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Objective: People with epilepsy (PWE) may be at an increased risk of severe COVID-19. It is important to characterize this risk to inform PWE and for future health and care planning. We assessed whether PWE were at higher risk of being hospitalized with, or dying from, COVID-19., Methods: We performed a retrospective cohort study using linked, population-scale, anonymized electronic health records from the SAIL (Secure Anonymised Information Linkage) databank. This includes hospital admission and demographic data for the complete Welsh population (3.1 million) and primary care records for 86% of the population. We identified 27 279 PWE living in Wales during the study period (March 1, 2020 to June 30, 2021). Controls were identified using exact 5:1 matching (sex, age, and socioeconomic status). We defined COVID-19 deaths as having International Classification of Diseases, 10th Revision (ICD-10) codes for COVID-19 on death certificates or occurring within 28 days of a positive SARS-CoV-2 polymerase chain reaction (PCR) test. COVID-19 hospitalizations were defined as having a COVID-19 ICD-10 code for the reason for admission or occurring within 28 days of a positive SARS-CoV-2 PCR test. We recorded COVID-19 vaccinations and comorbidities known to increase the risk of COVID-19 hospitalization and death. We used Cox proportional hazard models to calculate hazard ratios., Results: There were 158 (.58%) COVID-19 deaths and 933 (3.4%) COVID-19 hospitalizations in PWE, and 370 (.27%) deaths and 1871 (1.4%) hospitalizations in controls. Hazard ratios for COVID-19 death and hospitalization in PWE compared to controls were 2.15 (95% confidence interval [CI] = 1.78-2.59) and 2.15 (95% CI = 1.94-2.37), respectively. Adjusted hazard ratios (adjusted for comorbidities) for death and hospitalization were 1.32 (95% CI = 1.08-1.62) and 1.60 (95% CI = 1.44-1.78)., Significance: PWE are at increased risk of being hospitalized with, and dying from, COVID-19 when compared to age-, sex-, and deprivation-matched controls, even when adjusting for comorbidities. This may have implications for prioritizing future COVID-19 treatments and vaccinations for PWE., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

Objective: This study was undertaken to characterize changes in health care utilization and mortality for people with epilepsy (PWE) during the COVID-19 pandemic., Methods: We performed a retrospective study using linked, individual-level, population-scale anonymized health data from the Secure Anonymised Information Linkage databank. We identified PWE living in Wales during the study "pandemic period" (January 1, 2020-June 30, 2021) and during a "prepandemic" period (January 1, 2016-December 31, 2019). We compared prepandemic health care utilization, status epilepticus, and mortality rates with corresponding pandemic rates for PWE and people without epilepsy (PWOE). We performed subgroup analyses on children (<18 years old), older people (>65 years old), those with intellectual disability, and those living in the most deprived areas. We used Poisson models to calculate adjusted rate ratios (RRs)., Results: We identified 27 279 PWE who had significantly higher rates of hospital (50.3 visits/1000 patient months), emergency department (55.7), and outpatient attendance (172.4) when compared to PWOE (corresponding figures: 25.7, 25.2, and 87.0) in the prepandemic period. Hospital and epilepsy-related hospital admissions, and emergency department and outpatient attendances all reduced significantly for PWE (and all subgroups) during the pandemic period. RRs [95% confidence intervals (CIs)] for pandemic versus prepandemic periods were .70 [.69-.72], .77 [.73-.81], .78 [.77-.79], and .80 [.79-.81]. The corresponding rates also reduced for PWOE. New epilepsy diagnosis rates decreased during the pandemic compared with the prepandemic period (2.3/100 000/month cf. 3.1/100 000/month, RR = .73, 95% CI = .68-.78). Both all-cause deaths and deaths with epilepsy recorded on the death certificate increased for PWE during the pandemic (RR = 1.07, 95% CI = .997-1.145 and RR = 2.44, 95% CI = 2.12-2.81). When removing COVID deaths, RRs were .88 (95% CI = .81-.95) and 1.29 (95% CI = 1.08-1.53). Status epilepticus rates did not change significantly during the pandemic (RR = .95, 95% CI = .78-1.15)., Significance: All-cause non-COVID deaths did not increase but non-COVID deaths associated with epilepsy did increase for PWE during the COVID-19 pandemic. The longer term effects of the decrease in new epilepsy diagnoses and health care utilization and increase in deaths associated with epilepsy need further research., (© 2024 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.)

