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

Predicting COVID-19 Cases in Nursing Homes of California and Ohio: Does the Work Environment Matter?

OBJECTIVE

The cross-sectional study evaluates if the prepandemic work environments in nursing homes predict coronavirus disease 2019 (COVID-19) cases among residents and staff, accounting for other factors.

METHOD

Leveraging data from a survey of California and Ohio nursing homes (n = 340), we examined if Workplace Integrated Safety and Health domains - Leadership, Participation, and Comprehensive and Collaborative Strategies predicted cumulative COVID-19 cases among nursing home residents and staff.

RESULTS

In Ohio, a 1-unit increase in Leadership score was associated with 2 fewer staff cases and 4 fewer resident cases. A 1-unit increase in Comprehensive and Collaborative Strategies score in California showed an average marginal effect of approximately 1 less staff case and 2 fewer resident cases.

CONCLUSIONS

These findings suggest that leadership commitment and interdepartment collaboration to prioritize worker safety may have protected against COVID-19 cases in nursing homes.

Variation in Excess Mortality Across Nursing Homes in the Netherlands During the COVID-19 Pandemic

OBJECTIVES

Nursing home residents constituted a vulnerable population during the COVID-19 pandemic, and half of all cause-attributed COVID-19 deaths occurred within nursing homes. Yet, given the low life expectancy of nursing home residents, it is unclear to what extent COVID-19 mortality increased overall mortality within this population. Moreover, there might have been differences between nursing homes in their ability to protect residents against excess mortality. This article estimates the number of excess deaths among Dutch nursing home residents during the pandemic, the variation in excess deaths across nursing homes, and its relationship with nursing home characteristics.

DESIGN

Retrospective, use of administrative register data.

SETTING AND PARTICIPANTS

All residents (N = 194,432) of Dutch nursing homes (n = 1463) in 2016-2021.

METHODS

We estimated the difference between actual and predicted mortality, pooled at the nursing home level, which provided an estimate of nursing home-specific excess mortality corrected for resident case-mix differences. We show the variation in excess mortality across nursing homes and relate this to nursing home characteristics.

RESULTS

In 2020 and 2021, the mortality probability among nursing home residents was 4.0 and 1.6 per 100 residents higher than expected. There was considerable variation in excess deaths across nursing homes, even after correcting for differences in resident case mix and regional factors. This variation was substantially larger than prepandemic mortality and was in 2020 related to prepandemic spending on external personnel and satisfaction with the building, and in 2021 to prepandemic staff absenteeism.

CONCLUSIONS AND IMPLICATIONS

The variation in excess mortality across nursing homes was considerable during the COVID-19 pandemic, and larger compared with prepandemic years. The association of excess mortality with the quality of the building and spending on external personnel indicates the importance of considering differences across nursing home providers when designing policies and guidelines related to pandemic preparedness.

Clinical Outcomes After Admission of Patients With COVID-19 to Skilled Nursing Facilities

Importance

During the COVID-19 pandemic, stabilized COVID-19-positive patients were discharged to skilled nursing facilities (SNFs) to alleviate hospital crowding. These discharges generated controversy due to fears of seeding outbreaks, but there is little empirical evidence to inform policy.

Objective

To assess the association between the admission to SNFs of COVID-19-positive patients and subsequent COVID-19 cases and death rates among residents.

Design, Setting, and Participants

This cohort study analyzed survey data from the National Healthcare Safety Network of the Centers for Disease Control and Prevention. The cohort included SNFs in the US from June 2020 to March 2021. Exposed facilities (ie, with initial admission of COVID-19-positive patients) were matched to control facilities (ie, without initial admission of COVID-19-positive patients) in the same county and with similar preadmission case counts. Data were analyzed from June 2023 to February 2024.

Exposure

The week of the first observable admission of COVID-19-positive patients (defined as those previously diagnosed with COVID-19 and continued to require transmission-based precautions) during the study period.

Main Outcomes and Measures

Weekly counts of new cases of COVID-19, COVID-19-related deaths, and all-cause deaths per 100 residents in the week prior to the initial admission. A stacked difference-in-differences approach was used to compare outcomes for 10 weeks before and 15 weeks after the first admission. Additional analyses examined whether outcomes differed in facilities with staff or personal protective equipment (PPE) shortages.

Results

A matched group of 264 exposed facilities and 518 control facilities was identified. Over the 15-week follow-up period, exposed SNFs had a cumulative increase of 6.94 (95% CI, 2.91-10.98) additional COVID-19 cases per 100 residents compared with control SNFs, a 31.3% increase compared with the sample mean (SD) of 22.2 (26.4). Exposed facilities experienced 2.31 (95% CI, 1.39-3.24) additional cumulative COVID-19-related deaths per 100 residents compared with control facilities, representing a 72.4% increase compared with the sample mean (SD) of 3.19 (5.5). Exposed facilities experiencing potential staff shortage and PPE shortage had larger increases in COVID-19 cases per 100 residents (additional 10.97 [95% CI, 2.76-19.19] cases and additional 14.81 [95% CI, 2.38-27.25] cases, respectively) compared with those without such shortages.

Conclusion

This cohort study suggests that admission of COVID-19-positive patients into SNFs early in the pandemic was associated with preventable COVID-19 cases and mortality among residents, particularly in facilities with potential staff and PPE shortages. The findings speak to the importance of equipping SNFs to adhere to infection-control best practices as they continue to face COVID-19 strains and other respiratory diseases.

The association of nursing home infection preventionists' training and credentialing with resident COVID 19 deaths

BACKGROUND

Nursing home (NH) residents' vulnerability to COVID-19 underscores the importance of infection preventionists (IPs) within NHs. Our study aimed to determine whether training and credentialing of NH IPs were associated with resident COVID-19 deaths.

METHODS

This retrospective observational study utilized data from the Centers for Disease Control and Prevention's National Healthcare Safety Network NH COVID-19 Module and USAFacts, from May 2020 to February 2021, linked to a 2018 national NH survey. We categorized IP personnel training and credentialing into four groups: (1) LPN without training; (2) RN/advanced clinician without training; (3) LPN with training; and (4) RN/advanced clinician with training. Multivariable linear regression models of facility-level weekly deaths per 1000 residents as a function of facility characteristics, and county-level COVID-19 burden (i.e., weekly cases or deaths per 10,000 population) were estimated.

