Suchergebnisse

IntroductionDiscovering suitable datasets is an important part of health research, particularly for projects using linked and/or cohort data, but with the proliferation of so many national and international initiatives, it is becoming increasingly difficult for research teams to locate real world datasets that are most relevant to their project objectives.
Objectives and ApproachTo assist researchers in this, a bibliographic data analysis platform, bibInsight, is being developed which aims to identify potentially useful datasets, among other information, from large numbers of publications.
A search dataset on the broad topic of "dementia" was obtained from PubMed and abstracts mentioning cohort names were identified. These helped in determining the context within which cohort data are mentioned. Terms were also informed by specialist knowledge from the European Medical Information Framework (EMIF) Alzheimer's Disease project, and were used to train a one-class classifier that identified their structure.
ResultsThe initial PubMed search resulted in 129,040 articles, with 1961 identified cohorts. From these, the classifier was able to identify 1,588 as containing cohort information, and 373 as not, a precision of approximately 80\%.
The terms identified by the classifier included "annual", "longitudinal", and "prospective", suggesting re-contact.
Further analysis of these 1,588 abstracts can find those most relevant to specific topics, co-authorship collaborations (suggesting data sharing agreements are already in place), and mention of linkage to other datasets. These can be done through keyword extraction, longitudinal data mining methods, linking author affiliations to institutions through the Global Resource Information Database (GRID), and graph databases, all of which have been built into the bibInsight platform.
Conclusion/Implications`This approach shows promise in facilitating research by making literature searches more efficient. A key issue is working with unstructured text data which requires additional standardisation for analysis. Data reuse is a growing area, and publications can assist this, but better reporting would be beneficial.

BackgroundDiscovering suitable datasets is an important part of health research, particularly for projects working with cohort data, but with the proliferation of so many national and international initiatives, it is becoming increasingly difficult for research teams to locate real world datasets that are most relevant to their project objectives.
MethodsTo assist researchers in this, we developed bibInsight, a data analysis platform to identify potentially useful data sources and more generally enable large scale research over bibliographical datasets.
Data source names were identified from a broad, topic specific literature search. Context-specific terms like "annual", "longitudinal", and "prospective" were used to train a classifier that identified potential datasets.
ResultsThe classifier was able to identify 1588 of 1961 abstracts as containing cohort-relevant information: a precision of approximately 80%.
Further analysis such as topic analysis, geographical mapping, and collaboration networks can refine and prioritise the search results to determine the most relevant data source(s) for a research project.
ConclusionsA very large amount of information, including data source description and use, remains unexploited in unstructured bibliographical datasets. Here, we used a thematic search to provide a more manageable starting point towards locating disease specific datasets.

IntroductionRoutine data sources are increasingly being explored as an alternative to surveys for governmental censuses. Censuses are useful, but only capture one snapshot in time. For research, changes in state over time can be important. This is particularly true for households, where changes in both composition and location are routine.
Objectives and ApproachThe Secure Anonymised Information Linkage (SAIL) databank at Swansea University holds anonymised address data tied to Welsh General Practice (GP) registrations. The dataset has the individual's unique identifier (ALF), address identifier (RALF), and moving in and moving out dates. This can be securely linked to other demographic and health data.
Using this data, a finite, deterministic household model was developed. This model implements a set of rules for establishing, advancing, and terminating households. The rules cover different types of households, including transient and multi-generational, but not communal residences such as student halls or residential care homes.
ResultsThe model was implemented in Python, and operates over finite moving in/out transactions undertaken by actors (ALFs) on specific properties (RALFs). The roles also help to diminish data issues, such as infants moving into an address before their parents.
The model creates and updates histories of households for each RALF. This allows researchers to identify unstable versus stable households, or to look at possible environmental health factors over time.
The script also provides a running count of the total number of residents at each RALF at any given time. This makes it useful for time-specific research, or for linking to censuses.
Conclusion/ImplicationsThe ability to have a longitudinal record of households can provide additional detail to research which can be costly to obtain otherwise. This method shows promise as a useful tool for linked population data research. Further validation against surveys, and work to identify and model communal residences is needed.