There are national and global moves to improve effective digital data design and application in healthcare. This New Horizons commentary describes the role of digital data in healthcare of the ageing population. We outline how health and social care professionals can engage in the proactive design of digital systems that appropriately serve people as they age, carers and the workforce that supports them., Key Points: Healthcare improvements have resulted in increased population longevity and hence multimorbidity. Shared care records to improve communication and information continuity across care settings hold potential for older people. Data structure and coding are key considerations. A workforce with expertise in caring for older people with relevant knowledge and skills in digital healthcare is important., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: it is not known if clinical practice reflects guideline recommendations for the management of hypertension in older people and whether guideline adherence varies according to overall health status., Aims: to describe the proportion of older people attaining National Institute for Health and Care Excellence (NICE) guideline blood pressure targets within 1 year of hypertension diagnosis and determine predictors of target attainment., Methods: a nationwide cohort study of Welsh primary care data from the Secure Anonymised Information Linkage databank including patients aged ≥65 years newly diagnosed with hypertension between 1st June 2011 and 1st June 2016. The primary outcome was attainment of NICE guideline blood pressure targets as measured by the latest blood pressure recording up to 1 year after diagnosis. Predictors of target attainment were investigated using logistic regression., Results: there were 26,392 patients (55% women, median age 71 [IQR 68-77] years) included, of which 13,939 (52.8%) attained a target blood pressure within a median follow-up of 9 months. Success in attaining target blood pressure was associated with a history of atrial fibrillation (OR 1.26, 95% CI 1.11, 1.43), heart failure (OR 1.25, 95% CI 1.06, 1.49) and myocardial infarction (OR 1.20, 95% CI 1.10, 1.32), all compared to no history of each, respectively. Care home residence, the severity of frailty, and increasing co-morbidity were not associated with target attainment following adjustment for confounder variables., Conclusions: blood pressure remains insufficiently controlled 1 year after diagnosis in nearly half of older people with newly diagnosed hypertension, but target attainment appears unrelated to baseline frailty, multi-morbidity or care home residence., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: Treatment decisions about oral anticoagulants (OACs) for atrial fibrillation (AF) are complex in older care home residents., Aim: To explore factors associated with OAC prescription., Design and Setting: Retrospective cohort study set in care homes in Wales, UK, listed in the Care Inspectorate Wales Registry 2017/18., Method: Analysis of anonymised individual-level electronic health and administrative data was carried out on people aged ≥65 years entering a care home between 1 January 2003 and 31 December 2018, provisioned from the Secure Anonymised Information Linkage Databank., Results: Between 2003 and 2018, 14 493 people with AF aged ≥65 years became new residents in care homes in Wales and 7057 (48.7%) were prescribed OACs (32.7% in 2003 compared with 72.7% in 2018) within 6 months before care home entry. Increasing age and prescription of antiplatelet therapy were associated with lower odds of OAC prescription (adjusted odds ratio [aOR] 0.96 per 1-year age increase, 95% confidence interval [CI] = 0.95 to 0.96 and aOR 0.91, 95% CI = 0.84 to 0.98, respectively). Conversely, prior venous thromboembolism (aOR 4.06, 95% CI = 3.17 to 5.20), advancing frailty (mild: aOR 4.61, 95% CI = 3.95 to 5.38; moderate: aOR 6.69, 95% CI = 5.74 to 7.80; and severe: aOR 8.42, 95% CI = 7.16 to 9.90), and year of care home entry from 2011 onwards (aOR 1.91, 95% CI = 1.76 to 2.06) were associated with higher odds of an OAC prescription., Conclusion: There has been an increase in OAC prescribing in older people newly admitted to care homes with AF. This study provides an insight into the factors influencing OAC prescribing in this population., (© The Authors.)

Background: dementia 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., Methods: we 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., Results: the 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., Discussion: whilst 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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: To determine atrial fibrillation (AF) prevalence and temporal trends, and examine associations between AF and risk of adverse health outcomes in older care home residents., Methods: Retrospective 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., Results: There 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)., Conclusions: Older 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., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society.)

There is a need for better understanding of the risk of thrombocytopenic, haemorrhagic, thromboembolic disorders following first, second and booster vaccination doses and testing positive for SARS-CoV-2. Self-controlled cases series analysis of 2.1 million linked patient records in Wales between 7th December 2020 and 31st December 2021. Outcomes were the first diagnosis of thrombocytopenic, haemorrhagic and thromboembolic events in primary or secondary care datasets, exposure was defined as 0-28 days post-vaccination or a positive reverse transcription polymerase chain reaction test for SARS-CoV-2. 36,136 individuals experienced either a thrombocytopenic, haemorrhagic or thromboembolic event during the study period. Relative to baseline, our observations show greater risk of outcomes in the periods post-first dose of BNT162b2 for haemorrhagic (IRR 1.47, 95%CI: 1.04-2.08) and idiopathic thrombocytopenic purpura (IRR 2.80, 95%CI: 1.21-6.49) events; post-second dose of ChAdOx1 for arterial thrombosis (IRR 1.14, 95%CI: 1.01-1.29); post-booster greater risk of venous thromboembolic (VTE) (IRR-Moderna 3.62, 95%CI: 0.99-13.17) (IRR-BNT162b2 1.39, 95%CI: 1.04-1.87) and arterial thrombosis (IRR-Moderna 3.14, 95%CI: 1.14-8.64) (IRR-BNT162b2 1.34, 95%CI: 1.15-1.58). Similarly, post SARS-CoV-2 infection the risk was increased for haemorrhagic (IRR 1.49, 95%CI: 1.15-1.92), VTE (IRR 5.63, 95%CI: 4.91, 6.4), arterial thrombosis (IRR 2.46, 95%CI: 2.22-2.71). We found that there was a measurable risk of thrombocytopenic, haemorrhagic, thromboembolic events after COVID-19 vaccination and infection., (© 2022. The Author(s).)