RESULTS

Our study included 857 NHs (weighted n = 14,840) across 489 counties and 50 states. Most NHs had over 100 beds, were for profit, part of chain organizations, and located in urban areas. Approximately 53% of NH IPs had infection control training and 82% were RNs/advanced clinicians. Compared with NHs employing IPs who were LPNs without training, NHs employing IPs who were RNs/advanced clinicians without training had lower weekly COVID-19 death rates (-1.04 deaths per 1000 residents; 95% CI -1.90, -0.18), and NHs employing IPs who were LPNs with training had lower COVID-19 death rates (-1.09 deaths per 1000 residents; 95% CI -2.07, -0.11) in adjusted models.

CONCLUSIONS

NHs with LPN IPs without training in infection control had higher death rates than NHs with LPN IPs with training in infection control, or NHs with RN/advanced clinicians in the IP role, regardless of IP training. IP training of RN/advanced clinician IPs was not associated with death rates. These findings suggest that efforts to standardize and improve IP training may be warranted.

Evaluating methods for risk prediction of Covid-19 mortality in nursing home residents before and after vaccine availability: a retrospective cohort study

BACKGROUND

SARS-CoV-2 vaccines are effective in reducing hospitalization, COVID-19 symptoms, and COVID-19 mortality for nursing home (NH) residents. We sought to compare the accuracy of various machine learning models, examine changes to model performance, and identify resident characteristics that have the strongest associations with 30-day COVID-19 mortality, before and after vaccine availability.

METHODS

We conducted a population-based retrospective cohort study analyzing data from all NH facilities across Ontario, Canada. We included all residents diagnosed with SARS-CoV-2 and living in NHs between March 2020 and July 2021. We employed five machine learning algorithms to predict COVID-19 mortality, including logistic regression, LASSO regression, classification and regression trees (CART), random forests, and gradient boosted trees. The discriminative performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC) for each model using 10-fold cross-validation. Model calibration was determined through evaluation of calibration slopes. Variable importance was calculated by repeatedly and randomly permutating the values of each predictor in the dataset and re-evaluating the model's performance.

RESULTS

A total of 14,977 NH residents and 20 resident characteristics were included in the model. The cross-validated AUCs were similar across algorithms and ranged from 0.64 to 0.67. Gradient boosted trees and logistic regression had an AUC of 0.67 pre- and post-vaccine availability. CART had the lowest discrimination ability with an AUC of 0.64 pre-vaccine availability, and 0.65 post-vaccine availability. The most influential resident characteristics, irrespective of vaccine availability, included advanced age (≥ 75 years), health instability, functional and cognitive status, sex (male), and polypharmacy.

CONCLUSIONS

The predictive accuracy and discrimination exhibited by all five examined machine learning algorithms were similar. Both logistic regression and gradient boosted trees exhibit comparable performance and display slight superiority over other machine learning algorithms. We observed consistent model performance both before and after vaccine availability. The influence of resident characteristics on COVID-19 mortality remained consistent across time periods, suggesting that changes to pre-vaccination screening practices for high-risk individuals are effective in the post-vaccination era.

Perspectives of nursing home administrators across the United States during the COVID-19 pandemic

OBJECTIVE

To characterize the experiences of nursing home administrators as they manage facilities across the United States during the COVID-19 pandemic.

DATA SOURCES AND STUDY SETTING

We conducted 156 interviews, consisting of four repeated interviews with administrators from 40 nursing homes in eight health care markets across the country from July 2020 through December 2021.

STUDY DESIGN

We subjected the interview transcripts to a rigorous qualitative analysis to identify overarching themes using a modified grounded theory approach to applied thematic analysis.

DATA COLLECTION METHODS

In-depth, semi-structured qualitative interviews were conducted virtually or by phone, and audio-recorded, with participants' consent. Audio recordings were transcribed.

PRINCIPAL FINDINGS

Interviews with nursing home administrators revealed a number of important cross-cutting themes. In interviewing each facility's administrator four times over the course of the pandemic, we heard perspectives regarding the stages of the pandemic, and how they varied by the facility and changed over time. We also heard how policies implemented by federal, state, and local governments to respond to COVID-19 were frequently changing, confusing, and conflicting. Administrators described the effect of COVID-19 and efforts to mitigate it on residents, including how restrictions on activities, communal dining, and visitation resulted in cognitive decline, depression, and weight loss. Administrators also discussed the impact of COVID-19 on staff and staffing levels, reporting widespread challenges in keeping facilities staffed as well as strategies used to hire and retain staff. Administrators described concerns for the sustainability of the nursing home industry resulting from the substantial costs and pressures associated with responding to COVID-19, the reductions in revenue, and the negative impact of how nursing homes appeared in the media.

CONCLUSIONS

Findings from our research reflect nursing home administrator perspectives regarding challenges operating during COVID-19 and have substantial implications for policy and practice.

COVID-19 pandemic in long-term care: An international perspective for policy considerations

This paper identifies key factors rooted in the systemic failings of the long-term care sector amongst four high income countries during the COVID-19 pandemic. The goal is to offer practice and policy solutions to prevent future tragedies. Based on data from Australia, Canada, Spain and the United States, the findings support evidence-based recommendations at macro, meso and micro levels of practice and policy intervention. Key macro recommendations include improving funding, transparency, accountability and health system integration; and promoting not-for-profit and government-run long-term care facilities. The meso recommendation involves moving from warehouses to “green houses.” The micro recommendations emphasize mandating recommended staffing levels and skill mix; providing infection prevention and control training; establishing well-being and mental health supports for residents and staff; building evidence-based practice cultures; ensuring ongoing education for staff and nursing students; and fully integrating care partners, such as families or friends, into the healthcare team. Enacting these recommendations will improve residents' safety and quality of life; families’ peace of mind; and staff retention and work satisfaction.

