded, and qualitatively analyzed using thematic analysis.
Results
Reported COVID-19 infection rates among PACE participants for 2020 averaged 12.3 cases, 4.6 hospitalizations, and 1.9 deaths per 100 enrollees. Six themes emerged from analyses: new, unprecedented administrative challenges; insufficient access to and integration with other health care providers; reevaluation of the core PACE model, resulting in a transition to home-based care; re-orientation to be more family-focused in care provision; implementation of new, creative strategies to address participant and family psychological and social well-being in the home; and major reconfiguration of staffing, including transitions to new and different roles and a concomitant effort to provide support and relief to staff.
Conclusions and Implications
While facing many challenges that required major changes in care provision, PACE was successful in mounting a COVID-19 response that upheld safety, promoted the physical and mental well-being of participants, and responded to the needs of family caregivers. Administrators felt that, after the pandemic, PACE’s service model is likely to remain more home-based and less reliant on the day center than in the past. As a result, PACE may have changed for the better and be well-positioned to play an expanded role in our evolving long-term care system.
Resumen Objetivo: evaluar la adhesión de instituciones brasileñas de larga estancia a las orientaciones de Prevención y Control de Infecciones de la Organización Mundial de la Salud y evaluar la asociación entre su tamaño y la adhesión a esas recomendaciones. Método: estudio transversal realizado con gerentes de establecimientos. Los autores desarrollaron un cuestionario de 20 ítems basado en estas directrices y un puntaje general de cumplimiento acorde a la observancia de estas recomendaciones. La adhesión se calificó (1) excelente para aquellas que cumplieron con ≥14 de 20 recomendaciones; (2) buena para 10 a 13 artículos; y (3) baja para aquellas con menos de diez elementos. El tamaño de las instalaciones se clasificó como pequeños, medianos y grandes de acuerdo con un análisis de clúster de dos pasos. Se utilizó estadística descriptiva y la prueba de chi-cuadrado con un nivel de significancia del 5%. Resultados: de las 362 instituciones incluidas, 308 (85,1%) se adhirieron a 14 o más recomendaciones. En cuanto a su tamaño, la adhesión al cribado de síntomas de COVID-19 de los visitantes (p=0,037) y al aislamiento de los pacientes hasta que tengan dos pruebas de laboratorio negativas (p=0,032) fue menor en los establecimientos más grandes en comparación con los establecimientos medianos y pequeños. Conclusión: la adhesión a las medidas de mitigación de la COVID-19 en las unidades brasileñas fue considerada excelente para la mayoría de las recomendaciones, independientemente del tamaño de las unidades.
Objective: to evaluate the adherence of Brazilian long-term care facilities to the World Health Organization Infection Prevention and Control guidance, and assess the association of their size with the adherence to these recommendations. Method: cross-sectional study conducted with facilities’ managers. Authors developed a 20-item questionnaire based on this guidance, and a global score of adherence, based on the adoption of these recommendations. Adherence was classified as (1) excellent for those who attended ≥14 out of 20 recommendations; (2) good for 10 to 13 items; and (3) low for those with less than ten items. Facilities’ sizes were established as small, intermediate, and large according to a two-step cluster analysis. Descriptive statistics and chi-square tests were used at a 5% significance level. Results: among 362 included facilities, 308 (85.1%) adhered to 14 or more recommendations. Regarding its size, adherence to screening COVID-19 symptoms of visitors (p=0.037) and isolating patients until they have had two negative laboratory tests (p=0.032) were lower on larger ones compared to medium and small facilities. Conclusion: adherence to COVID-19 mitigation measures in Brazilian facilities was considered excellent for most of the recommendations, regardless of the size of the units.
Objectives:
The first wave of the COVID-19 pandemic necessitated extensive infection control measures in long-term care (LTC) and had a significant impact on staffing and services. Anecdotal reports indicate that this negatively affected LTC residents' quality of care and wellbeing, but there is scarce evidence on the effects of COVID-19 on quality of dementia care in LTC.
Methods:
From December 2020 to March 2021, we conducted a cross-sectional online survey among staff who worked in LTC homes in Ontario, Canada. Survey questions examined staffs' perceptions of the impact of COVID-19 on dementia quality of care during the initial wave of the COVID-19 pandemic (beginning 1 March 2020).
Results:
There were a total of 227 survey respondents; more than half reported both worsened overall quality of care (51.3%) and worsening of a majority of specific quality of care measures (55.5%). Measures of cognitive functioning, mobility and behavioural symptoms were most frequently described as worsened. Medical and allied/support staff had the highest odds of reporting overall worsened quality of care, while specialized behavioural care staff and those with more experience in LTC were less likely to. LTC home factors including rural location and smaller size, staffing challenges, higher number of outbreaks and less COVID-19 preparedness were associated with increased odds of perceived worsening of quality of dementia care outcomes.