Background: falls 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., Aim: to 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 Design: longitudinal cross-sectional observational study., Setting: older people (aged 65+) resident in Wales between 1 January 2010 and 31 December 2020., Methods: we 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., Results: we 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]., Conclusions: falls prevention should be targeted to those at highest risk, and investigations into the reduction in admissions in 2020 is warranted., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Introduction: Critical Care is a specialty in medicine providing a service for severely ill and high-risk patients who, due to the nature of their condition, may require long periods recovering after discharge. Consequently, focus on the routine data collection carried out in Intensive Care Units (ICUs) leads to reporting that is confined to the critical care episode and is typically insensitive to variation in individual patient pathways through critical care to recovery.A resource which facilitates efficient research into interactions with healthcare services surrounding critical admissions, capturing the complete patient's healthcare trajectory from primary care to non-acute hospital care prior to ICU, would provide an important longer-term perspective for critical care research., Objective: To describe and apply a reproducible methodology that demonstrates how both routine administrative and clinically rich critical care data sources can be integrated with primary and secondary healthcare data to create a single dataset that captures a broader view of patient care., Method: To demonstrate the INTEGRATE methodology, it was applied to routine administrative and clinical healthcare data sources in the Secure Anonymised Data Linking (SAIL) Databank to create a dataset of patients' complete healthcare trajectory prior to critical care admission. SAIL is a national, data safe haven of anonymised linkable datasets about the population of Wales., Results: When applying the INTEGRATE methodology in SAIL, between 2010 and 2019 we observed 91,582 critical admissions for 76,019 patients. Of these, 90,632 (99%) had an associated non-acute hospital admission, 48,979 (53%) had an emergency admission, and 64,832 (71%) a primary care interaction in the week prior to the critical care admission., Conclusion: This methodology, at population scale, integrates two critical care data sources into a single dataset together with data sources on healthcare prior to critical admission, thus providing a key research asset to study critical care pathways., Competing Interests: Statement on conflicts of interest: The authors declare they have no conflicts of interest.

Background: COVID-19 vaccinations have been prioritised for high risk individuals., Aim: 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 from the Secure Anonymised Information Linkage (SAIL) databank., Setting: Fourteen thousand seven hundred and eighty-six older care home residents (aged 65+) living in Wales between 1 September 2020 and 1 May 2021. 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 PCR test. We included time-dependent covariates for the estimated community positive test rate of COVID-19, hospital inpatient status, vaccination status and frailty. Additional covariates were included for age, sex and specialist care home services., Results: The multivariable regression model indicated an increase in age (OR 1.01 [1.00,1.01] per year), community positive test rate (OR 1.13 [1.12,1.13] per percent increase), 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., Conclusions: Care providers need to remain vigilant despite the vaccination rollout, and extra precautions should be taken when caring for the most vulnerable. Minimising potential COVID-19 infection for care home residents when admitted to hospital should be prioritised., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Background: defining features of the COVID-19 pandemic in many countries were the tragic extent to which care home residents were affected and the difficulty in preventing the introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was the transfer of patients from hospitals that were experiencing high levels of nosocomial events., Methods: we tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period from March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in case rates following exposure to a hospital discharge using multi-level hierarchical logistic regression and a novel stochastic Hawkes process outbreak model., Findings: in regression analysis, after adjusting for care home size, we found no significant association between hospital discharge and subsequent increases in care home case numbers (odds ratio: 0.99, 95% CI: 0.82, 1.90). Risk factors for increased cases included care home size, care home resident density and provision of nursing care. Using our outbreak model, we found a significant effect of hospital discharge on the subsequent intensity of cases. However, the effect was small and considerably less than the effect of care home size, suggesting the highest risk of introduction came from interaction with the community. We estimated that approximately 1.8% of hospital discharged patients may have been infected., Interpretation: there is growing evidence in the UK that the risk of transfer of COVID-19 from the high-risk hospital setting to the high-risk care home setting during the early stages of the pandemic was relatively small. Although access to testing was limited to initial symptomatic cases in each care home at this time, our results suggest that reduced numbers of discharges, selection of patients and action taken within care homes following transfer all may have contributed to the mitigation. The precise key transmission routes from the community remain to be quantified., (© The Author(s) 2022. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Introduction: School-based COVID-19 mitigation strategies have greatly impacted the primary school day (children aged 3-11) including: wearing face coverings, two metre distancing, no mixing of children, and no breakfast clubs or extra-curricular activities. This study examines these mitigation measures and association with COVID-19 infection, respiratory infection, and school staff wellbeing between October to December 2020 in Wales, UK., Methods: A school staff survey captured self-reported COVID-19 mitigation measures in the school, participant anxiety and depression, and open-text responses regarding experiences of teaching and implementing measures. These survey responses were linked to national-scale COVID-19 test results data to examine association of measures in the school and the likelihood of a positive (staff or pupil) COVID-19 case in the school (clustered by school, adjusted for school size and free school meals using logistic regression). Linkage was conducted through the SAIL (Secure Anonymised Information Linkage) Databank., Results: Responses were obtained from 353 participants from 59 primary schools within 15 of 22 local authorities. Having more direct non-household contacts was associated with a higher likelihood of COVID-19 positive case in the school (1-5 contacts compared to none, OR 2.89 (1.01, 8.31)) and a trend to more self-reported cold symptoms. Staff face covering was not associated with a lower odds of school COVID-19 cases (mask vs. no covering OR 2.82 (1.11, 7.14)) and was associated with higher self-reported cold symptoms. School staff reported the impacts of wearing face coverings on teaching, including having to stand closer to pupils and raise their voices to be heard. 67.1% were not able to implement two metre social distancing from pupils. We did not find evidence that maintaining a two metre distance was associated with lower rates of COVID-19 in the school., Conclusions: Implementing, adhering to and evaluating COVID-19 mitigation guidelines is challenging in primary school settings. Our findings suggest that reducing non-household direct contacts lowers infection rates. There was no evidence that face coverings, two metre social distancing or stopping children mixing was associated with lower odds of COVID-19 or cold infection rates in the school. Primary school staff found teaching challenging during COVID-19 restrictions, especially for younger learners and those with additional learning needs., Competing Interests: The authors declare there are no competing interests.