Characteristics of telemedicine workflows in nursing homes during the COVID-19 pandemic

Background

The use of telemedicine increased dramatically in nursing homes (NHs) during the COVID-19 pandemic. However, little is known about the actual process of conducting a telemedicine encounter in NHs. The objective of this study was to identify and document the work processes associated with different types of telemedicine encounters conducted in NHs during the COVID-19 pandemic.

Methods

A mixed methods convergent study was utilized. The study was conducted in a convenience sample of two NHs that had newly adopted telemedicine during the COVID-19 pandemic. Participants included NH staff and providers involved in telemedicine encounters conducted in the study NHs. The study involved semi-structured interviews and direct observation of telemedicine encounters and post-encounter interviews with staff and providers involved in telemedicine encounters observed by research staff. The semi-structured interviews were structured using the Systems Engineering Initiative for Patient Safety (SEIPS) model to collect information about telemedicine workflows. A structured checklist was utilized to document steps performed during direct observations of telemedicine encounters. Information from interviews and observations informed the creation of a process map of the NH telemedicine encounter.

Results

A total of 17 individuals participated in semi-structured interviews. Fifteen unique telemedicine encounters were observed. A total of 18 post-encounter interviews with 7 unique providers (15 interviews in total) and three NH staff were performed. A 9-step process map of the telemedicine encounter, along with two microprocess maps related to encounter preparation and activities within the telemedicine encounter, were created. Six main processes were identified: encounter planning, family or healthcare authority notification, pre-encounter preparation, pre-encounter huddle, conducting the encounter, and post-encounter follow-up.

Conclusion

The COVID-19 pandemic changed the delivery of care in NHs and increased reliance on telemedicine services in these facilities. Workflow mapping using the SEIPS model revealed that the NH telemedicine encounter is a complex multi-step process and identified weaknesses related to scheduling, electronic health record interoperability, pre-encounter planning, and post-encounter information exchange, which represent opportunities to improve and enhance the telemedicine encounter process in NHs. Given public acceptance of telemedicine as a care delivery model, expanding the use of telemedicine beyond the COVID-19 pandemic, especially for certain NH telemedicine encounters, could improve quality of care.

Lessons From the Field: Rapid Antigen Testing Is Efficient and Practical for Mitigation of Coronavirus Disease 2019 Outbreaks in Long-Term Care Facilities

Background

Mitigation of coronavirus disease 2019 (COVID-19) outbreaks in long-term care facilities (LTCFs) is facilitated by rapid identification and isolation of infectious individuals to interrupt viral transmission. Immunochromatographic (IC) tests, or rapid antigen tests, have high sensitivity and specificity during the contagious period for COVID-19. Mathematical modeling predicts frequent IC surveillance will be more efficient than polymerase chain reaction (PCR)-based strategies, especially during community surges when reporting of PCR results can be delayed. However, there are few published field studies evaluating IC testing strategies in this long-term care setting.

Methods

In fall and winter of 2020, the Marin Health and Human Services Department implemented thrice-weekly IC mass testing by nonlaboratory workers in outbreaks that occurred in 2 LTCFs, in addition to then-standard semiweekly PCR testing. The IC test performance was characterized using same-day PCR specimens as reference standard. Cumulative incidence and duration of transmission for the 2 IC intervention facility outbreaks were compared with 6 reference LTCFs that used weekly to semiweekly PCR alone during an outbreak response.

Results

Of 123 same-day test pairs, IC test sensitivity and specificity were 75% (95% confidence interval [CI], 48%-93%) and 100% (95% CI, 97%-100%), respectively. The median duration of outbreak transmission was 19.5 days in the 2 intervention sites and 28 days in the reference facilities (P = .40). Cumulative incidence for the outbreaks among LTCF residents was 41% in the intervention facilities versus 52% in the reference facilities (P = .04, Fisher 2-sided exact).

Conclusions

Thrice-weekly mass IC testing as used by nonlaboratory personnel can be highly practical and effective for COVID-19 outbreak mitigation in the LTCF setting.

The United States public health services failure to control the coronavirus epidemic

The unprecedented COVID-19 epidemic in the United States (US) and worldwide, caused by a new type of coronavirus (SARS-CoV-2), occurred mostly because of higher-than-expected transmission speed and degree of virulence compared with previous respiratory virus outbreaks, especially earlier Coronaviruses with person-to-person transmission (e.g., MERS, SARS). The epidemic's size and duration, however, are mostly a function of failure of public health systems to prevent/control the epidemic. In the US, this failure was due to historical disinvestment in public health services, key players equivocating on decisions, and political interference in public health actions. In this communication, we present a summary of these failures, discuss root causes, and make recommendations for improvement with focus on public health decisions.

An agent-based model of COVID-19 pandemic and its variants using fuzzy subsets and real data applied in an island environment

In this paper, we present a model of the spread of the COVID-19 pandemic simulated by a multi-agent system (MAS) based on demographic data and medical knowledge. Demographic data are linked to the distribution of the population according to age and to an index of socioeconomic fragility with regard to the elderly. Medical knowledge are related to two risk factors: age and obesity. The contributions of this approach are as follows. Firstly, the two aggravating risk factors are introduced into the MAS using fuzzy sets. Secondly, the worsening of disease caused by these risk factors is modeled by fuzzy aggregation operators. The appearance of virus variants is also introduced into the simulation through a simplified modeling of their contagiousness. Using real data from inhabitants of an island in the Antilles (Guadeloupe, FWI), we model the rate of the population at risk which could be critical cases, if neither social distancing nor barrier gestures are respected by the entire population. The results show that hospital capacities are exceeded. The results show that hospital capacities are exceeded. The socioeconomic fragility index is used to assess mortality and also shows that the number of deaths can be significant.

Excess deaths from COVID-19 among Medicare beneficiaries with psychiatric diagnoses: Community versus nursing home

BACKGROUND

Psychiatric illness may pose an additional risk of death for older adults during the COVID-19 pandemic. Older adults in the community versus institutions might be influenced by the pandemic differently. This study examines excess deaths during the COVID-19 pandemic among Medicare beneficiaries with and without psychiatric diagnoses (depression, anxiety, bipolar disorder, and schizophrenia) in the community versus nursing homes.