Conclusions:
These findings suggest that COVID-19 pandemic restrictions and related effects such as inadequate staffing may have contributed to poor quality of care and outcomes for those with dementia in LTC.
The coronavirus disease 2019 (COVID-19) pandemic brought to the fore deficiencies in the long-term residential care (LTRC) sector, including issues of governance, funding and staffing. Many of these issues pre-dated the pandemic and have contributed to concerns around the sustainability of the current model of LTRC in Ireland. The aim of the project detailed in this protocol is to provide an evidence base to help ensure the sustainability of the LTRC sector in Ireland within a new wider model of care for older people. The project includes three key objectives: (i) to describe and analyse the characteristics of LTRC homes across Ireland; (ii) to examine the association between LTRC home characteristics and COVID-19 outbreaks and deaths and (iii) to identify challenges to the sustainability of the LTRC sector within a COVID-19 environment and beyond. Bringing together the findings from these three objectives, the project will identify approaches and strategies which will help ensure the sustainability of LTRC that meets the needs of residents. The proposed research incorporates quantitative analyses and a review. Combining data from a variety of administration sources and using a variety of statistical techniques, the project will include a retrospective observational analysis of COVID-19 in LTRC homes in Ireland. Subsequently, a review will examine the current funding model of LTRC in Ireland, as well as the regulations and governance structure that underlie the system. The review will also examine international practices in these areas. Bringing together the findings from the quantitative analysis and the review and working with the knowledge users on the project, the project will build upon recent work in the area to identify the current challenges to the system of LTRC and possible solutions.
Purpose of review:
Despite advances in infection prevention and control and breakthroughs in vaccination development, challenges remain for long-term care facilities (LTCFs) as they face a likely future of emerging infectious diseases. To ensure the safety of LTCF residents from the current and future pandemics, we identify lessons learned from the coronavirus disease 2019 (COVID-19) experience for improving future prevention and response efforts.
Recent findings:
In addition to high disease susceptibility among LTCF residents, LTCF vulnerabilities include a lack of pandemic preparedness, a lack of surge capacity in human, material and testing resources, and poorly designed buildings. External sources of vulnerability include staff working in multiple LTCFs and high COVID-19 rates in surrounding communities. Other challenges include poor cooperation between LTCFs and the other components of health systems, inadequately enforced regulations, and the sometimes contradictory interests for-profit LTCFs face between protecting their residents and turning a profit.
Summary:
These challenges can be addressed in the post-COVID-19 period through systemic reforms. Governments should establish comprehensive health networks that normalize mechanisms for prediction/preparedness and response/recovery from disruptive events including pandemics. In addition, governments should facilitate cooperation among public and private sector health systems and institutions while utilizing advanced digital communication technologies. These steps will greatly reduce the threat to LTCFs posed by emerging infectious diseases in future.
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.
Coronavirus disease 2019 (COVID-19) has led to a surge of patients requiring post-acute care. In order to support federal, state and corporate planning, we offer a four-stage regionally oriented approach to achieving optimal systemwide resource allocation across a region's post-acute service settings and providers over time. In the first stage, the post-acute care system must, to the extent possible, help relieve acute hospitals of non-COVID-19 patients to create as much inpatient capacity as possible over the surge period. In the second stage after the initial surge as subsided, post-acute providers must protect vulnerable populations from COVID-19, prepare treat-in-place protocols for non-COVID-19 admissions, and create and formalize COVID-19 specific settings. In the third stage after a vaccine has been developed or an effective prophylactic option is available, post-acute care providers must assist with distribution and administration of vaccinations and prophylaxis, develop strategies to deliver non-COVID-19 related medical care, and begin to transition to the post-COVID-19 landscape. In the final stage, we must create health advisory bodies to review post-acute sector's response, identify opportunities to improve performance going forward, and develop a pandemic response plan for post-acute care providers.
More than 2,200 coronavirus deaths in nursing homes, but federal government isn't tracking them
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State reporting of cases and deaths due to COVID-19 in long-term care facilities. Kaiser Family Foundation
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Nearly 1 in 10 nursing homes nationwide report coronavirus cases
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More than 2 200 coronavirus deaths in nursing homes but federal government isn’t tracking them.NBC News
- Khimms Stricklerl
- Blanksteina Georgievp
Nearly 1 in 10 nursing homes nationwide report coronavirus cases
- Cenziperd Jacobsj Mulcahys