Introduction: COVID-19 risk prediction algorithms can be used to identify at-risk individuals from short-term serious adverse COVID-19 outcomes such as hospitalisation and death. It is important to validate these algorithms in different and diverse populations to help guide risk management decisions and target vaccination and treatment programs to the most vulnerable individuals in society., Objectives: To validate externally the QCOVID risk prediction algorithm that predicts mortality outcomes from COVID-19 in the adult population of Wales, UK., Methods: We conducted a retrospective cohort study using routinely collected individual-level data held in the Secure Anonymised Information Linkage (SAIL) Databank. The cohort included individuals aged between 19 and 100 years, living in Wales on 24 th January 2020, registered with a SAIL-providing general practice, and followed-up to death or study end (28 th July 2020). Demographic, primary and secondary healthcare, and dispensing data were used to derive all the predictor variables used to develop the published QCOVID algorithm. Mortality data were used to define time to confirmed or suspected COVID-19 death. Performance metrics, including R 2 values (explained variation), Brier scores, and measures of discrimination and calibration were calculated for two periods (24 th January-30 th April 2020 and 1 st May-28 th July 2020) to assess algorithm performance., Results: 1,956,760 individuals were included. 1,192 (0.06%) and 610 (0.03%) COVID-19 deaths occurred in the first and second time periods, respectively. The algorithms fitted the Welsh data and population well, explaining 68.8% (95% CI: 66.9-70.4) of the variation in time to death, Harrell's C statistic: 0.929 (95% CI: 0.921-0.937) and D statistic: 3.036 (95% CI: 2.913-3.159) for males in the first period. Similar results were found for females and in the second time period for both sexes., Conclusions: The QCOVID algorithm developed in England can be used for public health risk management for the adult Welsh population., Competing Interests: Conflicts of interest: AS is a member of the Scottish Government’s COVID-19 Chief Medical Officer’s Advisory Group and its Standing Committee on Pandemics; he is also a member of NERVTAG’s Risk Stratification Subgroup. KK is member of NERVTAG subgroup and member of the Scientific Advisory Group for Emergencies (SAGE). JHC reports grants from National Institute for Health Research (NIHR) Biomedical Research Centre, Oxford, grants from John Fell Oxford University Press Research Fund, grants from Cancer Research UK (CR-UK) grant number C5255/A18085, through the Cancer Research UK Oxford Centre, grants from the Oxford Wellcome Institutional Strategic Support Fund (204826/Z/16/Z) and other research councils, during the conduct of the study. JHC is an unpaid director of QResearch, a not-for-profit organisation which is a partnership between the University of Oxford and EMIS Health who supply the QResearch database used for this work. JHC is a founder and shareholder of ClinRisk ltd and was its medical director until 31st May 2019. ClinRisk Ltd produces open and closed source software to implement clinical risk algorithms (outside this work) into clinical computer systems. JHC is chair of the NERVTAG risk stratification subgroup and a member of SAGE COVID-19 groups and the NHS group advising on prioritisation of use of monoclonal antibodies in COVID-19 infection. RAL is a member of the Welsh Government COVID-19 Technical Advisory Group.