METHODS

This is a retrospective cohort study of a 20% random sample of 15,229,713 fee-for-service Medicare beneficiaries, from January 2019 through December 2021. Unadjusted monthly mortality risks, COVID-19 infection rates, and case-fatality rates after COVID-19 diagnosis were calculated. Excess deaths in 2020, compared to 2019 were estimated from multivariable logistic regressions.

RESULTS

Of all included Medicare beneficiaries in 2020 (N = 5,140,619), 28.9% had a psychiatric diagnosis; 1.7% lived in nursing homes. In 2020, there were 246,422 observed deaths, compared to 215,264 expected, representing a 14.5% increase over expected. Patients with psychiatric diagnoses had more excess deaths than those without psychiatric diagnoses (1,107 vs. 403 excess deaths per 100,000 beneficiaries, p < 0.01). The largest increases in mortality risks were observed among patients with schizophrenia (32.4% increase) and bipolar disorder (25.4% increase). The pandemic-associated increase in deaths with psychiatric diagnoses was only found in the community, not in nursing homes. The increased mortality for patients with psychiatric diagnoses was limited to those with medical comorbidities. The increase in mortality for psychiatric diagnoses was associated with higher COVID-19 infection rates (1-year infection rate = 7.9% vs. 4.2% in 2020), rather than excess case fatality.

CONCLUSIONS

Excess deaths during the COVID-19 pandemic were disproportionally greater in beneficiaries with psychiatric diagnoses, at least in part due to higher infection rates. Policy interventions should focus on preventing COVID-19 infections and deaths among community-dwelling patients with major psychiatric disorders in addition to those living the nursing homes.

COVID-19 related visiting ban in nursing homes as a source of concern for residents’ family members: a cross sectional study

Background

Visiting a close relative who resides in a nursing home is an opportunity for family members to extend their caring roles and find reassurance that the older person’s life is continuing as well as possible. At the same time, visits allow family members to observe the quality of formal care in the facility. In Finland, the COVID-19 pandemic led to the imposition of visiting bans in nursing homes in March 2020, thereby preventing customary interaction between residents and their family members. The aim of this study is to investigate family members’ experiences of the visiting ban and its effects on their concern over the wellbeing of close relatives living in nursing homes.

Methods

A cross-sectional study was conducted to explore family members’ self-reported concerns and the factors associated with those concerns. In the context of this unpredictable pandemic, this was considered an appropriate approach, as information at the very beginning of the visiting ban was sought, and causal relations were not investigated. The data consist of a quantitative survey (n = 366) conducted among family members in May–June 2020. Binary logistic regression analyses were performed to explore the association between the independent variables and reported concern.

Results

The results showed that increased concern was extremely common (79%). The factors associated with this notable increase were adequacy of contact and information, observations of changes in the wellbeing of the relative in question, and doubts over the appropriateness of the visiting restriction.

Conclusions

In light of the findings, care providers should improve their information provision to residents’ family members and find new ways of allowing visits to nursing homes in the future in all circumstances.

Changes in Health and Quality of Life in US Skilled Nursing Facilities by COVID-19 Exposure Status in 2020

Importance

During the COVID-19 pandemic, the US federal government required that skilled nursing facilities (SNFs) close to visitors and eliminate communal activities. Although these policies were intended to protect residents, they may have had unintended negative effects.

Objective

To assess health outcomes among SNFs with and without known COVID-19 cases.

Design, Setting, and Participants

This retrospective observational study used US Medicare claims and Minimum Data Set 3.0 for January through November in each year beginning in 2018 and ending in 2020 including 15 477 US SNFs with 2 985 864 resident-years.

Exposures

January through November of calendar years 2018, 2019, and 2020. COVID-19 diagnoses were used to assign SNFs into 2 mutually exclusive groups with varying membership by month in 2020: active COVID-19 (≥1 COVID-19 diagnosis in the current or past month) or no-known COVID-19 (no observed diagnosis by that month).

Main Outcomes and Measures

Monthly rates of mortality, hospitalization, emergency department (ED) visits, and monthly changes in activities of daily living (ADLs), body weight, and depressive symptoms. Each SNF in 2018 and 2019 served as its own control for 2020.

Results

In 2018-2019, mean monthly mortality was 2.2%, hospitalization 3.0%, and ED visit rate 2.9% overall. In 2020, among active COVID-19 SNFs compared with their own 2018-2019 baseline, mortality increased by 1.60% (95% CI, 1.58% to 1.62%), hospitalizations decreased by 0.10% (95% CI, -0.12% to -0.09%), and ED visit rates decreased by 0.57% (95% CI, -0.59% to -0.55%). Among no-known COVID-19 SNFs, mortality decreased by 0.15% (95% CI, -0.16% to -0.13%), hospitalizations by 0.83% (95% CI, -0.85% to -0.81%), and ED visits by 0.79% (95% CI, -0.81% to -0.77%). All changes were statistically significant. In 2018-2019, across all SNFs, residents required assistance with an additional 0.89 ADLs between January and November, and lost 1.9 lb; 27.1% had worsened depressive symptoms. In 2020, residents in active COVID-19 SNFs required assistance with an additional 0.36 ADLs (95% CI, 0.34 to 0.38), lost 3.1 lb (95% CI, -3.2 to -3.0 lb) more weight, and were 4.4% (95% CI, 4.1% to 4.7%) more likely to have worsened depressive symptoms, all statistically significant changes. In 2020, residents in no-known COVID-19 SNFs had no significant change in ADLs (-0.06 [95% CI, -0.12 to 0.01]), but lost 1.8 lb (95% CI, -2.1 to -1.5 lb) more weight and were 3.2% more likely (95% CI, 2.3% to 4.1%) to have worsened depressive symptoms, both statistically significant changes.

Conclusions and Relevance

Among skilled nursing facilities in the US during the first year of the COVID-19 pandemic and prior to the availability of COVID-19 vaccination, mortality and functional decline significantly increased at facilities with active COVID-19 cases compared with the prepandemic period, while a modest statistically significant decrease in mortality was observed at facilities that had never had a known COVID-19 case. Weight loss and depressive symptoms significantly increased in skilled nursing facilities in the first year of the pandemic, regardless of COVID-19 status.

