Identifying Dysphagia and Demographic Associations in Older Adults Using Electronic Health Records: A National Longitudinal Observational Study in Wales (United Kingdom) 2008–2018

Dysphagia is increasingly being recognised as a geriatric syndrome (giant). There is limited research on the prevalence of dysphagia using electronic health records. To investigate associations between dysphagia, as recorded in electronic health records and age, frailty using the electronic frailty index, gender and deprivation (Welsh index of multiple deprivation). A Cross-sectional longitudinal cohort study in over 400,000 older adults was undertaken (65 +) in Wales (United Kingdom) per year from 2008 to 2018. We used the secure anonymised information linkage databank to identify dysphagia diagnoses in primary and secondary care. We used chi-squared tests and multivariate logistic regression to investigate associations between dysphagia diagnosis and age, frailty (using the electronic Frailty index), gender and deprivation. Data indicated < 1% of individuals were recorded as having a dysphagia diagnosis per year. We found dysphagia to be statistically significantly associated with older age, more severe frailty and individuals from more deprived areas. Multivariate analyses indicated increased odds ratios [OR (95% confidence intervals)] for a dysphagia diagnosis with increased age [reference 65–74: aged 75–84 OR 1.09 (1.07, 1.12), 85 + OR 1.23 (1.20, 1.27)], frailty (reference fit: mild frailty 2.45 (2.38, 2.53), moderate frailty 4.64 (4.49, 4.79) and severe frailty 7.87 (7.55, 8.21)] and individuals from most deprived areas [reference 5. Least deprived, 1. Most deprived: 1.10 (1.06, 1.14)]. The study has identified that prevalence of diagnosed dysphagia is lower than previously reported. This study has confirmed the association of dysphagia with increasing age and frailty. A previously unreported association with deprivation has been identified. Deprivation is a multifactorial problem that is known to affect health outcomes, and the association with dysphagia should not be a surprise. Research in to this relationship is indicated

Annual risk of falls resulting in emergency department and hospital attendances for older people: an observational study of 781,081 individuals living in Wales (United Kingdom) including deprivation, frailty and dementia diagnoses between 2010 and 2020

Backgroundfalls are common in older people, but associations between falls, dementia and frailty are relatively unknown. The impact of the COVID-19 pandemic on falls admissions has not been studied.Aimto investigate the impact of dementia, frailty, deprivation, previous falls and the differences between years for falls resulting in an emergency department (ED) or hospital admission.Study Designlongitudinal cross-sectional observational study.Settingolder people (aged 65+) resident in Wales between 1 January 2010 and 31 December 2020.Methodswe created a binary (yes/no) indicator for a fall resulting in an attendance to an ED, hospital or both, per person, per year. We analysed the outcomes using multilevel logistic and multinomial models.Resultswe analysed a total of 5,141,244 person years of data from 781,081 individuals. Fall admission rates were highest in 2012 (4.27%) and lowest in 2020 (4.27%). We found an increased odds ratio (OR [95% confidence interval]) of a fall admission for age (1.05 [1.05, 1.05] per year of age), people with dementia (2.03 [2.00, 2.06]) and people who had a previous fall (2.55 [2.51, 2.60]). Compared with fit individuals, those with frailty had ORs of 1.60 [1.58, 1.62], 2.24 [2.21, 2.28] and 2.94 [2.89, 3.00] for mild, moderate and severe frailty respectively. Reduced odds were observed for males (0.73 [0.73, 0.74]) and less deprived areas; most deprived compared with least OR 0.75 [0.74, 0.76].Conclusionsfalls prevention should be targeted to those at highest risk, and investigations into the reduction in admissions in 2020 is warranted

Prevalence and outcomes of atrial fibrillation in older people living in care homes in Wales: a routine data linkage study 2003–2018

ObjectiveTo determine atrial fibrillation (AF) prevalence and temporal trends, and examine associations between AF and risk of adverse health outcomes in older care home residents.MethodsRetrospective cohort study using anonymised linked data from the Secure Anonymised Information Linkage Databank on CARE home residents in Wales with AF (SAIL CARE-AF) between 2003 and 2018. Fine-Gray competing risk models were used to estimate the risk of health outcomes with mortality as a competing risk. Cox regression analyses were used to estimate the risk of mortality.ResultsThere were 86,602 older care home residents (median age 86.0 years [interquartile range 80.8–90.6]) who entered a care home between 2003 and 2018. When the pre-care home entry data extraction was standardised, the overall prevalence of AF was 17.4% (95% confidence interval 17.1–17.8) between 2010 and 2018. There was no significant change in the age- and sex-standardised prevalence of AF from 16.8% (15.9–17.9) in 2010 to 17.0% (16.1–18.0) in 2018. Residents with AF had a significantly higher risk of cardiovascular mortality (adjusted hazard ratio [HR] 1.27 [1.17–1.37], P < 0.001), all-cause mortality (adjusted HR 1.14 [1.11–1.17], P < 0.001), ischaemic stroke (adjusted sub-distribution HR 1.55 [1.36–1.76], P < 0.001) and cardiovascular hospitalisation (adjusted sub-distribution HR 1.28 [1.22–1.34], P < 0.001).ConclusionsOlder care home residents with AF have an increased risk of adverse health outcomes, even when higher mortality rates and other confounders are accounted for. This re-iterates the need for appropriate oral anticoagulant prescription and optimal management of cardiovascular co-morbidities, irrespective of frailty status and predicted life expectancy

How does the environment in and around the home impact social care and health outcomes for older people?

