Data Resource Profile: Children Looked After Return (CLA).
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ABSTRACT:
SUBMITTER: Mc Grath-Lone L
PROVIDER: S-EPMC5005948 | biostudies-literature | 2016 Jun
REPOSITORIES: biostudies-literature
Publications
Data Resource Profile: Children Looked After Return (CLA).
Mc Grath-Lone Louise L Harron Katie K Dearden Lorraine L Nasim Bilal B Gilbert Ruth R
International journal of epidemiology 20160601 3
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Project description:IntroductionChildren who are 'looked after' by the State are considered one of the most vulnerable groups in society. Being in State care is associated with poor social, educational and health outcomes. Exploring how to improve the system and better support children in care is key to improving these outcomes. When children and young people come to the attention of children's social services a significant amount of information about their care experience is routinely collected by local authorities. In Wales, routine data are captured in the 'Children Looked After' Census which is submitted annually to the Welsh Government and has recently been shared with the Secure Anonymised Information Linkage (SAIL) Databank.MethodThe aim of this paper is to provide an overview of the main 'Children Looked After' Census dataset and its subsets. These datasets contain rich, situational and individual level data on children looked after, such as information on placement types, education and leaving care. We outline the strengths and limitations of the available information and how to access the data.ResultsThe 'Children Looked After' Census has recently been made available for research purposes and access to it will enable researchers to explore and understand at population level the journey through the care system and outcomes of leaving care. There is also the opportunity, through the SAIL Databank, for data linkage to health, education and family justice datasets, allowing research to holistically explore other factors associated with being in care.ConclusionThese data provide a rich source of information about children and young people who have been in care in Wales. They offer researchers opportunities to better understand the care system and outcomes for this within it. Findings will have important implications for making improvements in children's social care policy and practice.
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Project description:The PATHS Data Resource is a unique database comprising data that follow individuals from the prenatal period to adulthood. The PATHS Resource was developed for conducting longitudinal epidemiological research into child health and health equity. It contains individual-level data on health, socioeconomic status, social services and education. Individuals' data are linkable across these domains, allowing researchers to follow children through childhood and across a variety of sectors. PATHS includes nearly all individuals that were born between 1984 and 2012 and registered with Manitoba's universal health insurance programme at some point during childhood. All PATHS data are anonymized. Key concepts, definitions and algorithms necessary to work with the PATHS Resource are freely accessible online and an interactive forum is available to new researchers working with these data. The PATHS Resource is one of the richest and most complete databases assembled for conducting longitudinal epidemiological research, incorporating many variables that address the social determinants of health and health equity. Interested researchers are encouraged to contact [mchp_access@cpe.umanitoba.ca] to obtain access to PATHS to use in their own programmes of research.
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Project description:The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.
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Project description:BackgroundTo improve the assessment of COVID-19 vaccine use, safety, and effectiveness in older adults and persons with complex multimorbidity, the COVid VAXines Effects on the Aged (COVVAXAGE) database was established by linking CVS Health and Walgreens pharmacy customers to Medicare claims.MethodsWe deterministically linked CVS Health and Walgreens customers who had a pharmacy dispensation/encounter paid for by Medicare to Medicare enrollment and claims records. Linked data include U.S. Medicare claims, Medicare enrollment files, and community pharmacy records. The data currently span 01/01/2016 to 08/31/2022. "Research-ready" files were created, with weekly indicators for vaccinations, censoring, death, enrollment, demographics, and comorbidities. Data are updated quarterly.ResultsAs of November 2022, records for 27,086,723 CVS Health and 23,510,025 Walgreens unique customer IDs were identified for potential linkage. Approximately 91% of customers were matched to a Medicare beneficiary ID (95% for those aged 65 years or older). In the final linked cohort, there were 38,250,873 unique beneficiaries representing ~60% of the Medicare population. Among those alive and enrolled in Medicare as of January 1, 2020 (n = 33,721,568; average age = 73 years, 74% White, 51% Medicare Fee-for-Service, and 11% dual-eligible for Medicaid), the average follow-up time was 130 weeks. The cohort contains 16,021,055 beneficiaries with evidence a first COVID-19 vaccine dose. Data are stored on the secure Medicare & Medicaid Resource Information Center Health & Aging Data Enclave.Data accessInvestigators with funded or in-progress funding applications to the National Institute on Aging who are interested in learning more about the database should contact Dr Vincent Mor [Vincent_mor@brown.edu] and Dr Kaleen Hayes [kaley_hayes@brown.edu]. A data dictionary can be provided under reasonable request.ConclusionsThe COVVAXAGE cohort is a large and diverse cohort that can be used for the ongoing evaluation of COVID-19 vaccine use and other research questions relevant to the Medicare population.
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Project description:Electronic health records (EHRs) can provide researchers with extraordinary opportunities for population-based research. The National Health Insurance system of Taiwan was established in 1995 and covers more than 99.6% of the Taiwanese population; this system's claims data are released as the National Health Insurance Research Database (NHIRD). All data from primary outpatient departments and inpatient hospital care settings after 2000 are included in this database. After a change and update in 2016, the NHIRD is maintained and regulated by the Data Science Centre of the Ministry of Health and Welfare of Taiwan. Datasets for approved research are released in three forms: sampling datasets comprising 2 million subjects, disease-specific databases, and full population datasets. These datasets are de-identified and contain basic demographic information, disease diagnoses, prescriptions, operations, and investigations. Data can be linked to government surveys or other research datasets. While only a small number of validation studies with small sample sizes have been undertaken, they have generally reported positive predictive values of over 70% for various diagnoses. Currently, patients cannot opt out of inclusion in the database, although this requirement is under review. In conclusion, the NHIRD is a large, powerful data source for biomedical research.
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Project description:IntroductionRandomised controlled trials (RCTs) conducted in care home settings address a range of health conditions impacting older people, but often include a common core of data about residents and the care home environment. These data can be used to inform service provision, but accessing these data can be challenging.MethodsThe Virtual International Care Home Trials Archive (VICHTA) collates care home RCTs conducted since 2010, with >100 participants, across multiple conditions, with documented eligibility criteria, initially identified from a scoping review. A Steering Committee comprising contributing trialists oversees proposed uses of fully anonymised data. We characterised available demography and outcomes to inform potential analyses. Data are accessible via application to the Virtual Trials Archives, through a secure online analysis platform. Trial recruitment is ongoing and future expansion will include international studies.ResultsThe first phase of VICHTA includes data from six UK RCTs, with individual participant data (IPD) on 5,674 residents across 308 care homes. IPD include age, sex, dementia status, length of stay, quality of life, clinical outcome measures, medications, resource use, and care home characteristics, such as funding, case mix, and occupancy. Follow-up ranges between four and sixteen months.ConclusionsVICHTA collates and makes accessible data on a complex and under-represented research population for novel analyses, and to inform design of future studies. Planned expansion to international care home RCTs will facilitate a wider range of research questions. Interested collaborators can submit trial data or request data at http://www.virtualtrialsarchives.org.
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