Managing the Impact of COVID-19 in Nursing Homes and Long-Term Care Facilities: An Update

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 more than 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 and 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 or family, and staff well-being. 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, nonpharmacologic outbreak control measures and vaccination strategies in this cohort. Finally, the impact of SARS-CoV-2 on the sector is reflected on as we emphasize 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.

Incidence and Outcomes of SARS-CoV-2 in Post-Acute Skilled Nursing Facility Care

OBJECTIVES

To examine the risk of contracting SARS-CoV-2 during a post-acute skilled nursing facility (SNF) stay and the associated risk of death.

DESIGN

Cohort study using Minimum Data Set and electronic health record data from a large multistate long-term care provider. Primary outcomes included testing positive for SARS-CoV-2 during the post-acute SNF stay, and death among those who tested positive.

SETTING AND PARTICIPANTS

The sample included all new admissions to the provider's 286 SNFs between January 1 and December 31, 2020. Patients known to be infected with SARS-CoV-2 at the time of admission were excluded.

METHODS

SARS-CoV-2 infection and mortality rates were measured in time intervals by month of admission. A parametric survival model with SNF random effects was used to measure the association of patient demographic factors, clinical characteristics, and month of admission, with testing positive for SARS-CoV-2.

RESULTS

The sample included 45,094 post-acute SNF admissions. Overall, 5.7% of patients tested positive for SARS-CoV-2 within 100 days of admission, with 1.0% testing positive within 1-14 days, 1.4% within 15-30 days, and 3.4% within 31-100 days. Of all newly admitted patients, 0.8% contracted SARS-CoV-2 and died, whereas 6.7% died without known infection. Infection rates and subsequent risk of death were highest for patients admitted during the first and third US pandemic waves. Patients with greater cognitive and functional impairment had a 1.45 to 1.92 times higher risk of contracting SARS-CoV-2 than patients with less impairment.

CONCLUSIONS AND IMPLICATIONS

The absolute risk of SARS-CoV-2 infection and death during a post-acute SNF admission was 0.8%. Those who did contract SARS-CoV-2 during their SNF stay had nearly double the rate of death as those who were not infected. Findings from this study provide context for people requiring post-acute care, and their support systems, in navigating decisions around SNF admission during the SARS-CoV-2 pandemic.

Staffing Patterns in US Nursing Homes During COVID-19 Outbreaks

Importance

Staff absences and departures at nursing homes may put residents at risk and present operational challenges.

Objective

To quantify changes in nursing home facility staffing during and after a severe COVID-19 outbreak.

Design Setting and Participants

In this cohort study, daily staffing payroll data were used to construct weekly measures of facility staffing, absences, departures, and use of overtime and contract staff among US nursing homes experiencing a severe COVID-19 outbreak that started between June 14, 2020, and January 1, 2021. Facility outbreaks were identified using COVID-19 case data. An event-study design with facility and week fixed effects was used to investigate the association of severe outbreaks with staffing measures.

Exposures

Weeks since the beginning of a severe COVID-19 outbreak (4 weeks prior to 16 weeks after).

Main Outcomes and Measures

Total weekly staffing hours, staff counts, staff absences, departures, new hires, overtime and contract staff hours measured for all nursing staff and separately by staff type (registered nurses, licensed practical nurses, certified nursing assistants), facility self-reported staff shortages, and resident deaths.

Results

Of the included 2967 nursing homes experiencing severe COVID-19 outbreaks, severe outbreaks were associated with a statistically significant drop in nursing staffing levels owing to elevated absences and departures. Four weeks after an outbreak's start, around when average new cases peaked, staffing hours were 2.6% (95% CI, 2.1%-3.2%) of the mean below preoutbreak levels, despite facilities taking substantial measures to bolster staffing through increased hiring and the use of contract staff and overtime. Because these measures were mostly temporary, staffing declined further in later weeks; 16 weeks after an outbreak's start, staffing hours were 5.5% (95% CI, 4.5%-6.5%) of the mean below preoutbreak levels. Staffing declines were greatest among certified nursing assistants, primarily owing to smaller increases in new hires of this staff type compared with licensed practical nurses and registered nurses.

Conclusions and Relevance

In this cohort study of nursing homes experiencing severe COVID-19 outbreaks, facilities experienced considerable staffing challenges during and after outbreaks. These results suggest the need for policy action to ensure facilities' abilities to maintain adequate staffing levels during and after infectious disease outbreaks.

Associations between Florida counties' COVID-19 case and death rates and meaningful use among Medicaid providers: Cross-sectional ecologic study

Although the Health Information Technology for Economic and Clinical Health (HITECH) Act has accelerated adoption of Electronic Health Records (EHRs) among Medicaid providers, only half achieved Meaningful Use. Furthermore, Meaningful Use' impact on reporting and/or clinical outcomes remains unknown. To address this deficit, we assessed the difference between Medicaid providers who did and did not achieve Meaningful Use regarding Florida county-level cumulative COVID-19 death, case and case fatality rates (CFR), accounting for county-level demographics, socioeconomic and clinical markers, and healthcare environment. We found that cumulative incidence rates of COVID-19 deaths and CFRs were significantly different between the 5025 Medicaid providers not achieving Meaningful Use and the 3723 achieving Meaningful Use (mean 0.8334/1000 population; SD = 0.3489 vs. mean = 0.8216/1000; SD = 0.3227, respectively) (P = .01). CFRs were .01797 and .01781, respectively, P = .04. County-level characteristics independently associated with increased COVID-19 death rates and CFRs include greater concentrations of persons of African American or Black race, lower median household income, higher unemployment, and higher concentrations of those living in poverty and without health insurance (all P < .001). In accordance with other studies, social determinants of health were independently associated with clinical outcomes. Our findings also suggest that the association between Florida counties' public health outcomes and Meaningful Use achievement may have had less to do with using EHRs for reporting of clinical outcomes and more to do with using EHRs for coordination of care-a key measure of quality. The Florida Medicaid Promoting Interoperability Program which incentivized Medicaid providers towards achieving Meaningful Use, has demonstrated success regarding both rates of adoption and clinical outcomes. Because the Program ends in 2021, we support programs such as HealthyPeople 2030 Health IT which address the remaining half of Florida Medicaid providers who have not yet achieved Meaningful Use.