BackgroundThere are there are considerable challenges to be addressed so the benefits of administrative data for research can be realised. Significant headway is being made, but there is great scope and appetite for further improvement.
ObjectivesThis study set out to explore good practice, barriers and bottlenecks in effective administrative data use, and to gain suggestions on how to share the good, solve the bad and improve the clunky issues.
MethodsUsing the ESRC-funded UK Administrative Data Research Network (ADRN) as the case study, a qualitative survey, focusing on the data use pathway, was carried out across the network. This encompassed a set of 18 questions spanning from acquisition to archiving. Survey responses were grouped into six themes: data acquisition; approval processes; controls on access and disclosure; data and metadata; researcher support; and data reuse and retention. The resulting information matrix was presented to participants at the All Hands meeting (April-May 2017) to facilitate discussion.
FindingsSurvey responses were received from across the network (N=27) and 95 people took part in the workshop. The combined information from the survey and workshop was used to inform set of 18 recommendations across the 6 themes, and this has been used by the ADRN directors to develop an action plan for implementation.
ConclusionsThe ADRN has broken new ground in overcoming many challenges in using administrative data for research in the UK. The recommendations and action plan show how further improvements will be made in the ADRCs, and the findings of this study are relevant more widely to other organisations working with administrative data.

ABSTRACTObjectivesThe main objective of this poster is to present a pilot project in determining emerging population health themes and identifying key research-enabling datasets ahead of time.
At present, large-scale databanks, such as the Secure Anonymised Information Linkage (SAIL) Databank at Swansea University Medical School, already manage large quantities of health and administrative linked datasets. While these datasets are valuable for research purposes, complementary datasets may be required by collaborating researchers to answer detailed population health research questions. Dataset acquisition can take several years, which is a serious delay to a project with time-limited funding.
The ability to pre-emptively acquire datasets so that these are ready for use before a researcher requests them would obviously be beneficial. However, a recent study conducted by the Farr Cipher team at Swansea University identified over 800 health and administrative datasets in Wales alone.
With limited resources such as available funding and time, which of these datasets is worth its effort in acquiring?
ApproachBibliometrics has long been a means of measuring the impact of papers on the wider academic community. Lately, the focus of analyses has been extended to include the topics, authorship and citations of the publications. Existing bibliometric data mining techniques suggest that it is possible to identify emerging topic trends and through this assist in prioritising dataset identification and acquisition.
The project explored mining available literature through bibliometric analysis in order to predict emerging trends and through these identify potentially relevant and valuable datasets for acquisition on behalf of the Dementias Platform UK (DPUK). Literature searches were conducted for papers published on the topic of "dementia" over the last 20 years. Additional keywords and topics were extracted to identify emerging areas of research and clinical interest. These were then compared against an existing list of over 800 Welsh datasets currently not held in SAIL.
ResultsResults focus on:

Using bibliometric methods in the context of DPUK cohort publications
Identifying emerging trends in the field of dementia research.
Identifying and prioritising datasets which might be useful for the SAIL Databank to acquire

The effect of the wider social-environment on physical and emotional health has long been an area of study. Extrapolating the impact of the individual's immediate environment, such as living with a smoker or caring for a chronically-ill child, would potentially reduce confounding effects in health-related research. Surveys, including the UK Census, are beginning to collect data on household composition. However, these surveys are expensive, time consuming, and, as such, are only completed by a subsection of the population. Large-scale, linked databanks, such as the SAIL Databank at Swansea University, which hold routinely collected secondary use clinical and administrative datasets, are broader in scope, both in terms of the nature of the data held, and the population. The SAIL databank includes demographic data and a geographic indicator that makes it possible to identify groups of people that share accommodation, and in some cases the familial relationships among them. This paper describes a method for creating households, including considerations for how that information can be securely shared for research purposes. This approach has broad implications in Wales and beyond, opening up possibilities for more detailed population-level research that includes consideration of residential social interactions.

BackgroundFlying Start (FS) is the Welsh Government's (WG) flagship Early Years programme for families with children aged less than 4 years of age. Running since 2006, the four entitlements are:

Free part-time childcare for 2-3 year olds
Enhanced Health Visiting
Parenting support
Speech, language, and communication support

ObjectivesCurrently, while we know which areas in Wales are receiving FS support, individual-level data on which child received what entitlements is not available. Area-level outcomes can be used as proxy indicators but the individual impact of receiving FS support cannot be examined.The project aims to evaluate FS by linking the FS cohort to a range of outcomes including health, education and social care.
MethodsA Dataflow Development Project (DDP) has been launched to install SAIL (Secure Anonymised Information Linkage) appliances into 6 pilot Local Authorities in Wales which will test acquiring and linking the individual level FS data from pilot Local Authorities with other datasets in SAIL.
FindingsThe project will report some emerging findings from the analysis of pilot data.
ImplicationsThere is a growing interest in using linked administrative data to evaluate government initiatives, and mounting enthusiasm in Local Government. If successful, this model is likely to be adopted by related WG programmes; improving the evidence base, facilitating effective evaluation, and adding to the data available for re-use in Wales.

