Suchergebnisse

IntroductionThe Dementias Platform UK (DPUK) Cohort Explorer is an interactive, online visualisation tool that allows users to explore data for a number of DPUK cohorts. Over 30 variables across cohorts have been harmonised, including information on demographics, lifestyle, cognition, health, and genetic biomarkers.
Objectives and ApproachThe tool has been developed to complement existing DPUK cohort metadata to provide a visual representation of participant numbers and field-level information for a selection of cohorts. This enables users to determine a cohort's eligibility before applying for access to a cohort's data, and aid in shaping potential hypotheses. Developed using Microsoft PowerBI, the Explorer hosts a subset of the cohort's baseline, harmonised data, allowing a user to interrogate the visualisations of the uploaded data in a secure manner on the DPUK Data Portal website. Visualisations are linked so that participant numbers and distributions can be explored interactively.
ResultsThis approach allows the user to explore the harmonised data across a number of cohorts simultaneously whilst setting and adjusting filters that are of interest to the user's search criteria. This provides a better understanding of the real-world data and enables the user to determine the feasibility of each cohort for potential studies, whilst facilitating meaningful comparisons across cohorts. The tool currently visualises five DPUK cohorts with a total of 82,391 participants, however it is being incrementally developed with more cohorts being added continually.
Conclusion / ImplicationsBy combing an easy-to-use, interactive dashboard with harmonised sets of real-world data, the tool allows the user to explore, interrogate and better understand field-level information in a secure manner with zero data transfer. This provides more insight for the user when applying for access to a cohort dataset using the DPUK Data Portal and may help the user to make more informed decisions and/or hypotheses.

ObjectivesWe aim to determine the proportion of infants entering care in Wales via the two primary legal routes (section 76 of the Social Services and Wellbeing (Wales) Act 2014, and section 31 of the Children Act 1989), and associations between mode of entry and infant characteristics and outcomes.
ApproachThis is a longitudinal cohort study using routinely collected data held in the Secure Anonymised Information Linkage (SAIL) Databank. We will link the Looked After Children dataset with family justice (Cafcass Cymru) data on section 31 proceedings, to explore pathways through the care and family justice systems for infants aged <1 year entering care in Wales between 2012 and 2019. We will follow up each child for two years from the date of their entry into care to track legal outcomes (final legal orders) and placement outcomes (placement type, number of placements, and re-entry into the care system).
ResultsDescriptive statistics will include frequencies and proportions of infants who initially enter the care system via voluntary arrangements (section 76) and care proceedings (section 31), by age, year, local authority, and category of need. We will describe the proportion and characteristics of those with voluntary arrangements who later become the subject of care proceedings, and the distribution of final legal orders and placement types by initial route of entry to care. We will use funnel plots to investigate variation between local authorities. We will use linear regression to test for statistically significant differences in the proportions of infants entering care via the two different routes over time, and chi-square tests to investigate associations between mode of entry and infant characteristics and outcomes.
ConclusionThere is limited information on the care journeys of children in Wales at the individual level. This study will help us to understand the patterns of use of voluntary arrangements for infants over time, the proportion subsequently involved in section 31 applications and the impact on outcomes for children.

Introduction Dementia Platform UK (DPUK) brings together over 50 different dementia-related cohorts. Most studies have restricted follow-up times and all are based on information from people who volunteer time and data for research. Participants are therefore often not representative of the 'wider population' and generalization of results is complicated. The Secure Anonymised Information Linkage databank (SAIL) holds long-time information on every person in Wales registered with the national health service, so generalization of study results is easier; however, data management and analysis of SAIL data is not trivial. We used data from SAIL to construct an easily accessible, well described dementia e-cohort.
Methods With some age restrictions, all Welsh residents for whom primary care data were available were included. Within SAIL, a table was created holding demographic information for every participant including follow-up times and several dementia indicators. Using validated diagnostic code lists, this table was linked to information on every dementia-related diagnostic event and several covariates and co-morbidites. SAIL-DeC can be modified according to varying study designs using annotated SQL-based scripts. Information on SAIL-DeC can easily be updated and linked to additional data on the SAIL database. Interactive visualisations effectively summarise cohort characteristics, aiding researchers to quickly determine cohort eligibility for dementia studies.
Results From 4.4 million participants in SAIL, 1.2 million met the cohort inclusion criteria, resulting in 18.8 million person-years of follow-up. Of these, 129,650 (10%) developed all-cause dementia during follow-up, with 77,978 (60%) having dementia subtype codes. Seventy-nine percent of participants who developed dementia died during follow-up. Median survival was 12.3 years for participants diagnosed with dementia when aged 50-60, 6.8 years when aged 60-70, 4.2 years when aged 70-80 and 2.4 years when aged 80-90.
Conclusions We have created a generalisable, national dementia e-cohort, aimed at facilitating epidemiological dementia research.