COVID-19 amongst western democracies: A welfare state analysis

The COVID-19 pandemic has resulted in more than 282 million cases and almost 5.5 million deaths (WHO Coronavirus Disease (COVID-19) Dashboard, 2022). Its impact, however, has not been uniform. This analysis examines differences in COVID-19 cases and mortality rates amongst different welfare states within the first three waves of the pandemic using repeated measures Multivariate Analysis of Covariance (MANCOVA). Liberal states fared much better on the number of COVID-19 cases, deaths, and excess deaths than the Conservative/Corporatist welfare democracies. Social Democratic countries, in turn, did not fare any better than their Conservative/Corporatist counterparts once potential confounding economic and political variables were accounted for: countries’ economic status, healthcare spending, availability of medical personnel, hospital beds, pandemic-related income support and debt relief, electoral events, and left-power mobilization. The pandemic-related welfare responses after the first wave were similar across all three types of western democracies, but the differences in pandemic outcomes remained. The somewhat better outlook of the Liberal states could be attributed to the so-called social democratization of the Anglo-American democracies, but also to the fact that neoliberalism could have flattened the previous differences between the welfare states typologies and could have brought states closer to each other, ideologically speaking, in terms of welfare provision.

Structural Racism, Place, and COVID-19: A Narrative Review Describing How We Prepare for an Endemic COVID-19 Future

Background:

Place is a social determinant of health, as recently evidenced by COVID-19. Previous literature surrounding health disparities in the United States often fails to acknowledge the role of structural racism on place-based health disparities for historically marginalized communities (i.e., Black and African American communities, Hispanic/Latinx communities, Indigenous communities [i.e., First Nations, Native American, Alaskan Native, and Native Hawaiian], and Pacific Islanders). This narrative review summarizes the intersection between structural racism and place as contributors to COVID-19 health disparities.

Methods:

This narrative review accounts for the unique place-based health care experiences influenced by structural racism, including health systems and services and physical environment. We searched online databases for peer-reviewed and governmental sources, published in English between 2000 and 2021, related to place-based U.S. health inequities in historically marginalized communities. We then narrate the link between the historical trajectory of structural racism and current COVID-19 health outcomes for historically marginalized communities.

Results:

Structural racism has infrequently been named as a contributor to place as a social determinant of health. This narrative review details how place is intricately intertwined with the results of structural racism, focusing on one's access to health systems and services and physical environment, including the outdoor air and drinking water. The role of place, health disparities, and structural racism has been starkly displayed during the COVID-19 pandemic, where historically marginalized communities have been subject to greater rates of COVID-19 incidence and mortality.

Conclusion:

As COVID-19 becomes endemic, it is crucial to understand how place-based inequities and structural racism contributed to the COVID-19 racial disparities in incidence and mortality. Addressing structurally racist place-based health inequities through anti-racist policy strategies is one way to move the United States toward achieving health equity.

Resident Mortality And Worker Infection Rates From COVID-19 Lower In Union Than Nonunion US Nursing Homes, 2020-21

Since the start of the COVID-19 pandemic, nursing home residents have accounted for roughly one of every six COVID-19 deaths in the United States. Nursing homes have also been very dangerous places for workers, with more than one million nursing home workers testing positive for COVID-19 as of April 2022. Labor unions may play an important role in improving workplace safety, with potential benefits for both nursing home workers and residents. We examined whether unions for nursing home staff were associated with lower resident COVID-19 mortality rates and worker COVID-19 infection rates compared with rates in nonunion nursing homes, using proprietary data on nursing home-level union status from the Service Employees International Union for all forty-eight continental US states from June 8, 2020, through March 21, 2021. Using negative binomial regression and adjusting for potential confounders, we found that unions were associated with 10.8 percent lower resident COVID-19 mortality rates, as well as 6.8 percent lower worker COVID-19 infection rates. Substantive results were similar, although sometimes smaller and less precisely estimated, in sensitivity analyses.

There and back again: the shape of telemedicine in U.S. nursing homes following COVID-19

Introduction

Telemedicine use in nursing homes (NHs) expanded during the COVID-19 pandemic. The objectives of this study were to characterize plans to continue telemedicine among newly adopting NHs and identify factors limiting its use after COVID-19.

Methods

Key informants from 9 Wisconsin NHs that adopted telemedicine during COVID-19 were recruited. Semi-structured interviews and surveys were employed to identify participant perceptions about the value of telemedicine, implementation challenges encountered, and plans and barriers to sustaining its delivery after COVID-19. Directed content analysis and a deductive thematic approach using the Systems Engineering Initiative for Patient Safety (SEIPS) model was used during analyses. Quantitative and qualitative data were integrated to identify participant views on the value of telemedicine and the tools and work system enhancements needed to make telemedicine easier and more effective.

Results

All participating NHs indicated a preference to continue telemedicine after COVID-19. Urgent assessments of resident change-in-condition and cognitively based sub-specialty consultations were identified as the encounter types most amenable to telemedicine. Reductions in resident off-site encounters and minimization of resident therapy interruptions were identified as major benefits of telemedicine. Twelve work system enhancements needed to better sustain telemedicine were identified, including improvements to: 1) equipment/IT infrastructure; 2) scheduling; 3) information exchange; and 4) telemedicine facilitators.

Discussion

NHs that adopted telemedicine during COVID-19 wish to continue its use. However, interventions that enhance the integration of telemedicine into NH and off-site clinic work systems require changes to existing regulations and reimbursement models to sustain its utilization after COVID-19.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03046-y.

Factors associated with COVID-19 mortality in municipalities in the state of São Paulo (Brazil): an ecological study

Background:

The mortality rate of coronavirus disease (COVID-19) in the state of São Paulo is highly heterogeneous. This study investigated geographic, economic, social, and health-related factors associated with this discrepancy.

