scholarly journals COVID-19 infection and attributable mortality in UK care homes: cohort study using active surveillance and electronic records (March–June 2020)

2021 ◽  
Author(s):  
Peter F Dutey-Magni ◽  
Haydn Williams ◽  
Arnoupe Jhass ◽  
Greta Rait ◽  
Fabiana Lorencatto ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Care Home ◽  
Case Fatality ◽  
Epidemiological Data ◽  
Care Homes ◽  
Attributable Mortality ◽  
Term Care ◽  
Individual Level ◽  
Staffing Ratios

Abstract Background epidemiological data on COVID-19 infection in care homes are scarce. We analysed data from a large provider of long-term care for older people to investigate infection and mortality during the first wave of the pandemic. Methods cohort study of 179 UK care homes with 9,339 residents and 11,604 staff. We used manager-reported daily tallies to estimate the incidence of suspected and confirmed infection and mortality in staff and residents. Individual-level electronic health records from 8,713 residents were used to model risk factors for confirmed infection, mortality and estimate attributable mortality. Results 2,075/9,339 residents developed COVID-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory-confirmed infections. The incidence of confirmed infection was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days in residents and staff, respectively. Sixty-eight percent (121/179) of care homes had at least one COVID-19 infection or COVID-19-related death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection. Out of 607 residents with confirmed infection, 217 died (case fatality rate: 35.7% [31.9%; 39.7%]). Mortality in residents with no direct evidence of infection was twofold higher in care homes with outbreaks versus those without (adjusted hazard ratio: 2.2 [1.8; 2.6]). Conclusions findings suggest many deaths occurred in people who were infected with COVID-19, but not tested. Higher occupancy and lower staffing levels were independently associated with risks of infection. Protecting staff and residents from infection requires regular testing for COVID-19 and fundamental changes to staffing and care home occupancy.

scholarly journals Covid-19 infection and attributable mortality in UK Long Term Care Facilities: Cohort study using active surveillance and electronic records (March-June 2020)

2020 ◽  
Author(s):  
Peter F Dutey-Magni ◽  
Haydn Williams ◽  
Arnoupe Jhass ◽  
Greta Rait ◽  
Harry Hemingway ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Active Surveillance ◽  
Long Term Care ◽  
Case Fatality ◽  
Control Measures ◽  
Attributable Mortality ◽  
Term Care ◽  
Care Facilities

Background: Rates of Covid-19 infection have declined in many countries, but outbreaks persist in residents of long-term care facilities (LTCFs) who are at high risk of severe outcomes. Epidemiological data from LTCFs are scarce. We used population-level active surveillance to estimate incidence of, and risk factors for Covid-19, and attributable mortality in elderly residents of LTCFs. Methods: Cohort study using individual-level electronic health records from 8,713 residents and daily counts of infection for 9,339 residents and 11,604 staff across 179 UK LTCFs. We modelled risk factors for infection and mortality using Cox proportional hazards and estimated attributable fractions. Findings: 2,075/9,339 residents developed Covid-19 symptoms (22.2% [95% confidence interval: 21.4%; 23.1%]), while 951 residents (10.2% [9.6%; 10.8%]) and 585 staff (5.0% [4.7%; 5.5%]) had laboratory confirmed infections. Confirmed infection incidence in residents and staff respectively was 152.6 [143.1; 162.6] and 62.3 [57.3; 67.5] per 100,000 person-days. 121/179 (67.6%) LTCFs had at least one Covid-19 infection or death. Lower staffing ratios and higher occupancy rates were independent risk factors for infection. 1,694 all-cause deaths occurred in 8,713 (19.4% [18.6%; 20.3%]) residents. 217 deaths occurred in 607 residents with confirmed infection (case-fatality rate: 35.7% [31.9%; 39.7%]). 567/1694 (33.5%) of all-cause deaths were attributable to Covid-19, 28.0% of which occurred in residents with laboratory-confirmed infection. The remainder of excess deaths occurred in asymptomatic or symptomatic residents in the context of limited testing for infection, suggesting substantial under-ascertainment. Interpretation: 1 in 5 residents had symptoms of infection during the pandemic, but many cases were not tested. Higher occupancy and lower staffing levels increase infection risk. Disease control measures should integrate active surveillance and testing with fundamental changes in staffing and care home occupancy to protect staff and residents from infection. Funding: Economic and Social Research Council [ES/V003887/1].

scholarly journals COVID-19 risk factors amongst 14,786 care home residents: An observational longitudinal analysis including daily community positive test rates of COVID-19, hospital stays, and vaccination status in Wales (UK) between 1st September 2020 and 1st May 2021.