Background: vaccinations for COVID-19 have been prioritised for older people living in care homes. However, vaccination trials included limited numbers of older people., Aim: we aimed to study infection rates of SARS-CoV-2 for older care home residents following vaccination and identify factors associated with increased risk of infection., Study Design and Setting: we conducted an observational data-linkage study including 14,104 vaccinated older care home residents in Wales (UK) using anonymised electronic health records and administrative data., Methods: we used Cox proportional hazards models to estimate hazard ratios (HRs) for the risk of testing positive for SARS-CoV-2 infection following vaccination, after landmark times of either 7 or 21 days post-vaccination. We adjusted HRs for age, sex, frailty, prior SARS-CoV-2 infections and vaccination type., Results: we observed a small proportion of care home residents with positive polymerase chain reaction (tests following vaccination 1.05% (N = 148), with 90% of infections occurring within 28 days. For the 7-day landmark analysis we found a reduced risk of SARS-CoV-2 infection for vaccinated individuals who had a previous infection; HR (95% confidence interval) 0.54 (0.30, 0.95). For the 21-day landmark analysis, we observed high HRs for individuals with low and intermediate frailty compared with those without; 4.59 (1.23, 17.12) and 4.85 (1.68, 14.04), respectively., Conclusions: increased risk of infection after 21 days was associated with frailty. We found most infections occurred within 28 days of vaccination, suggesting extra precautions to reduce transmission risk should be taken in this time frame., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Background: falls are common in older people, but evidence for the effectiveness of preventative home adaptations is limited., Aim: determine whether a national home adaptation service, Care&Repair Cymru (C&RC), identified individuals at risk of falls occurring at home and reduced the likelihood of falls., Study Design: retrospective longitudinal controlled non-randomised intervention cohort study., Setting: our cohort consisted of 657,536 individuals aged 60+ living in Wales (UK) between 1 January 2010 and 31 December 2017. About 123,729 individuals received a home adaptation service., Methods: we created a dataset with up to 41 quarterly observations per person. For each quarter, we observed if a fall occurred at home that resulted in either an emergency department or an emergency hospital admission. We analysed the data using multilevel logistic regression., Results: compared to the control group, C&RC clients had higher odds of falling, with an odds ratio (OR [95% confidence interval]) of 1.93 [1.87, 2.00]. Falls odds was higher for females (1.44 [1.42, 1.46]), older age (1.07 [1.07, 1.07]), increased frailty (mild 1.57 [1.55, 1.60], moderate 2.31 [2.26, 2.35], severe 3.05 [2.96, 3.13]), and deprivation (most deprived compared to least: 1.16 [1.13, 1.19]). Client fall odds decreased post-intervention; OR 0.97 [0.96, 0.97] per quarter. Regional variation existed for falls (5.8%), with most variation at the individual level (31.3%)., Conclusions: C&RC identified people more likely to have an emergency fall admission occurring at home, and their service reduced the odds of falling post-intervention. Service provisioning should meet the needs of an individual and need varies by personal and regional circumstance., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Purpose: The COVID-19 pandemic has increased mortality worldwide and those with chronic conditions may have been disproportionally affected. However, it is unknown whether the pandemic has changed mortality rates for people with epilepsy. We aimed to compare mortality rates in people with epilepsy in Wales during the pandemic with pre-pandemic rates., Methods: We performed a retrospective study using individual-level linked population-scale anonymised electronic health records. We identified deaths in people with epilepsy (DPWE), i.e. those with a diagnosis of epilepsy, and deaths associated with epilepsy (DAE), where epilepsy was recorded as a cause of death on death certificates. We compared death rates in 2020 with average rates in 2015-2019 using Poisson models to calculate death rate ratios., Results: There were 188 DAE and 628 DPWE in Wales in 2020 (death rates: 7.7/100,000/year and 25.7/100,000/year). The average rates for DAE and DPWE from 2015 to 2019 were 5.8/100,000/year and 23.8/100,000/year, respectively. Death rate ratios (2020 compared to 2015-2019) for DAE were 1.34 (95%CI 1.14-1.57, p<0.001) and for DPWE were 1.08 (0.99-1.17, p = 0.09). The death rate ratios for non-COVID deaths (deaths without COVID mentioned on death certificates) for DAE were 1.17 (0.99-1.39, p = 0.06) and for DPWE were 0.96 (0.87-1.05, p = 0.37)., Conclusions: The significant increase in DAE in Wales during 2020 could be explained by the direct effect of COVID-19 infection. Non-COVID-19 deaths have not increased significantly but further work is needed to assess the longer-term impact., (Copyright © 2021. Published by Elsevier Ltd.)