Methods:

An ecological study compared COVID-19 mortality rates according to geographic, economic, social, and health-related variables during initial infection of 2.5% of the population in municipalities with more than 30,000 inhabitants.

Results:

Mortality was positively associated with demographic density and social inequality (Gini index), and inversely associated with HDI income and longevity of these municipalities, accounting for 33.2% of the variation in mortality.

Conclusions:

Social determinants influenced COVID-19 outcomes.

Modeling of nursing care-associated airborne transmission of SARS-CoV-2 in a real-world hospital setting

Respiratory transmission of SARS-CoV-2 from one older patient to another by airborne mechanisms in hospital and nursing home settings represents an important health challenge during the COVID-19 pandemic. However, the factors that influence the concentration of respiratory droplets and aerosols that potentially contribute to hospital- and nursing care-associated transmission of SARS-CoV-2 are not well understood. To assess the effect of health care professional (HCP) and patient activity on size and concentration of airborne particles, an optical particle counter was placed (for 24 h) in the head position of an empty bed in the hospital room of a patient admitted from the nursing home with confirmed COVID-19. The type and duration of the activity, as well as the number of HCPs providing patient care, were recorded. Concentration changes associated with specific activities were determined, and airway deposition modeling was performed using these data. Thirty-one activities were recorded, and six representative ones were selected for deposition modeling, including patient's activities (coughing, movements, etc.), diagnostic and therapeutic interventions (e.g., diagnostic tests and drug administration), as well as nursing patient care (e.g., bedding and hygiene). The increase in particle concentration of all sizes was sensitive to the type of activity. Increases in supermicron particle concentration were associated with the number of HCPs (r = 0.66; p < 0.05) and the duration of activity (r = 0.82; p < 0.05), while submicron particles increased with all activities, mainly during the daytime. Based on simulations, the number of particles deposited in unit time was the highest in the acinar region, while deposition density rate (number/cm2/min) was the highest in the upper airways. In conclusion, even short periods of HCP-patient interaction and minimal patient activity in a hospital room or nursing home bedroom may significantly increase the concentration of submicron particles mainly depositing in the acinar regions, while mainly nursing activities increase the concentration of supermicron particles depositing in larger airways of the adjacent bed patient. Our data emphasize the need for effective interventions to limit hospital- and nursing care-associated transmission of SARS-CoV-2 and other respiratory pathogens (including viral pathogens, such as rhinoviruses, respiratory syncytial virus, influenza virus, parainfluenza virus and adenoviruses, and bacterial and fungal pathogens).

Evaluating the Findings of the IMPACT-C Randomized Clinical Trial to Improve COVID-19 Vaccine Coverage in Skilled Nursing Facilities

IMPORTANCE

Identifying successful strategies to increase COVID-19 vaccination among skilled nursing facility (SNF) residents and staff is integral to preventing future outbreaks in a continually overwhelmed system.

OBJECTIVE

To determine whether a multicomponent vaccine campaign would increase vaccine rates among SNF residents and staff.

DESIGN, SETTING, AND PARTICIPANTS

This was a cluster randomized trial with a rapid timeline (December 2020-March 2021) coinciding with the Pharmacy Partnership Program (PPP). It included 133 SNFs in 4 health care systems across 16 states: 63 and 70 facilities in the intervention and control arms, respectively, and participants included 7496 long-stay residents (>100 days) and 17 963 staff.

INTERVENTIONS

Multicomponent interventions were introduced at the facility level that included: (1) educational material and electronic messaging for staff; (2) town hall meetings with frontline staff (nurses, nurse aides, dietary, housekeeping); (3) messaging from community leaders; (4) gifts (eg, T-shirts) with socially concerned messaging; (5) use of a specialist to facilitate consent with residents' proxies; and (6) funds for additional COVID-19 testing of staff/residents.

MAIN OUTCOMES AND MEASURES

The primary outcomes of this study were the proportion of residents (from electronic medical records) and staff (from facility logs) who received a COVID-19 vaccine (any), examined as 2 separate outcomes. Mixed-effects generalized linear models with a binomial distribution were used to compare outcomes between arms, using intent-to-treat approach. Race was examined as an effect modifier in the resident outcome model.

RESULTS

Most facilities were for-profit (95; 71.4%), and 1973 (26.3%) of residents were Black. Among residents, 82.5% (95% CI, 81.2%-83.7%) were vaccinated in the intervention arm, compared with 79.8% (95% CI, 78.5%-81.0%) in the usual care arm (marginal difference 0.8%; 95% CI, -1.9% to 3.7%). Among staff, 49.5% (95% CI, 48.4%-50.6%) were vaccinated in the intervention arm, compared with 47.9% (95% CI, 46.9%-48.9%) in usual care arm (marginal difference: -0.4%; 95% CI, -4.2% to 3.1%). There was no association of race with the outcome among residents.

CONCLUSIONS AND RELEVANCE

A multicomponent vaccine campaign did not have a significant effect on vaccination rates among SNF residents or staff. Among residents, vaccination rates were high. However, half the staff remained unvaccinated despite these efforts. Vaccination campaigns to target SNF staff will likely need to use additional approaches.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04732819.

A Typology of COVID-19 Data Gaps and Noise From Long-Term Care Facilities: Approximating the True Numbers

Although there is agreement that COVID-19 has had devastating impacts in long-term care facilities (LTCFs), estimates of cases and deaths have varied widely with little attention to the causes of this variation. We developed a typology of data vulnerabilities and a strategy for approximating the true total of COVID-19 cases and deaths in LTCFs. Based on iterative qualitative consensus, we categorized LTCF reporting vulnerabilities and their potential impacts on accuracy. Concurrently, we compiled one dataset based on LTCF self-reports and one based on confirmatory matching with California’s COVID-19 databases, including death certificates. Through March 2021, Alameda County LTCFs reported 6663 COVID-19 cases and 481 deaths. In contrast, our confirmatory matching file includes 5010 cases and 594 deaths, corresponding to 25% fewer cases but 23% more deaths. We argue that the higher (self-report) case total approximates the lower bound of true COVID-19 cases, and the higher (confirmed match) death total approximates the lower bound of true COVID-19 deaths, both of which are higher than state and federal counts. LTCFs other than nursing facilities accounted for 35% of cases and 29% of deaths. Improving the accuracy of COVID-19 figures, particularly across types of LTCFs, would better inform interventions for these vulnerable populations.