IntroductionAdministrative data arising via the operation of public service delivery systems hold great benefits for citizens and society providing they can be made available for research in a safe, socially-acceptable way. In recognition of this potential, the UK Administrative Data Research Network was established in 2013 to enable new research for public benefit. However, there are considerable challenges to be overcome for effective data use, and many of these are common to administrative data enterprises in general. Using this network as a practical case study, we set out to explore the challenges, and to share the 'good', suggest solutions to the 'bad', and improve the 'clunky' issues.
MethodsA qualitative survey replicating the data use pathway was carried out across the network, followed by a workshop to discuss the summarised findings and make further suggestions. This led to a set of recommendations to inform the development of an action plan for implementation.
ResultsThe survey respondents (N=27) and workshop participants (N=95) comprised multi‑disciplinary staff from across the network. The responses were summarised by consensus of three researchers and grouped into six areas: A) Data acquisition pathway; B) Approval processes; C) Controls on access & disclosure; D) Data and metadata; E) Researcher support; and F) Data reuse & retention, leading to an embedded set of 18 recommendations. Key developments promoted by this study were the development of themed research partnerships to progress data acquisition, and a policy of data retention and reuse for research.
ConclusionThe network has broken new ground in using administrative data for research. This study has enabled the development of an evidence-based action plan to address many challenges in the effective use of administrative data. It represents a practical worked example, widely relevant to enterprises working with administrative data across the world.
KeywordsAdministrative data research, data access, data linkage

BackgroundHarmonisation of different data sources from various electronic health records (EHRs) across systems enhances the potential scope and granularity of data available to health data research.
ObjectiveTo describe data harmonisation of routine electronic healthcare records in Wales and Scotland linked to a UK longitudinal birth cohort, the Millennium Cohort Study (MCS).
MethodsComparable secondary care data was linked, with parental consent, to MCS information for 1838 and 1431 children participating in MCS and residing in Wales and Scotland, by assigning, respectively, unique Anonymised Linkage Fields to personbased records in the privacy protecting Secure Anonymised Information Linkage (SAIL) databank at Swansea University, and by the National Health Service (NHS) Information Standards Division. Survey and non-response weights were created to account for the clustered sample, sample attrition and consent to linkage. Heterogeneous variables from the Patient Episode Dataset for Wales, Emergency Department Data Set for Wales, Scottish Medical Record 01 and Accident and Emergency dataset for Scotland were harmonised enabling data to be pooled and standardised for research.
FindingsOverall linkage to harmonised health care data was achieved for 98.9% (99.9% for Wales and 97.6% for Scotland) of consented MCS participants. 66% of children experienced at least one hospital admission (total 5747 hospital admissions) up totheir 14th birthday, while 60% attended A&E departments at least once (total 5221 attendances) between their 9th and 14th birthday. We managed date granularity by generating random dates of birth, standardising periods of data collection,identifying inconsistencies and then mapping and bridging differences in definitions of periods of care across countries and datasets.
ConclusionsCombining and harmonising data from multiple sources and linking them to information from a longitudinal cohort create useful resources for population health research. These methods are reproducible and can be utilised by other researchersand projects.

IntroductionHarmonization of different data sources from various electronic health records across systems enhances the potential scope and granularity of data available to health data research, providing more opportunities for research by improving the generalizability and effective sample size of a range of outcome metrics.
Objectives and ApproachThis study describes data harmonisation for a UK longitudinal birth cohort, the Millennium Cohort Study (MCS) which was linked to routine inpatient and emergency department, and, where available, general practice and child health records for 1838 Welsh and 1431 Scottish consenting MCS participants. Datasets requiring harmonisation were: from Wales, Patient Episode Dataset for Wales (PEDW) and Emergency Department Data Set (EDDS) data and from Scotland, Scottish Medical Record 01 (SMR01) and Accident and Emergency dataset (A&E2). Heterogeneous variables were created by transforming variable names, concepts, codes to improve scope for analysis.
ResultsA harmonized dataset of 2166 participants and 5747 hospital admissions were derived of cohort members who had at least 1 hospital inpatient or A&E event before their 14th birthday. Harmonisation included: dealing with date granularity by generating random dates of birth; standardising periods of data collection; identifying inconsistencies and then mapping and bridging differences in definitions of periods of care and levels of diagnostic and operational coding across countries and datasets.
Conclusion/ImplicationsHeterogeneous variables from different data sources were pooled and converted into standardised data for research, extending existing harmonisation work, including curation of a population based anonymously linkable longitudinal cohort. [AA1] These methods are reproducible and can be utilised by other researchers and projects applying to use these routine data sources.