Background: The electronic Frailty Index (eFI) has been developed in primary care settings. The Hospital Frailty Risk Score (HFRS) was derived using secondary care data., Objective: Compare the two different tools for identifying frailty in older people admitted to hospital., Design and Setting: Retrospective cohort study using the Secure Anonymised Information Linkage Databank, comprising 126,600 people aged 65+ who were admitted as an emergency to hospital in Wales from January 2013 up until December 2017., Methods: Pearson's correlation coefficient and weighted kappa were used to assess the correlation between the tools. Cox and logistic regression were used to estimate hazard ratios (HRs) and odds ratios (ORs). The Concordance statistic and area under the receiver operating curves (AUROC) were estimated to determine discrimination., Results: Pearson's correlation coefficient was 0.26 and the weighted kappa was 0.23. Comparing the highest to the least frail categories in the two scores the HRs for 90-day mortality, 90-day emergency readmission and care home admissions within 1-year using the HFRS were 1.41, 1.69 and 4.15 for the eFI 1.16, 1.63 and 1.47. Similarly, the ORs for inpatient death, length of stay greater than 10 days and readmission within 30-days were 1.44, 2.07 and 1.52 for the HFRS, and 1.21, 1.21 and 1.44 for the eFI. AUROC was determined as having no clinically relevant difference between the tools., Conclusions: The eFI and HFRS have a low correlation between their scores. The HRs and ORs were higher for the increasing frailty categories for both the HFRS and eFI., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

The ideal method of identifying frailty is uncertain, and data on long-term outcomes is relatively limited. We examined frailty indices derived from population-scale linked data on Intensive Care Unit (ICU) and hospitalised non-ICU patients with pneumonia to elucidate the influence of frailty on mortality. Longitudinal cohort study between 2010-2018 using population-scale anonymised data linkage of healthcare records for adults admitted to hospital with pneumonia in Wales. Primary outcome was in-patient mortality. Odds Ratios (ORs [95% confidence interval]) for age, hospital frailty risk score (HFRS), electronic frailty index (eFI), Charlson comorbidity index (CCI), and social deprivation index were estimated using multivariate logistic regression models. The area under the receiver operating characteristic curve (AUC) was estimated to determine the best fitting models. Of the 107,188 patients, mean (SD) age was 72.6 (16.6) years, 50% were men. The models adjusted for the two frailty indices and the comorbidity index had an increased odds of in-patient mortality for individuals with an ICU admission (ORs for ICU admission in the eFI model 2.67 [2.55, 2.79], HFRS model 2.30 [2.20, 2.41], CCI model 2.62 [2.51, 2.75]). Models indicated advancing age, increased frailty and comorbidity were also associated with an increased odds of in-patient mortality (eFI, baseline fit, ORs: mild 1.09 [1.04, 1.13], moderate 1.13 [1.08, 1.18], severe 1.17 [1.10, 1.23]. HFRS, baseline low, ORs: intermediate 2.65 [2.55, 2.75], high 3.31 [3.17, 3.45]). CCI, baseline < 1, ORs: '1-10' 1.15 [1.11, 1.20], > 10 2.50 [2.41, 2.60]). For predicting inpatient deaths, the CCI and HFRS based models were similar, however for longer term outcomes the CCI based model was superior. Frailty and comorbidity are significant risk factors for patients admitted to hospital with pneumonia. Frailty and comorbidity scores based on administrative data have only moderate ability to predict outcome.

Background: Better understanding of the role that children and school staff play in the transmission of SARS-CoV-2 is essential to guide policy development on controlling infection while minimising disruption to children's education and well-being., Methods: Our national e-cohort (n=464531) study used anonymised linked data for pupils, staff and associated households linked via educational settings in Wales. We estimated the odds of testing positive for SARS-CoV-2 infection for staff and pupils over the period August- December 2020, dependent on measures of recent exposure to known cases linked to their educational settings., Results: The total number of cases in a school was not associated with a subsequent increase in the odds of testing positive (staff OR per case: 0.92, 95% CI 0.85 to 1.00; pupil OR per case: 0.98, 95% CI 0.93 to 1.02). Among pupils, the number of recent cases within the same year group was significantly associated with subsequent increased odds of testing positive (OR per case: 1.12, 95% CI 1.08 to 1.15). These effects were adjusted for a range of demographic covariates, and in particular any known cases within the same household, which had the strongest association with testing positive (staff OR: 39.86, 95% CI 35.01 to 45.38; pupil OR: 9.39, 95% CI 8.94 to 9.88)., Conclusions: In a national school cohort, the odds of staff testing positive for SARS-CoV-2 infection were not significantly increased in the 14-day period after case detection in the school. However, pupils were found to be at increased odds, following cases appearing within their own year group, where most of their contacts occur. Strong mitigation measures over the whole of the study period may have reduced wider spread within the school environment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction The COVID-19 pandemic has highlighted the need for robust data linkage systems and methods for identifying outbreaks of disease in near real-time. Objectives The primary objective of this study was to develop a real-time geospatial surveillance system to monitor the spread of COVID-19 across the UK. Methods Using self-reported app data and the Secure Anonymised Information Linkage (SAIL) Databank, we demonstrate the use of sophisticated spatial modelling for near-real-time prediction of COVID-19 prevalence at small-area resolution to inform strategic government policy areas. Results We demonstrate that using a combination of crowd-sourced app data and sophisticated geo-statistical techniques it is possible to predict hot spots of COVID-19 at fine geographic scales, nationally. We are also able to produce estimates of their precision, which is an important pre-requisite to an effective control strategy to guard against over-reaction to potentially spurious features of 'best guess' predictions. Conclusion In the UK, important emerging risk-factors such as social deprivation or ethnicity vary over small distances, hence risk needs to be modelled at fine spatial resolution to avoid aggregation bias. We demonstrate that existing geospatial statistical methods originally developed for global health applications are well-suited to this task and can be used in an anonymised databank environment, thus preserving the privacy of the individuals who contribute their data., (Crown Copyright © 2021. Published by Elsevier B.V. All rights reserved.)