A Tale of Two Surges: Differences in Outcomes in the COVID-19 Pandemic in a Community Teaching Hospital in Massachusetts

Background

The coronavirus disease 2019 (COVID-19) pandemic has challenged the scientific community in the prompt implementation of therapies. We report and contrast characteristics and outcomes from two COVID-19 surges in March 2020 and December 2020 in patients at MetroWest Medical Center in Framingham.

Methods

The study was conducted at MetroWest Medical Center. We extracted the data of 315 patients from March 17, 2020, to June 30, 2020, and 104 patients from November 19, 2020, to December 30, 2020. All patients were inpatients and had confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by polymerase chain reaction (PCR). We extracted the patient’s demographic information, clinical data, and given treatments. We also examined comorbidities and categorized them by the Charlson Comorbidity Index (CCI). The primary endpoints were intensive care unit (ICU) level of care, mechanical ventilation, or death.

Results

A total of 419 patients were studied. The median age was 76. During the first surge (S1), 150 (47%) were from nursing homes and 133 (42%) were from independent living. More than half (72) of the independent living patients had a primary language other than English. During the second surge (S2), 12% (13) were from nursing homes. The most common comorbidities were similar for both groups and included obesity, diabetes, and chronic lung disease. However, during the first surge, 33% (104) of the patients had dementia. The median Charlson Comorbidity Index score was worse in the first surge; the predicted 10-year survival was 21% versus 53%. The treatments given included remdesivir in 5% (16) in the first surge versus 60% (62) in the second surge. Dexamethasone was given only in the second surge in 69% (72) of the patients.

Outcomes

The reported outcomes are contrasted by the first versus the second surge. Admission to the intensive care unit was required in 83 (27%) of the patients during the first surge versus 15 (14%) of the patients during the second surge. Mechanical ventilation was required in 33 (11%) of the patients during the first surge versus 5 (11%) of the patients during the second surge. The overall mortality was 25% during the first surge (79) versus 9% (9) during the second surge.

Conclusion

Among patients with COVID-19 infection admitted to a community teaching hospital during the second Massachusetts surge, there was a significant improvement in clinical outcomes, particularly mortality, compared with patients admitted during the early pandemic. It is tempting to attribute the improved outcomes to the implementation of treatment with corticosteroids and more use of antiviral therapy. However, the patients admitted during the larger first surge were more likely to have a do not resuscitate (DNR) status on admission, be from a nursing home, have dementia, and have poorer predicted survival.

Longitudinal validation of an electronic health record delirium prediction model applied at admission in COVID-19 patients

OBJECTIVE

To validate a previously published machine learning model of delirium risk in hospitalized patients with coronavirus disease 2019 (COVID-19).

METHOD

Using data from six hospitals across two academic medical networks covering care occurring after initial model development, we calculated the predicted risk of delirium using a previously developed risk model applied to diagnostic, medication, laboratory, and other clinical features available in the electronic health record (EHR) at time of hospital admission. We evaluated the accuracy of these predictions against subsequent delirium diagnoses during that admission.

RESULTS

Of the 5102 patients in this cohort, 716 (14%) developed delirium. The model's risk predictions produced a c-index of 0.75 (95% CI, 0.73-0.77) with 27.7% of cases occurring in the top decile of predicted risk scores. Model calibration was diminished compared to the initial COVID-19 wave.

CONCLUSION

This EHR delirium risk prediction model, developed during the initial surge of COVID-19 patients, produced consistent discrimination over subsequent larger waves; however, with changing cohort composition and delirium occurrence rates, model calibration decreased. These results underscore the importance of calibration, and the challenge of developing risk models for clinical contexts where standard of care and clinical populations may shift.

Immunogenicity after 6 months of BNT162b2 vaccination in frail or disabled nursing home residents: The COVID-A Study

BACKGROUND

There is incomplete information regarding evolution of antibody titers against SARS-CoV-2 after a two-dose strategy vaccination with BNT162b2 in older adults in long-term care facilities (LTCFs) with frailty, disability, or cognitive impairment. We aimed to determine IgG antibody titer loss in older adults in LTCFs.

METHODS

This is a multicenter longitudinal cohort study including 127 residents (90 females and 37 males) with a mean age of 82.7 years (range 65-99) with different frailty and disability profiles in two LTCFs in Albacete, Spain. Residents received two doses of BNT162b2 as per label, and antibody levels were determined 1 and 6 months after the second dose. Age, sex, previous history of coronavirus disease 2019 (COVID-19), comorbidity (Charlson Index), performance in activities of daily living (Barthel Index), frailty (FRAIL instrument), and cognitive status were assessed.

RESULTS

The mean antibody titers 1 and 6 months after the second vaccine dose were 32,145 AU/ml (SD 41,206) and 6182 AU/ml (SD 13,316), respectively. Across all participants, the median antibody titer loss measured 77.6% (interquartile range [IQR] 23.8%). Notably, the decline of titers in individuals with pre-vaccination COVID-19 infection was significantly lower than in those without a history of SARS-CoV-2 infection (72.2% vs. 85.3%; p < 0.001). The median titer decrease per follow-up day was 0.47% (IQR 0.14%) and only pre-vaccination COVID-19 was associated with lower rate of antibody decline at 6 months (hazard ratio 0.17; 95% confidence interval 0.07-0.41; p < 0.001). Frailty, disability, older age, cognitive impairment, or comorbidity were not associated with the extent of antibody loss.

CONCLUSIONS

Older adults in LTCFs experience a rapid loss of antibodies over the first 6 months after the second dose of BNT162b2 vaccine. Only pre-vaccination COVID-19 is associated with a slower rate of antibody decrease. Our data support immunization with a third dose in this vulnerable, high-risk population.