2021 ◽  
Author(s):  
Joe Hollinghurst ◽  
Robyn Hollinghurst ◽  
Laura North ◽  
Amy Mizen ◽  
Ashley Akbari ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Hospital Admissions ◽  
Care Home ◽  
Vaccination Status ◽  
Care Homes ◽  
Positive Test ◽  
Care Providers ◽  
Specialist Care ◽  
Individual Level

Objectives: Determine individual level risk factors for care home residents testing positive for SARS-CoV-2. Study Design: Longitudinal observational cohort study using individual-level linked data. Setting: Care home residents in Wales (United Kingdom) between 1st September 2020 and 1st May 2021. Participants: 14,786 older care home residents (aged 65+). Our dataset consisted of 2,613,341 individual-level daily observations within 697 care homes. Methods: We estimated odds ratios (ORs [95% confidence interval]) using multilevel logistic regression models. Our outcome of interest was a positive SARS-CoV-2 polymerase chain reaction (PCR) test. We included time dependent covariates for the estimated community positive test rate of COVID-19, hospital admissions, and vaccination status. Additional covariates were included for age, positive PCR tests prior to the study, sex, frailty (using the hospital frailty risk score), and specialist care home services. Results: The multivariable logistic regression model indicated an increase in age (OR 1.01 [1.00,1.01] per year of age), community positive test rate (OR 1.13 [1.12,1.13] per percent increase in positive test rate), hospital inpatients (OR 7.40 [6.54,8.36]), and residents in care homes with non-specialist dementia care (OR 1.42 [1.01,1.99]) had an increased odds of a positive test. Having a positive test prior to the observation period (OR 0.58 [0.49,0.68]) and either one or two doses of a vaccine (0.21 [0.17,0.25] and 0.05 [0.02,0.09] respectively) were associated with a decreased odds of a positive test. Conclusions: Our findings suggest care providers need to stay vigilant despite the vaccination rollout, and extra precautions should be taken when caring for the most vulnerable. Furthermore, minimising potential COVID-19 infection for care home residents admitted to hospital should be prioritised.

scholarly journals Geographical variation and clustering are found in atrial fibrillation beyond socioeconomic differences: a Danish cohort study, 1987–2015

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Kirstine Wodschow ◽  
Kristine Bihrmann ◽  
Mogens Lytken Larsen ◽  
Gunnar Gislason ◽  
Annette Kjær Ersbøll
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Cohort Study ◽  
Incidence Rate ◽  
Socioeconomic Position ◽  
Geographical Variation ◽  
Incidence Rates ◽  
Socioeconomic Differences ◽  
Individual Level ◽  
Geographical Variations

Abstract Background The prevalence and incidence rate of atrial fibrillation (AF) increase worldwide and AF is a risk factor for more adverse cardiovascular diseases including stroke. Approximately 44% of AF cases cannot be explained by common individual risk factors and risk might therefore also be related to the environment. By studying geographical variation and clustering in risk of incident AF adjusted for socioeconomic position at an individual level, potential neighbourhood risk factors could be revealed. Methods Initially, yearly AF incidence rates 1987–2015 were estimated overall and stratified by income in a register-based cohort study. To examine geographical variation and clustering in AF, we used both spatial scan statistics and a hierarchical Bayesian Poisson regression analysis of AF incidence rates with random effect of municipalities (n = 98) in Denmark in 2011–2015. Results The 1987–2015 cohort included 5,453,639 individuals whereof 369,800 were diagnosed with an incident AF. AF incidence rate increased from 174 to 576 per 100,000 person-years from 1987 to 2015. Inequality in AF incidence rate ratio between highest and lowest income groups increased from 23% in 1987 to 38% in 2015. We found clustering and geographical variation in AF incidence rates, with incidence rates at municipality level being up to 34% higher than the country mean after adjusting for socioeconomic position. Conclusions Geographical variations and clustering in AF incidence rates exist. Compared to previous studies from Alberta, Canada and the United States, we show that geographical variations exist in a country with free access to healthcare and even when accounting for socioeconomic differences at an individual level. An increasing social inequality in AF was seen from 1987 to 2015. Therefore, when planning prevention strategies, attention to individuals with low income should be given. Further studies focusing on identification of neighbourhood risk factors for AF are needed.

scholarly journals National Early Warning Scores And COVID-19 Deaths In Care Homes: An Ecological Time Series Study