Reducing the burden of falls and fall-related admissions to hospital and care homes is an important policy area. Falls cause significant injury leading to a reduced quality of life. We wanted to know if the environment around people’s homes changes the risk of falls for older people in Wales. We linked routinely collected, anonymised health data on frailty, dementia, hospital admissions, care home admission, and A&E attendance in the Secure Anonymised Information Linkage Databank. We also linked individual level demographic data and household level neighbourhood walkability and accessibility metrics detailing the built environment (e.g. access to services, greenspace). We capture change in the built environment and house moves between January 2010 and December 2017. Using unadjusted and adjusted cox regression models we will assess how the risk and severity of a fall changes in relation to the built environment. We have created a dynamic national e-cohort linking data on frailty, dementia, hospital admissions, care home admission, A&E attendance and built environment measures for people living in Wales aged 60 and above between January 2010 and December 2017. At the conference we will report summary statistics for each quarter as well as the overall population. We will also report unadjusted cox model odds ratios, as well as fully adjusted models. We will adjust for age, sex, urbanicity (urban/rural), deprivation (WIMD), dementia diagnosis, and seasonal weather trends. We will also report odds ratios for our stratification analysis where we will investigate whether associations vary by urbanicity and deprivation. With an aging population, it is becoming more important to help the current and future older population age healthily, preventing adverse health outcomes before they happen. This research will help guide policy and resource allocation to support people staying at home and have a more fulfilling life for longer

The impact of dementia, frailty and care home characteristics on SARS-CoV-2 incidence in a national cohort of Welsh care home residents during a period of high community prevalence

Backgrounddementia may increase care home residents’ risk of COVID-19, but there is a lack of evidence on this effect and on interactions with individual and care home-level factors.Methodswe created a national cross-sectional retrospective cohort of care home residents in Wales for 1 September to 31 December 2020. Risk factors were analysed using multi-level logistic regression to model the likelihood of SARS-CoV-2 infection and mortality.Resultsthe cohort included 9,571 individuals in 673 homes. Dementia was diagnosed in 5,647 individuals (59%); 1,488 (15.5%) individuals tested positive for SARS-CoV-2. We estimated the effects of age, dementia, frailty, care home size, proportion of residents with dementia, nursing and dementia services, communal space and region. The final model included the proportion of residents with dementia (OR for positive test 4.54 (95% CIs 1.55–13.27) where 75% of residents had dementia compared to no residents with dementia) and frailty (OR 1.29 (95% CIs 1.05–1.59) for severe frailty compared with no frailty). Analysis suggested 76% of the variation was due to setting rather than individual factors. Additional analysis suggested severe frailty and proportion of residents with dementia was associated with all-cause mortality, as was dementia diagnosis. Mortality analyses were challenging to interpret.Discussionwhilst individual frailty increased the risk of COVID-19 infection, dementia was a risk factor at care home but not individual level. These findings suggest whole-setting interventions, particularly in homes with high proportions of residents with dementia and including those with low/no individual risk factors may reduce the impact of COVID-19

Using Residential Anonymous Linking Fields to Identify Vulnerable Populations in Administrative Data

Introduction Demographic profiling is an important aspect of anonymised healthcare research to identify the population of interest. Typically, administrative data is used in conjunction with patient registers to create cohorts, but it can be a time consuming process. We describe a method using routinely collected health data to identify vulnerable populations. Objectives and Approach Using existing longitudinal data and the Residential Anonymised Linking Field (RALF) we aim to identify institutions linked to vulnerable populations. We search for specific characteristics of these institutions including the age of occupants, number of current residents, and rate of change of occupants. We also aim to compare our method to a pseudonymised national registry for care homes to ensure it is accurate. This can effectively reduce the need for repeat pseudonymisation of institutions, which is both expensive and time consuming. Results To implement our method we found the most recent address for living individuals aged 65-95. This produced 202,640 residences from 1,330,335. Of the 202,640 residences, 1347 had four or more cohabitants aged 65-95, and 172 had exactly three residents with ten or more distinct individuals registered over a 10-year period. Our final synthetic dataset therefore had 1519 unique potential care homes to compare to the national registry, which contains 1525 registered care homes. We can now link the synthetic dataset to individuals to flag their residential status, which may be a defining factor in their level of care. Furthermore, we can answer specific research questions relating to their residency, such as the time it takes to move to a care home following a hospital admission. Conclusion/Implications By using quantifiable characteristics of care homes we were able to create a synthetic care home register by searching existing data. This is a reproducible process that would be of particular benefit for projects where a registry is not available, or where time or cost would limit the availability