Background: Falls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base., Objective: The aim of this study is to conduct a systematic review of the evidence of the use of routinely collected data in the evaluations of HAM interventions., Methods: We searched the following databases from inception until January 31, 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were those evaluating HAMs designed to reduce falls involving participants aged 60 years or more. We included study protocols and full reports. Bias was assessed using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool., Results: A total of 7 eligible studies were identified in 8 papers. Government organizations provided the majority of data across studies, with health care providers and third-sector organizations also providing data. Studies used a range of demographic, clinical and health, and administrative data. The purpose of using routinely collected data spanned recruiting and creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes. Nonhome-based modification interventions (eg, in nursing homes) using routinely collected data were not included in this study. We included two protocols, which meant that the results of those studies were not available. MeSH headings were excluded from the PubMed search because of a reduction in specificity. This means that some studies that met the inclusion criteria may not have been identified., Conclusions: Routine data can be used successfully in many aspects of HAM evaluations and can reduce biases and improve other important design considerations. However, the use of these data in these studies is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential., (©Helen Daniels, Joe Hollinghurst, Richard Fry, Andrew Clegg, Sarah Hillcoat-Nallétamby, Silviya Nikolova, Sarah E Rodgers, Neil Williams, Ashley Akbari. Originally published in JMIR Aging (https://aging.jmir.org), 23.04.2021.)

Background: mortality in care homes has had a prominent focus during the COVID-19 outbreak. Care homes are particularly vulnerable to the spread of infectious diseases, which may lead to increased mortality risk. Multiple and interconnected challenges face the care home sector in the prevention and management of outbreaks of COVID-19, including adequate supply of personal protective equipment, staff shortages and insufficient or lack of timely COVID-19 testing., Aim: to analyse the mortality of older care home residents in Wales during COVID-19 lockdown and compare this across the population of Wales and the previous 4 years., Study Design and Setting: we used anonymised electronic health records and administrative data from the secure anonymised information linkage databank to create a cross-sectional cohort study. We anonymously linked data for Welsh residents to mortality data up to the 14th June 2020., Methods: we calculated survival curves and adjusted Cox proportional hazards models to estimate hazard ratios (HRs) for the risk of mortality. We adjusted HRs for age, gender, social economic status and prior health conditions., Results: survival curves show an increased proportion of deaths between 23rd March and 14th June 2020 in care homes for older people, with an adjusted HR of 1.72 (1.55, 1.90) compared with 2016. Compared with the general population in 2016-2019, adjusted care home mortality HRs for older adults rose from 2.15 (2.11, 2.20) in 2016-2019 to 2.94 (2.81, 3.08) in 2020., Conclusions: the survival curves and increased HRs show a significantly increased risk of death in the 2020 study periods., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Background: home advice and modification interventions aim to promote independent living for those living in the community, but quantitative evidence of their effectiveness is limited., Aim: assess the risk of care home admissions for people with different frailty levels receiving home advice and modification interventions against a control group who do not., Study Design and Setting: matched control evaluation using linked longitudinal data from the Secure Anonymised Information Linkage (SAIL) Databank, comprising people aged 60-95, registered with a SAIL contributing general practice. The intervention group received the Care & Repair Cymru (C & RC) service, a home advice and modification service available to residents in Wales., Methods: frailty, age and gender were used in propensity score matching to assess the Hazard Ratio (HR) of care home admissions within a 1-, 3- and 5-year period for the intervention group (N = 93,863) compared to a matched control group (N = 93,863). Kaplan-Meier curves were used to investigate time to a care home admission., Results: the intervention group had an increased risk of a care home admission at 1-, 3- and 5-years [HR (95%CI)] for those classified as fit [1-year: 2.02 (1.73, 2.36), 3-years: 1.87 (1.72, 2.04), 5-years: 1.99 (1.86, 2.13)] and mildly frail [1-year: 1.25 (1.09, 1.42), 3-years: 1.25 (1.17, 1.34), 5-years: 1.30 (1.23, 1.38)], but a reduced risk of care home admission for moderately [1-year: 0.66 (0.58, 0.75), 3-years: 0.75 (0.70, 0.80), 5-years: 0.83 (0.78, 0.88)] and severely frail individuals [1-year: 0.44 (0.37, 0.54), 3-years: 0.54 (0.49, 0.60), 5-years: 0.60(0.55, 0.66)]., Conclusions: HRs indicated that the C & RC service helped to prevent care home admissions for moderately and severely frail individuals. The HRs generally increased with follow-up duration., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Introduction: The emergence of the novel respiratory SARS-CoV-2 and subsequent COVID-19 pandemic have required rapid assimilation of population-level data to understand and control the spread of infection in the general and vulnerable populations. Rapid analyses are needed to inform policy development and target interventions to at-risk groups to prevent serious health outcomes. We aim to provide an accessible research platform to determine demographic, socioeconomic and clinical risk factors for infection, morbidity and mortality of COVID-19, to measure the impact of COVID-19 on healthcare utilisation and long-term health, and to enable the evaluation of natural experiments of policy interventions., Methods and Analysis: Two privacy-protecting population-level cohorts have been created and derived from multisourced demographic and healthcare data. The C20 cohort consists of 3.2 million people in Wales on the 1 January 2020 with follow-up until 31 May 2020. The complete cohort dataset will be updated monthly with some individual datasets available daily. The C16 cohort consists of 3 million people in Wales on the 1 January 2016 with follow-up to 31 December 2019. C16 is designed as a counterfactual cohort to provide contextual comparative population data on disease, health service utilisation and mortality. Study outcomes will: (a) characterise the epidemiology of COVID-19, (b) assess socioeconomic and demographic influences on infection and outcomes, (c) measure the impact of COVID-19 on short -term and longer-term population outcomes and (d) undertake studies on the transmission and spatial spread of infection., Ethics and Dissemination: The Secure Anonymised Information Linkage-independent Information Governance Review Panel has approved this study. The study findings will be presented to policy groups, public meetings, national and international conferences, and published in peer-reviewed journals., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)