IntroductionOsteoporosis is a global disease with a 30-40% lifetime fracture risk according to the World Health Organisation. Over half a million people receive treatment for fragility fractures annually in the UK. Osteoporosis incidence is rising with aging populations; however, medical secondary prevention treatment may reduce fracture risk.
Objectives and ApproachPrimary aims were to investigate if secondary medical prevention treatment following an index fracture was associated with survival and subsequent fracture risk, evaluated using a pseudonymised population based e-cohort study design. Patients aged ≥60 years with an index fragility fracture at any anatomical location were identified from the Secure Anonymised Information Linkage (SAIL) databank. Fracture data were identified from secondary care datasets (emergency department and inpatient) and the National Hip Fracture Register data. In addition linkages were made to primary care datasets for medical prescription and Office for National Statistics records for mortality, supplementing data on demographic characteristics and co-morbidity.
ResultsThe cohort comprised 81,252 cases between April 2009 and December 2016 of median age 78 years (range 60-109) and 22,896 (28%) males. Medical secondary prevention treatment was received by 29,393 cases (36%). Subsequent fractures were reported for 10,907 cases (14%) and 29,026 cases (36%) died during the study period. For those that received medical prevention, the subsequent fracture and mortality rates were 15% and 28% respectively compared to 12% and 31% for those that did not receive the prevention treatment. Further analyses will include a discrete time competing risks model.
Conclusion/ImplicationsA population based e-cohort was successfully created by linking data across multiple datasets. Preliminary findings identified that <50% of eligible patients receive secondary medical prevention treatment after an index fragility fracture. These findings may help inform and unify treatment pathways for those at risk of fragility fractures.

BackgroundOsteoporosis is a global disease with a 30-40% lifetime fracture risk according to the World Health Organisation. Incidence is rising with aging populations; however, medical secondary prevention treatment may reduce fracture risk.
ObjectivesThe primary aim was to investigate if secondary medical prevention treatment following an index fracture was associated with survival and subsequent fracture risk.
MethodsPatients aged ≥60 years with an index fragility fracture at any anatomical location were identified from the Secure Anonymised Information Linkage (SAIL) databank. A population based e-cohort was created by linking fracture data identified from secondary care datasets and the National Hip Fracture Register data, with linkages to primary care datasets for medical prescription and Office for National Statistics records for mortality.
FindingsThe cohort comprised 81,252 cases between April 2009 and December 2016 of median age 78 years and 22,896 (28%) males. Medical secondary prevention treatment was received by 29,393 cases (36%). Subsequent fractures were reported for 10,907 cases (13%) and 29,026 cases (36%) died during the study period.
ConclusionsPreliminary findings identified that <50% of eligible patients receive secondary medical prevention treatment after an index fragility fracture. These findings may help inform and unify treatment pathways for those at risk of fragility fractures.