IntroductionPrimary care electronic health records (pcEHRs) are a valuable resource for life course research, however loss to follow up due to changing practices has received little attention. We investigated factors associated with changes in registration and record continuity in the Secure Anonymised Information Linkage (SAIL) databank, with ~80% practice coverage.
Objectives and ApproachWe analysed linked pcEHRs for 1834 (882 girls) Millennium Cohort Study (MCS) participants, resident in Wales and with parental consent to health record linkage at the age seven MCS interview. We studied time from first to next general practice (GP) registration in Wales by fitting Cox proportional hazards models, and estimated mutually-adjusted hazard ratios (aHRs) for the following factors: child (sex, ethnicity, mode of delivery, gestation, birthweight, neonatal illness, wheeze, longstanding illness); maternal (age, education, lone parent status); household (income, housing tenure, residential mobility, urban/rural residence); GP type (SAIL-contributing/-non-contributing). Analyses were weighted for survey design (Stata: Release 15; StataCorp LP).
ResultsThere were 3065 Welsh GP registrations for 1834 children. By age 5 years, 25% of children changed GP at least once, with 1070 (58.3%), 477 (26.0%) and 287 (15.7%) registered with 1, 2, 3+ GPs respectively up to 14 years of age. Children with older mothers (aHRs; 95% CI: 0.96; 0.95, 0.98; per year) or those residing in rural areas (0.75;0.56,0.99) were less likely, and those whose first registration was not with a SAIL contributing GP (2.16;1.60,2.93), whose mothers had no educational qualifications (1.40;1.15,1.71), or had recently changed address (1.62;1.21,2.16) more likely, to change GP. 305 (16.6%) children had never registered with a SAIL-contributing GP. Of 403 children initially registered with a SAIL contributing GP who then changed GP, 66.7% re-registered with a SAIL contributing GP.
Conclusion/ImplicationsGeographically contiguous primary care databanks, such as the SAIL databank, enable a high proportion of children to be reliably followed over time despite changing GP. Similar analyses of databases based on geographically disparate volunteer GPs are needed to quality assure their suitability for life course epidemiology research.

Background Databanks of primary care electronic health records (pcEHRs) are a valuable resource for life course research, however loss to follow up due to changing general practice has received little attention.
ObjectiveWe investigated factors associated with changing general practice (GP) in early life and continuity of participation in the Secure Anonymised Information Linkage (SAIL) databank, to which approximately 80% of Welsh practices contribute.
MethodsWe analysed linked pcEHRs for 1834 (882 girls) Millennium Cohort Study participants, resident in Wales, with consent to health record linkage. We studied time from first to next practice registration using Cox proportional hazards models, and estimated mutually-adjusted hazard ratios (aHRs) for child, household and practice factors.
FindingsThere were 3065 Welsh GP registrations for 1834 children. By age 5 years, 25% changed practice at least once, with 1070 (58.3%), 477 (26.0%), 287 (15.7%) registered with 1, 2, or 3+ GPs respectively by age 14 years. Changing practice was related to maternal age (aHRs; 95% CI: 0.96; 0.95,0.98), living in rural areas (0.75;0.56,0.99), initial registration with a non-SAIL-practice (2.16;1.60,2.93), recent address change (1.62;1.21,2.16), and no maternal educational qualifications (1.40;1.15,1.71). Overall, 305 (16.6%) children had never registered with a SAIL practice. Of 403 children initially registered with a SAIL practice who then changed practice, 66.7% re-registered with a SAIL practice.
ConclusionsIn a nationally representative sample of Welsh children, the majority remained registered with the same practice up to age 14 years, with change in practice varying by maternal and household factors. Continuity of participation in the Welsh SAIL databank over early life is high, reflecting the high proportion of practices contributing, and the high proportion of children registered with them. Geographically contiguous primary care databanks, such as SAIL, enable a high proportion of children to be followed over time despite changing general practice.

BackgroundIn longitudinal health research, combining the richness of cohort data to the extensiveness of routine data opens up new possibilities, providing information not available from one data source alone. In this study, we set out to extend information from a longitudinal birth cohort study by linking to the cohort child's routine primary and secondary health care data. The resulting linked datasets will be used to examine health outcomes and patterns of health service utilisation for a set of common childhood health problems. We describe the experiences and challenges of acquiring and linking electronic health records for participants in a national longitudinal study, the UK Millennium Cohort Study (MCS).
MethodWritten parental consent to link routine health data to survey responses of the MCS cohort member, mother and her partner was obtained for 90.7% of respondents when interviews took place at age seven years in the MCS. Probabilistic and deterministic linkage was used to link MCS cohort members to multiple routinely-collected health data sources in Wales and Scotland.
ResultsOverall linkage rates for the consented population using country-specific health service data sources were 97.6% for Scotland and 99.9% for Wales. Linkage rates between different health data sources ranged from 65.3% to 99.6%. Issues relating to acquisition and linkage of data sources are discussed.
ConclusionsLinking longitudinal cohort participants with routine data sources is becoming increasingly popular in population data research. Our results suggest that this is a valid method to enhance information held in both sources of data.

