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Background: Fitness and physical activity are important for cardiovascular and mental health but activity and fitness levels are declining especially in adolescents and among girls. This study examines clustering of factors associated with low fitness in adolescents in order to best target public health interventions for young people. Methods: 1147 children were assessed for fitness, had blood samples, anthropometric measures and all data were linked with routine electronic data to examine educational achievement, deprivation and health service usage. Factors associated with fitness were examined using logistic regression, conditional trees and data mining cluster analysis. Focus groups were conducted with children in a deprived school to examine barriers and facilitators to activity for children in a deprived community. Results: Unfit adolescents are more likely to be deprived, female, have obesity in the family and not achieve in education. There were 3 main clusters for risk of future heart disease/diabetes (high cholesterol/insulin); children at low risk (not obese, fit, achieving in education), children ‘visibly at risk’ (overweight, unfit, many hospital/GP visits) and ‘invisibly at risk’ (unfit but not overweight, failing in academic achievement). Qualitative findings show barriers to physical activity include cost, poor access to activity, lack of core physical literacy skills and limited family support. Conclusions: Low fitness in the non-obese child can reveal a hidden group who have high risk factors for heart disease and diabetes but may not be identified as they are normal weight. In deprived communities low fitness is associated with non-achievement in education but in non-deprived communities low fitness is associated with female gender. Interventions need to target deprived families and schools in deprived areas with community wide campaigns. [ABSTRACT FROM AUTHOR]

Background: Qualitative research methods are increasingly used within clinical trials to address broader research questions than can be addressed by quantitative methods alone. These methods enable health professionals, service users, and other stakeholders to contribute their views and experiences to evaluation of healthcare treatments, interventions, or policies, and influence the design of trials. Qualitative data often contribute information that is better able to reform policy or influence design. Methods: Health services researchers, including trialists, clinicians, and qualitative researchers, worked collaboratively to develop a comprehensive portfolio of standard operating procedures (SOPs) for the West Wales Organisation for Rigorous Trials in Health (WWORTH), a clinical trials unit (CTU) at Swansea University, which has recently achieved registration with the UK Clinical Research Collaboration (UKCRC). Although the UKCRC requires a total of 25 SOPs from registered CTUs, WWORTH chose to add an additional qualitative-methods SOP (QM-SOP). Results: The qualitative methods SOP (QM-SOP) defines good practice in designing and implementing qualitative components of trials, while allowing flexibility of approach and method. Its basic principles are that: qualitative researchers should be contributors from the start of trials with qualitative potential; the qualitative component should have clear aims; and the main study publication should report on the qualitative component. Conclusions: We recommend that CTUs consider developing a QM-SOP to enhance the conduct of quantitative trials by adding qualitative data and analysis. We judge that this improves the value of quantitative trials, and contributes to the future development of multi-method trials. [ABSTRACT FROM AUTHOR]

Background: A UK Register of people with Multiple Sclerosis has been developed to address the need for an increased knowledge-base about MS. The Register is being populated via: a web-based portal; NHS neurology clinical systems; and administrative data sources. The data are de-identified and linked at the individual level. At the outset, it was not known whether people with MS would wish to participate in the UK MS Register by personally contributing their data to the Register via a web-based system. Therefore, the research aim of this work was to build an internet-mounted recruitment and consenting technology for people with Multiple Sclerosis, and to assess its feasibility as a questionnaire delivery platform to contribute data to the UK MS Register, by determining whether the information provided could be used to describe a cohort of people with MS. Methods: The web portal was developed using VB.net and JQuery with a Microsoft SQL 2008 database. UK adults with MS can self-register and enter data about themselves by completing validated questionnaires. Descriptive statistics were used to characterise the respondents. Results: The web portal was launched in May 2011, and in first three months 7,279 individuals registered on the portal. The ratio of men to women was 1:2.4 (n = 5,899), the mean self-reported age at first symptoms was 33.8 (SD 10.5) years, and at diagnosis 39.6 (SD 10.3) years (n = 4,401). The reported types of MS were: 15% primary progressive, 63% relapsing-remitting, 8% secondary progressive, and 14% unknown (n = 5,400). These characteristics are similar to those of the prevalent MS population. Employment rates, sickness/disability rates, ethnicity and educational qualifications were compared with the general UK population. Information about the respondents' experience of early symptoms and the process of diagnosis, plus living arrangements are also reported. Conclusions: These initial findings from the MS Register portal demonstrate the feasibility of collecting data about people with MS via a web platform, and show that sufficient information can be gathered to characterise a cohort of people with MS. The innovative design of the UK MS register, bringing together three disparate sources of data, is creating a rich resource for research into this condition. [ABSTRACT FROM AUTHOR]