ObjectivesA defining feature 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.
ApproachUtilising linked data in the SAIL Databank we set out to develop a linked data platform as part of the 'One Wales' approach to generate evidence to inform policy makers on the key areas of transmission pathways, care home characteristics, excess mortality, and the impacts of vaccination. We used multi-sectoral linked data including routinely collected health data, administrative data and GIS generated metrics on care home characteristics and community infection rates to better understand how multiple factors impacted on care home residents.
ResultsWe created a care home index with enhanced care home characteristics for all care homes in Wales and were able to link 15,773 care home residents in the SAIL Databank to 923 care homes. We were able to generate early evidence demonstrating an increased risk of mortality for care home residents during Wave 1 (adjusted HR 1.72 compared to 2016). We were able to show that hospital discharge in Wales during the initial stages of the pandemic, although significant, had a much smaller impact on subsequent infections than care home size and accounted for 1.8% of infected discharge events. We also showed that community prevalence, inpatient appointments and people living with dementia all contributed to increased risks of catching COVID in a care home.
ConclusionThe response of the 'One Wales' team and the SAIL linked data platform facilitated meaningful insight on the impacts of COVID in social care settings in Wales. The evidence generated was used by policy makers from Welsh and UK Governments to inform policy direction as the pandemic progressed.

IntroductionResearch can often be slow to start and require duplication of effort which in lots of cases has previously been completed to generate research-ready-data-assets (RRDA). Within the UK, two programmes: Dementias Platform UK (DPUK) that brings together over 50 different dementia-related cohorts and Secure Anonymised Information Linkage (SAIL) Databank, which provides access to longitudinal population-scale person-level data for every person in Wales have tried to tackle this challenge of creation, use and management of RRDA's.
Objectives and ApproachCombining clinical, data and management expertise from DPUK and SAIL, we hoped to construct a RRDA that was easily accessible and well described for a dementia e-cohort. Welsh residents with available primary care records were included, with clinical and demographic information including follow-up times, several dementia indicators using validated diagnostic code lists, information on every dementia-related diagnostic event and several covariates and co-morbidities. SDeC was made available to researchers and can be modified according to appropriate study designs, with learning from projects used to update the SDeC to improve future uses. Interactive visualisations effectively summarise cohort characteristics, aiding researchers to quickly determine cohort eligibility for dementia studies.
ResultsSDeC contains data from 4.6 million participants in SAIL, with 1.5 million meeting cohort inclusion criteria, resulting in 24.3 million person-years of follow-up. Of these, 146,323 (10%) developed all-cause dementia during follow-up, with 90,150 (60%) having dementia subtype codes. We made this resource available to researchers who had never used SAIL before, with limited experience of population-scale routine-data, and projects have proceeded with one managing to proceed from point of initial access to submission of publication in less than 6-months.
Conclusion / ImplicationsSDeC provides a reproducible dynamic method for completing dementia research, and expediting learning and understanding of the use of these data, with further developments and maintenance planned to increase the complexity and detail available to researchers over time.

IntroductionThe Dementias Platform UK (DPUK) Data Portal is a secure, accessible environment facilitating provision of rich data towards the largest Dementia, cognition and ageing community of cohort studies in the world. DPUK is also providing services for cohort studies and researchers to maximise the research potential of the programme's community.
Objectives and ApproachAs part of the engagement of DPUK cohorts with the Data Portal, cohorts will upload data onto the DPUK instance of UK Secure eResearch Platform infrastructure. The Data Portal allows access to a collaborative working space that allows cohorts to enrich their own data, perform their own analysis, and enhance the research potential of their data whilst making use of expertise at various DPUK sites, such as data linking, curation and multi-modal specialism. Cohort data divided into ontologies allows researchers to access data specific to their study needs and can be requested from multiple cohorts simultaneously.
ResultsBy utilising the Data Portal researchers have access to cohort data that has been prepared for dementia epidemiology using the agreed ontologies, providing more rapid access to cohort data that otherwise may be large and complex. The knowledge and experience of DPUK staff and collaborators can also help to guide nascent cohorts and feasibility studies into producing research-ready datasets, enabling them to achieve greater impact with their data. A range of analytical tools are provided on the Data Portal making analysis of a cohort's own data or multiple independent datasets more accessible. Alongside data curation, DPUK also facilitates data linkage to routine sources, beginning with a Wales-wide use case that will expand to the UK over the course of the project.
Conclusion/ImplicationsData from international sources accessible using a central platform permits international collaboration, with ontologies allowing previously disparate data to be combined and analysed to build knowledge and research impact. DPUK projects create policy leading results and operational research standards, enhancing cohort impact and discovery of benefits for Dementia patients.