The past three decades have seen a steady increase in the availability of routinely collected health and social care data and the processing power to analyse it. These developments represent a major opportunity for ageing research, especially with the integration of different datasets across traditional boundaries of health and social care, for prognostic research and novel evaluations of interventions with representative populations of older people. However, there are considerable challenges in using routine data at the level of coding, data analysis and in the application of findings to everyday care. New Horizons in applying routine data to investigate novel questions in ageing research require a collaborative approach between clinicians, data scientists, biostatisticians, epidemiologists and trial methodologists. This requires building capacity for the next generation of research leaders in this important area. There is a need to develop consensus code lists and standardised, validated algorithms for common conditions and outcomes that are relevant for older people to maximise the potential of routine data research in this group. Lastly, we must help drive the application of routine data to improve the care of older people, through the development of novel methods for evaluation of interventions using routine data infrastructure. We believe that harnessing routine data can help address knowledge gaps for older people living with multiple conditions and frailty, and design interventions and pathways of care to address the complex health issues we face in caring for older people., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Background: frailty has major implications for health and social care services internationally. The development, validation and national implementation of the electronic Frailty Index (eFI) using routine primary care data has enabled change in the care of older people living with frailty in England., Aims: to externally validate the eFI in Wales and assess new frailty-related outcomes., Study Design and Setting: retrospective cohort study using the Secure Anonymised Information Linkage (SAIL) Databank, comprising 469,000 people aged 65-95, registered with a SAIL contributing general practice on 1 January 2010., Methods: four categories (fit; mild; moderate and severe) of frailty were constructed using recognised cut points from the eFI. We calculated adjusted hazard ratios (HRs) from Cox regression models for validation of existing outcomes: 1-, 3- and 5-year mortality, hospitalisation, and care home admission for validation. We also analysed, as novel outcomes, 1-year mortality following hospitalisation and frailty transition times., Results: HR trends for the validation outcomes in SAIL followed the original results from ResearchOne and THIN databases. Relative to the fit category, adjusted HRs in SAIL (95% CI) for 1-year mortality following hospitalisation were 1.05 (95% CI 1.03-1.08) for mild frailty, 1.24 (95% CI 1.21-1.28) for moderate frailty and 1.51 (95% CI 1.45-1.57) for severe frailty. The median time (lower and upper quartile) between frailty categories was 2,165 days (lower and upper quartiles: 1,510 and 2,831) from fit to mild, 1,155 days (lower and upper quartiles: 756 and 1,610) from mild to moderate and 898 days (lower and upper quartiles: 584 and 1,275) from moderate to severe., Conclusions: further validation of the eFI showed robust predictive validity and utility for new outcomes., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Introduction: This study will evaluate the effectiveness of home adaptations, both in preventing hospital admissions due to falls for older people, and improving timely discharge. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and fall prevention., Methods and Analysis: All individuals living in Wales, UK, aged 60 years and over, will be included in the study using anonymised linked data from the Secure Anonymised Information Linkage Databank. We will use a national database of home modifications implemented by the charity organisation Care & Repair Cymru (C&R) from 2009 to 2017 to define an intervention cohort. We will use the electronic Frailty Index to assign individual levels of frailty (fit, mild, moderate or severe) and use these to create a comparator group (non-C&R) of people who have not received a C&R intervention. Coprimary outcomes will be quarterly numbers of emergency hospital admissions attributed to falls at home, and the associated length of stay. Secondary outcomes include the time in moving to a care home following a fall, and the indicative financial costs of care for individuals who had a fall. We will use appropriate multilevel generalised linear models to analyse the number of hospital admissions related to falls. We will use Cox proportional hazard models to compare the length of stay for fall-related hospital admissions and the time in moving to a care home between the C&R and non-C&R cohorts. We will assess the impact per frailty group, correct for population migration and adjust for confounding variables. Indicative costs will be calculated using financial codes for individual-level hospital stays. Results will provide evidence for services at the interface between health and social care, informing policies seeking to promote healthy ageing through prudent healthcare and prevention., Ethics and Dissemination: Information governance requirements for the use of record-linked data have been approved and only anonymised data will be used in our analysis. Our results will be submitted for publication in peer-reviewed journals. We will also work with lay members and the knowledge transfer team at Swansea University to create communication and dissemination materials on key findings., Competing Interests: Competing interests: NW is an employee of Care & Repair Cymru. All other authors declare that they have no competing interests., (© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)