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 962-963
Author(s):  
Daniel Stow ◽  
Robert Barker ◽  
Fiona Matthews ◽  
Barbara Hanratty
Keyword(s):  
Time Series ◽  
Oxygen Saturation ◽  
Respiratory Rate ◽  
Early Warning ◽  
Disease Surveillance ◽  
Care Home ◽  
Outcome Data ◽  
Care Homes ◽  
Individual Level ◽  
Early Warning Scores

Abstract Tracking COVID-19 infections in the care home population has been challenging, because of the limited availability of testing and varied disease presentation. We consider whether National Early Warning Scores (NEWS/NEWS2) could contribute to COVID-19 surveillance in care homes. We analysed NEWS measurements from care homes in England (December 2019 to May 2020). We estimated pre-COVID (baseline) levels for NEWS and NEWS components using 80th and 20th centile scores for measurements before March 2020. We used time-series to compare the proportion of above-baseline NEWS to area-matched reports of registered deaths in care home residents from the Office for National Statistics We analysed 29,656 anonymised NEWS from 6,464 people in 480 care home units across 46 local authority areas. From March 23rd to May 20th, there were 5,753 deaths (1,532 involving COVID-19, 4,221 other causes) in corresponding geographical areas. A rise in the proportion of above-baseline NEWS was observed from March 16th 2020. The proportion of above-baseline oxygen saturation, respiratory rate and temperature measurements also increased approximately two weeks before peaks in deaths. We conclude that NEWS could contribute to disease surveillance in care homes during the COVID-19 pandemic. Oxygen saturation, respiratory rate and temperature could be prioritised as they appear to signal rise in mortality almost as well as total NEWS. This study reinforces the need to collate data from care homes, to monitor and protect residents’ health. Further work using individual level outcome data is needed to evaluate the role of NEWS in the early detection of resident illness.

scholarly journals Risk factors for pneumonia and influenza hospitalizations in long-term care facility residents: a retrospective cohort study

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Patience Moyo ◽  
Andrew R. Zullo ◽  
Kevin W. McConeghy ◽  
Elliott Bosco ◽  
Robertus van Aalst ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Long Term Care ◽  
Care Facility ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility

scholarly journals Depression and Functional Mobility Decline in Long Term Care Home Residents with Dementia: a Prospective Cohort Study

2021 ◽  
Vol 24 (4) ◽  
pp. 325-331
Author(s):  
Charlene H. Chu ◽  
Amanda My Linh Quan ◽  
Katherine S. McGilton
Keyword(s):  
Cohort Study ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Long Term Care ◽  
Care Home ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Term Care ◽  
Minute Walk

Objective  Assess the association between depression among new long-term care residents (<3 months stay) with dementia and functional mobility decline.  Methods  A multi-site prospective cohort study was carried out among 26 participants diagnosed with dementia. Functional mobility was measured by Timed-Up-and-Go (TUG) and 2-Minute walk test (2MWT) at baseline, and 60-day post-baseline while participants received usual care. Linear mixed models were applied to examine the association between depression and functional mobility decline.  Results  Residents experienced a statistically significant decline in functional mobility in as soon as 60 days. Each additional year of age was associated with a 2% increase in TUG. The interaction between depression and time spent in LTC was statistically significant. Age and time living in LTC were significantly associated with functional mobility decline in new residents with dementia.  Discussion  Further work determining why residents with dementia experience decline in functional mobility at an accelerated rate is needed. 

scholarly journals Impact of a public policy restricting staff mobility between long-term care homes in Ontario, Canada during the COVID-19 pandemic

2020 ◽  
Author(s):  
Aaron Jones ◽  
Alexander G. Watts ◽  
Salah Uddin Khan ◽  
Jack Forsyth ◽  
Kevin A. Brown ◽  
...  
Keyword(s):  
Public Policy ◽  
Long Term Care ◽  
Care Home ◽  
Relative Difference ◽  
Care Staff ◽  
Care Homes ◽  
Term Care ◽  
Undirected Network ◽  
Before And After