Background: To develop a population-based cohort of people with ankylosing spondylitis (AS) in Wales using (1) secondary care clinical datasets, (2) patient-derived questionnaire data and (3) routinely-collected information in order to examine disease history and the health economic cost of AS. Methods: This data model will include and link (1) secondary care clinician datasets (i.e. electronic patient notes from the rheumatologist) (2) patient completed questionnaires (giving information on disease activity, medication, function, quality of life, work limitations and health service utilisation) and (3) a broad range of routinely collected data (including; GP records, in-patient hospital admission data, emergency department data, laboratory/pathology data and social services databases). The protocol involves the use of a unique and powerful data linkage system which allows datasets to be interlinked and to complement each other. Discussion: This cohort can integrate patient supplied, primary and secondary care data into a unified data model. This can be used to study a range of issues such as; the true economic costs to the health care system and the patient, factors associated with the development of severe disease, long term adverse events of new and existing medication and to understand the disease history of this condition. It will benefit patients, clinicians and health care managers. This study forms a pilot project for the use of routine data/patient data linked cohorts for other chronic conditions. [ABSTRACT FROM AUTHOR]

Background: Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Methods: Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for recordlinkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. Results: The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were < 0.2%. A range of techniques for matching datasets to the NHSAR were applied and the optimum technique resulted in sensitivity values of: 99.9% for a GP dataset from primary care, 99.3% for a PEDW dataset from secondary care and 95.2% for the PARIS database from social care. Conclusion: With the infrastructure that has been put in place, the reliable matching process that has been developed enables an ALF to be consistently allocated to records in the databank. The SAIL databank represents a research-ready platform for record-linkage studies. [ABSTRACT FROM AUTHOR]

Background: Vast quantities of electronic data are collected about patients and service users as they pass through health service and other public sector organisations, and these data present enormous potential for research and policy evaluation. The Health Information Research Unit (HIRU) aims to realise the potential of electronically-held, person-based, routinely-collected data to conduct and support health-related studies. However, there are considerable challenges that must be addressed before such data can be used for these purposes, to ensure compliance with the legislation and guidelines generally known as Information Governance.Methods: A set of objectives was identified to address the challenges and establish the Secure Anonymised Information Linkage (SAIL) system in accordance with Information Governance. These were to: 1) ensure data transportation is secure; 2) operate a reliable record matching technique to enable accurate record linkage across datasets; 3) anonymise and encrypt the data to prevent re-identification of individuals; 4) apply measures to address disclosure risk in data views created for researchers; 5) ensure data access is controlled and authorised; 6) establish methods for scrutinising proposals for data utilisation and approving output; and 7) gain external verification of compliance with Information Governance.Results: The SAIL databank has been established and it operates on a DB2 platform (Data Warehouse Edition on AIX) running on an IBM 'P' series Supercomputer: Blue-C. The findings of an independent internal audit were favourable and concluded that the systems in place provide adequate assurance of compliance with Information Governance. This expanding databank already holds over 500 million anonymised and encrypted individual-level records from a range of sources relevant to health and well-being. This includes national datasets covering the whole of Wales (approximately 3 million population) and local provider-level datasets, with further growth in progress. The utility of the databank is demonstrated by increasing engagement in high quality research studies.Conclusion: Through the pragmatic approach that has been adopted, we have been able to address the key challenges in establishing a national databank of anonymised person-based records, so that the data are available for research and evaluation whilst meeting the requirements of Information Governance. [ABSTRACT FROM AUTHOR]