ABSTRACT
ObjectivesThe aim of this project is to address important issues relevant to children's health This will be done by enhancing information collected in the longitudinal, UK-wide Millennium Cohort Study (MCS) by linking participating children to their routine health records. These issues include: health service implications of early life onset of obesity and overweight; timeliness of immunisations; association of infections with asthma and allergic disorders in childhood; and burden of disease due to childhood injuries.
ApproachThe MCS comprises information on the social, economic and health-related circumstances of children surveyed at ages 9 months, 3, 5, 7, 11 and 14 years. At the age 7 interview, 12517 (89.1%) of the 14043 adults with parental responsibility consented for information from their child's routine heath records to be released to the MCS (a).
Routine health records have been requested for Wales, England and Scotland to be linked to MCS responses within the Secure Anonymised Information Linkage Databank at Swansea University. Data will be analysed using weights for non-response, non-consent and non-linkage and the linkage reported according to the RECORD guidelines (b).
ResultsTo date, all 1881 MCS children with valid consent who live or have lived in Wales have been linked by assigning an Anonymous Linking Field (ALF) to each individual which can be mapped across multiple datasets without risk of identification (c). Of these children, 1365 (72.3%) had experienced at least one hospital admission by the age of 14 years. Risk of admission by each of the survey ages for boys and girls separately will be calculated adjusting for non-response at different sweeps. These children have also been linked to their immunisation records (n = 1872), Emergency Department attendances (n = 1276), and available GP records (n = 1151) to enable analyses in fulfilment of the project objectives.
ConclusionsRoutine health records are a potentially valuable enhancement to longitudinal studies, allowing evaluation of questions of relevance to public health and health services, and the completeness and consistency of records from these different sources to be addressed.
Referencesa. Shepherd, P. (2013) Consent to linkage to child health data ISBN 978-1-906929-59-6b. Benchimol, E.I. et al (2015) DOI: 10.1371/journal.pmed.1001885 c. Ford, D.V. et al (2009) DOI: 10.1186/1472-6963-9-157

ABSTRACT
ObjectivesThe ELAStiC (Electronic Longitudinal Alcohol Study in Communities) project was established to determine factors that predict pathways into alcohol misuse and the life-course effects of alcohol use and misuse on health and well-being. This is achieved through accessing existing longitudinal data that are key sources of evidence for social and health policy, developing statistical methods and modelling techniques from a diverse range of disciplines, working with stakeholders in both policy, practice and the third sector to bring relevance to the work, and to bring together a diverse team of experts to collaborate and facilitate learning across diverse fields.
ApproachThe project will link data that include cohort studies such as; UK Biobank, ALSPAC (Avon Longitudinal Study of Parents and Children), Millennium Cohort Study, British Household Panel Survey, Understanding Society, E_CATALyST (Caerphilly Health and Social Needs Electronic Cohort Study) and WECC (Wales Electronic Cohort for Children). These data will be linked with routine data from primary and secondary healthcare in England, Scotland and Wales. Additional data from education and police data source will also be linked as part of the project.
The main work packages for the project are:
Methodological InnovationsMethodological developments in mechanisms for correcting bias in reporting alcohol consumption and for combining routine data with cohort data; the application of Markov models for examining the extent to which past behaviour influences future behaviour, and econometric hedonic pricing methods for providing insights into the costs of alcohol-related harm.
Pathways into HarmDo family structure, household composition, youngsters' previous ill-health and educational attainment predict their use of alcohol and what socio-economic factors and household transitions contribute to hazardous alcohol consumption in adults?
Secondary HarmsWhat is the effect on children's health and educational achievement of living in households in which one or more adults has experienced alcohol-related harm?
Mental Health & Well-BeingWhat is the relationship between alcohol consumption, hospital admission and mental health in adults and children?
ResultsThe results of the data linkage between the multiple cohorts and health, education and police data will be reported. The challenges of linking cohort and other data types from different nations will be discussed.
ConclusionsOur project will aim to provide evidence that informs the UK Government's commitment to "radically reshape the approach to alcohol and reduce the number of people drinking to excess", by working with existing longitudinal data collected in the UK to inform policy and practice.