AbstractObjectivesTo assess changes in the mobility of staff between long-term care homes in Ontario, Canada before and after enactment of public policy restricting staff from working at multiple homes.DesignPre-post observational study.Setting and Participants623 long-term cares homes in Ontario, Canada between March 2020 and June 2020.MethodsWe used anonymized mobile device location data to approximate connectivity between all 623 long-term care homes in Ontario during the 7 weeks before (March 1 – April 21) and after (April 22 – June 13) the policy restricting staff movement was implemented. We visualized connectivity between long-term care homes in Ontario using an undirected network and calculated the number of homes that had a connection with another long-term care home and the average number of connections per home in each period. We calculated the relative difference in these mobility metrics between the two time periods and compared within-home changes using McNemar’s test and the Wilcoxon rank-sum test.ResultsIn the period preceding restrictions, 266 (42.7%) long-term care homes had a connection with at least one other home, compared to 79 (12.7%) homes during the period after restrictions, a drop of 70.3% (p <0.001). The average number of connections in the before period was 3.90 compared to 0.77 in after period, a drop of 80.3% (p < 0.001). In both periods, mobility between long-term care homes was higher in homes located in larger communities, those with higher bed counts, and those part of a large chain.Conclusions and ImplicationsMobility between long-term care homes in Ontario fell sharply after an emergency order by the Ontario government limiting long-term care staff to a single home, though some mobility persisted. Reducing this residual mobility should be a focus of efforts to reduce risk within the long-term care sector during the COVID-19 pandemic.

How Often, Where, and by Which Specialty Do Long-Term Care Home Residents Receive Specialist Physician Care? A Retrospective Cohort Study

2020 ◽  
pp. 073346481990125
Author(s):  
Nicole S. Shaver ◽  
Julie Lapenskie ◽  
Glenys A. Smith ◽  
Amy T. Hsu ◽  
Clare Liddy ◽  
...  
Keyword(s):  
Cohort Study ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Long Term Care ◽  
Care Home ◽  
Specialist Care ◽  
Term Care ◽  
Physician Visits ◽  
Specialist Physician

This retrospective cohort study describes the rates, location, and determinants of specialist physician visits among 257,216 long-term care (LTC) residents across 648 LTC homes in Ontario, Canada, between 2007 and 2016. Visit rates in the last year of life were calculated for a sub-cohort of residents who died in LTC between 2013 and 2016. Visits were measured per resident-year using physician billings. Over 10 years, the rate of visits to specialists outside the LTC home was consistently higher than within LTC (2.99 vs. 1.55 visits/resident-year). Residents were less likely to receive specialist care if they were older, had dementia, or lived in urban LTC homes. From 12 months before death to the last week of life, rates of specialist visits increased by 246% and 56% inside and outside of LTC, respectively. Improving access to physician specialist care in LTC homes may reduce burdensome transitions and improve resident quality of life.

Implementation of eHealth to support assessment and decision-making for residents with dementia in long-term care: systematic review (Preprint)

2021 ◽  
Author(s):  
Juliet Gillam ◽  
Nathan Davies ◽  
Jesutofunmi Aworinde ◽  
Emel Yorganci ◽  
Janet E Anderson ◽  
...  
Keyword(s):  
Decision Making ◽  
Long Term Care ◽  
Care Home ◽  
End Users ◽  
Care Homes ◽  
Successful Implementation ◽  
Key Factors ◽  
Term Care ◽  
Care Assessment

BACKGROUND As dementia progresses, symptoms and concerns increase causing considerable distress for the person and caregivers. Integration of care between care homes and healthcare services is vital to meet increasing care needs and maintain quality of life. However, access to high-quality healthcare is inequitable. eHealth offers a potential solution, by supporting remote specialist input on care processes like clinical assessment and decision-making, and streamlining care on site. How best to implement eHealth in the care home setting is unclear. OBJECTIVE This review aimed to identify key factors that influence implementation of eHealth for people living with dementia in long-term care. METHODS A systematic search of EMBASE, PsychInfo, MEDLINE and CINHAL was conducted to identify studies published between 2000-2020. Studies were eligible if they focused on eHealth interventions to improve treatment and care assessment or decision-making for residents with dementia in care homes. Data were thematically analysed and deductively mapped onto the six constructs of the adapted Consolidated Framework for Implementation Research (CFIR). Results are presented as a narrative synthesis. RESULTS 29 studies were included, focusing on a variety of eHealth interventions including remote video-consultations and clinical decision support tools. Key factors which influenced eHealth implementation were identified across all six constructs of the CFIR. Most concerned the Inner Setting construct about requirements for implementation in the care home, such as providing a conducive learning climate, engaged leadership and sufficient training and resources. Four novel subconstructs were identified to inform implementation requirements to meet resident needs and engage end-users. CONCLUSIONS Implementing eHealth in care homes for people with dementia is multi-factorial and complex, involving interaction between the resident, staff and organisation. Application of the CFIR for care homes requires an emphasis on the needs of residents and the engagement of end users in the implementation process. A novel conceptual model of the key factors was developed, and translated into 18 practical recommendations on implementation of eHealth in long-term care to guide implementers or innovators in care homes. The policy imperative for integrated health and social care demands successful implementation of eHealth, to maximise uptake and drive improvements.

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