IntroductionModern team science requires effective sharing of data and skills. The DPUK Data Portal is a collection of tools, datasets and networks that allows for epidemiologists and specialist researchers alike to access, analyse and investigate cohort and different modalities of routine data across UK and international sources.
Objectives and ApproachThe Portal is housed on an instance of UKSeRP (UK Secure eResearch Platform), that allows customisable infrastructure to be used for multi-modal research (thus far live in genetics, imaging and clinical data) for researchers across the world using remote access technology whilst allowing governance to remain with the data provider. A central team at Swansea University is responsible for data curation and processing, and runs an access procedure for researchers to apply to use data from multiple sources to be analysed in a central analysis environment. Other modalities are similarly hosted, with input from partner sites in Cardiff and Oxford.
ResultsDPUK facilitates data access and research on 49 cohorts, 40 UK-based and 9 international. The centralised repository model including remote access and ability to store and make available different modalities of data, from phenotypic data, to genetic and imaging data, has allowed DPUK to begin to support research of varying topics, from those studying cognitive decline and Dementia as a disease, to those maturing analytical models. By providing access to data platforms specialising in genetics, imaging and routine clinical data, as well as to specialists in disease and biology to aid with its understanding, DPUK has realised a large-scale research exercise combining major data modalities on a central platform, and allow access to such rich data across the world under an umbrella of robust governance.
Conclusion/ImplicationsGlobally, cohorts are pooling data, expertise and desire to enrich their own aims in partnership with a federated research community to enable in-depth scrutiny of the biological origins of dementia and the development and evaluation of novel approach to disease prevention and cure.

IntroductionCOVID-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.
ObjectivesTo validate externally the QCOVID risk prediction algorithm that predicts mortality outcomes from COVID-19 in the adult population of Wales, UK.
MethodsWe 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 24th January 2020, registered with a SAIL-providing general practice, and followed-up to death or study end (28th 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 R2 values (explained variation), Brier scores, and measures of discrimination and calibration were calculated for two periods (24th January–30th April 2020 and 1st May–28th July 2020) to assess algorithm performance.
Results1,956,760 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.
ConclusionsThe QCOVID algorithm developed in England can be used for public health risk management for the adult Welsh population.

ObjectivesUnder section 31 (s.31) of the UK Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm. We examined health vulnerabilities of parents involved in public law care proceedings in the two-year period prior to involvement.
ApproachOur study created an anonymised individual-level population-based cohort, with a matched comparison group of parents in Wales who were not subject to care proceedings, matched on age, sex and deprivation. Family court data provided by Cafcass Cymru were linked to population-level healthcare records held within the Secure Anonymised Information Linkage (SAIL) Databank. Demographic characteristics, overall health service use and health profiles of parents of children subject to s.31 care proceedings between 2011 and 2019 were examined.
ResultsData were available for 8,821 parents involved in care proceedings between 2011 and 2019, with a comparison group of 32,006 parents. Nearly half (47.6%) of cohort parents resided in the most deprived quintile. Higher levels of healthcare use were found for cohort mothers and fathers compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%).
ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

