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Introduction: The EQ-5D is a widely-used, standardised, quality of life measure producing health profiles, indices and states. The aims of this study were to assess the role of various factors in how people with Multiple Sclerosis rate their quality of life, based on responses to the EQ-5D received via the web portal of the UK MS Register. Methods: The 4516 responses to the EQ-5D (between May 2011 and April 2012) were collated with basic demographic and descriptive MS data and the resulting dataset was analysed in SPSS (v.20). Results: The mean health state for people with MS was 59.73 (SD 22.4, median 61), compared to the UK population mean of 82.48 (which is approximately 1SD above the cohort mean). The characteristics of respondents with high health states (at or above +1SD) were: better health profiles (most predictive dimension: Usual Activities), higher health indices, younger age, shorter durations of MS, female gender, relapsing-remitting MS, higher educational attainment and being in paid employment (all p-values<0.001). Conversely, the characteristics of respondents with low health states (at or below -1SD) were: poorer health profiles (most predictive dimension: Mobility), lower health indices, older age, longer durations of MS, male gender, progressive MS, lower educational attainment and having an employment status of sick/disabled (p = 0.0014 for age, all other p-values<0.001). Particular living arrangements were not associated with either the high or low health status groups. Conclusions: This large-scale study has enabled in-depth analyses on how people with MS rate their quality of life, and it provides new knowledge on the various factors that contribute to their self-assessed health status. These findings demonstrate the impact of MS on quality of life, and they can be used to inform care provision and further research, to work towards enhancing the quality of life of people with MS. [ABSTRACT FROM AUTHOR]

Introduction:The MSIS-29 was developed to assess the physical and psychological impact of MS. The aims of this study were to use the responses to the MSIS-29 via the web portal of the UK MS Register to: examine the internal properties of the scale delivered via the internet, profile the cohort, and assess how well the scale measures impact of disability on the potential workforce. Methods: Between May 2011 and April 2012, 4558 people with MS completed the MSIS-29(v.1). The responses were collated with basic demographic and descriptive MS data and the resulting dataset was analysed in SPSS(v.20). Results: Internal consistency was high (Cronbach's alpha 0.97 MSIS-29-PHYS, 0.92 MSIS-29-PSYCH). The mean MSIS-29-PHYS score was 60.5 (50.6%) with a median of 62 and the mean MSIS-29-PSYCH score was 24.8 (43.8%) with a median of 24. Physical scores increased with age and disease duration (p<0.001, p<0.001), but there was a weak negative relationship between psychological scores and age (p<0.001). The odds of people having an employment status of sick/disabled were 7.2 (CI 5.5, 9.4, p<0.001) for people with a moderate physical score, and 22.3 (CI 17.0, 29.3, p<0.001) for people with a high physical score (relative to having a low physical score). Conclusions: This largest known study of its kind has demonstrated how the MSIS-29 can be administered via the internet to characterise a cohort, and to predict the likely impact of disability on taking an active part in the workforce, as a reasonable proxy for the effects of MS on general activities. The findings examining MSIS-29-PHYS and MSIS-29-PSYCH scores against age support the use of two sub-scales, not a combined score. These results underline the importance of using a scale such as this to monitor disability levels regularly in guiding MS care to enable people to be as active as possible. [ABSTRACT FROM AUTHOR]

Introduction: Studies have found that people with Multiple Sclerosis experience relatively high rates of anxiety and depression. Although methodologically robust, many of these studies had access to only modest sample sizes (N<200). The aims of this study were to use responses gained via the web portal of the UK MS Register (N>4000) to: describe the depression and anxiety profiles of people with MS; to determine if anxiety and depression are related to age or disease duration; and to assess whether the levels of anxiety and depression differ between genders and types of MS. Methods: From its launch in May 2011 to the end of December 2011, 7786 adults with MS enrolled to take part in the UK MS Register via the web portal. The responses to the Hospital Anxiety and Depression Scale (HADS) were collated with basic demographic and descriptive MS data provided at registration and the resulting dataset was analysed in SPSS (v.16). Results: The mean HADS score among the 4178 respondents was 15.7 (SE 0.117, SD 7.55) with a median of 15.0 (IQR 11). Anxiety and depression rates were notably high, with over half (54.1%) scoring ≥8 for anxiety and 46.9% scoring ≥8 for depression. Women with relapsing-remitting MS were more anxious than men with this type (p<0.001), and than women with other types of MS (p = 0.017). Within each gender, men and women with secondary progressive MS were more depressed than men or women with other types of MS (p<0.001, p<0.001). Conclusions: This largest known study of its kind has shown that anxiety and depression are highly prevalent in people with MS, indicating that their mental health needs could be better addressed. These findings support service planning and further research to provide the best care for people with MS to help alleviate these debilitating conditions. [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]

The authors offer insights on the use of data linkage in calculating the health effects of non-health care interventions. They discuss the lack of evidence base for non-health care interventions, the need for recognition of the complexity of real-life settings, and the challenge to the public health research community in measuring these effects.