BackgroundPopulation-level information on dispensed medication provides insight on the distribution of treated morbidities, particularly if linked to other population-scale data at an individual-level.
ObjectiveTo evaluate the impact of COVID-19 on dispensing patterns of medications.
MethodsRetrospective observational study using population-scale, individual-level dispensing records in Wales, UK. Total dispensed drug items for the population between 1st January 2016 and 31st December 2019 (3-years, pre-COVID-19) were compared to 2020 with follow up until 27th July 2021 (COVID-19 period). We compared trends across all years and British National Formulary (BNF) chapters and highlighted the trends in three major chapters for 2019-21: 1-Cardiovascular system (CVD); 2-Central Nervous System (CNS); 3-Immunological & Vaccine. We developed an interactive dashboard to enable monitoring of changes as the pandemic evolves.
ResultAmongst all BNF chapters, 73,410,543 items were dispensed in 2020 compared to 74,121,180 items in 2019 demonstrating -0.96% relative decrease in 2020. Comparison of monthly patterns showed average difference (D) of -59,220 and average Relative Change (RC) of -0.74% between the number of dispensed items in 2020 and 2019. Maximum RC was observed in March 2020 (D= +1,224,909 and RC= +20.62%), followed by second peak in June 2020 (D= +257,920, RC= +4.50%). A third peak was observed in September 2020 (D= +264,138, RC= +4.35%). Large increases in March 2020 were observed for CVD and CNS medications across all age groups. The Immunological and Vaccine products dropped to very low levels across all age groups and all months (including the March dispensing peak).
ConclusionsReconfiguration of routine clinical services during COVID-19 led to substantial changes in community pharmacy drug dispensing. This change may contribute to a long-term burden of COVID-19, raising the importance of a comprehensive and timely monitoring of changes for evaluation of the potential impact on clinical care and outcomes.

IntroductionUnder section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services.
ObjectiveTo examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement.
MethodsFamily court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used.
ResultsNearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%).
ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community.

Funding: This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (HDRUK2020.146). EAVE II is funded by the Medical Research Council (MC_PC_19075) and supported by the Scottish Government. This work is supported by BREATHE - The Health Data Research Hub for Respiratory Health (MC_PC_19004). BREATHE is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. ConCOV is supported by the Medical Research Council (MR/V028367/1); Health Data Research UK (HDR-9006) which receives its funding from the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust; and Administrative Data Research UK which is funded by the Economic and Social Research Council (grant ES/S007393/1). ; Introduction : The novel coronavirus SARS-CoV-2, which emerged in December 2019, has caused millions of deaths and severe illness worldwide. Numerous vaccines are currently under development of which a few have now been authorised for population-level administration by several countries. As of 20 September 2021, over 48 million people have received their first vaccine dose and over 44 million people have received their second vaccine dose across the UK. We aim to assess the uptake rates, effectiveness, and safety of all currently approved COVID-19 vaccines in the UK. Methods and analysis : We will use prospective cohort study designs to assess vaccine uptake, effectiveness and safety against clinical outcomes and deaths. Test-negative case–control study design will be used to assess vaccine effectiveness (VE) against laboratory confirmed SARS-CoV-2 infection. Self-controlled case series and retrospective cohort study designs will be carried out to assess vaccine safety against mild-to-moderate and severe adverse events, respectively. Individual-level pseudonymised data from primary care, secondary care, laboratory test and death records will be linked and analysed in secure research environments in each UK nation. Univariate and multivariate logistic regression models will be carried out to estimate vaccine uptake levels in relation to various population characteristics. VE estimates against laboratory confirmed SARS-CoV-2 infection will be generated using a generalised additive logistic model. Time-dependent Cox models will be used to estimate the VE against clinical outcomes and deaths. The safety of the vaccines will be assessed using logistic regression models with an offset for the length of the risk period. Where possible, data will be meta-analysed across the UK nations. Ethics and dissemination : We obtained approvals from the National Research Ethics Service Committee, Southeast Scotland 02 (12/SS/0201), the Secure Anonymised Information Linkage independent Information Governance Review Panel project number 0911. Concerning English data, University of Oxford is compliant with the General Data Protection Regulation and the National Health Service (NHS) Digital Data Security and Protection Policy. This is an approved study (Integrated Research Application ID 301740, Health Research Authority (HRA) Research Ethics Committee 21/HRA/2786). The Oxford-Royal College of General Practitioners Clinical Informatics Digital Hub meets NHS Digital's Data Security and Protection Toolkit requirements. In Northern Ireland, the project was approved by the Honest Broker Governance Board, project number 0064. Findings will be made available to national policy-makers, presented at conferences and published in peer-reviewed journals. ; Publisher PDF ; Peer reviewed