Similarly, higher body mass index was found to associate independently with increased susceptibility to SARS-CoV-2 infection and COVID-19, and higher titres of anti-S antibodies following COVID-19 and vaccination against SARS-CoV-2.[7],[9],[10] The mechanisms underlying these associations are also worthy of investigation. Follow-up online questionnaires capturing incident symptoms of COVID-19 and other acute respiratory infections, incident swab test-confirmed COVID-19, doses of SARS-CoV-2 vaccine received and quality of life are completed at monthly intervals. A major strength is that COVIDENCE UK was established specifically in response to the SARS-CoV-2 outbreak; thus, in contrast to previously established cohort studies, our questionnaires were tailored to capture potential risk factors and incident symptoms of COVID-19. Key Features The COVIDENCE UK cohort was established to investigate risk factors for, and impacts of, COVID-19 in UK residents aged >=16 years. [Extracted from the article]

Background: People with MS (pwMS) have had higher rates of anxiety and depression than the general population before the COVID-19 pandemic, placing them at higher risk of experiencing poor psychological wellbeing during the pandemic. Objective: To assess mental health and its social/lifestyle determinants in pwMS during the first wave of the outbreak in the United Kingdom. Methods: This is a community-based, prospective longitudinal cohort and cross-sectional case–control online questionnaire study. It includes 2010 pwMS from the UK MS Register and 380 people without MS. Results: The Hospital Anxiety and Depression Scale scores of pwMS for anxiety and depression during the outbreak did not change from the previous year. PwMS were more likely to have anxiety (using General Anxiety Disorder-7) and/or depression (using Patient Health Questionnaire-9) than controls during the outbreak (OR: 2.14, 95% CI: 1.58–2.91). PwMS felt lonelier (OR: 1.37, 95% CI: 1.04–1.80) reported worse social support (OR: 1.90, 95% CI: 1.18–3.07) and reported worsened exercise habits (OR: 1.65, 95% CI: 1.18–2.32) during the outbreak than controls. Conclusion: Early in the pandemic, pwMS remained at higher risk of experiencing anxiety and depression than the general population. It is important that multidisciplinary teams improve their support for the wellbeing of pwMS, who are vulnerable to the negative effects of the pandemic on their lifestyle and social support. [ABSTRACT FROM AUTHOR]

Introduction: It is widely acknowledged that breaches and misuses of health-related data can have serious implications and consequently they often carry penalties. However, harm due to the omission of health data usage, or data non-use, is a subject that lacks attention. A better understanding of this 'other side of the coin' is required before it can be addressed effectively.Approach: This article uses an international case study approach to explore why data non-use is difficult to ascertain, the sources and types of health-related data non-use, its implications for citizens and society and some of the reasons it occurs. It does this by focussing on issues with clinical care records, research data and governance frameworks and associated examples of non-use.Results and Discussion: The non-use of health-related data is a complex issue with multiple explanations. Individual instances of data non-use can be associated with harm, but taken together, they can describe a trail of data non-use that may complicate and compound its impacts. There is ample indirect evidence that health data non-use is implicated in the deaths of many thousands of people and potentially £billions in financial burdens to societies.Conclusions: Harm due to the non-use of health data is difficult to attribute unequivocally and actual proven evidence is sparse. Although it can be elusive, it is nevertheless a real problem with widespread and serious, if largely unquantifiable, consequences. The most effective initiatives to address specific contexts of data non-use will be those that: firstly, understand the pertinent sources, types and reasons for data non-use in a given domain in order to meet the challenges and create appropriate incentives and repercussions; and secondly, are cognisant of the multiple aspects to this complex issue in other domains to keep benefits and limitations in perspective, to move steadily towards socially responsible reuse of data becoming the norm to save lives and resources. [ABSTRACT FROM AUTHOR]

Background: Local and national governments have implemented sector-specific policies to support economic development through innovation, entrepreneurship and knowledge exchange. Supported by the Welsh Government through the European Regional Development Fund, The Life Science Exchange® project was created with the aim to increase interaction between stakeholders, to develop more effective knowledge exchange mechanisms, and to stimulate the formation and maintenance of long-term collaborative relationships within the Welsh life sciences ecosystem. The Life Science Exchange allowed participants to interact with other stakeholder communities (clinical, academic, business, governmental), exchange perspectives and discover new opportunities.Methods: Six sub-sector focus groups comprising over 200 senior stakeholders from academia, industry, the Welsh Government and National Health Service were established. Over 18 months, each focus group provided input to inform healthcare innovation policy and knowledge mapping exercises of their respective sub-sectors. Collaborative projects identified during the focus groups and stakeholder engagement were further developed through sandpit events and bespoke support.Results: Each sub-sector focus group produced a report outlining the significant strengths and opportunities in their respective areas of focus, made recommendations to overcome any 'system failures', and identified the stakeholder groups which needed to take action. A second outcome was a stakeholder-driven knowledge mapping exercise for each area of focus. Finally, the sandpit events and bespoke support resulted in participants generating more than £1.66 million in grant funding and inward investment. This article outlines four separate outcomes from the Life Science Exchange programme.Conclusions: The Life Science Exchange process has resulted in a multitude of collaborations, projects, inward investment opportunities and special interest group formations, in addition to securing over ten times its own costs in funding for Wales. The Life Science Exchange model is a simple and straightforward mechanism for a regional or national government to adapt and implement in order to improve innovation, skills, networks and knowledge exchange. [ABSTRACT FROM AUTHOR]

PsyCymru was initially established as a proof of concept to investigate the feasibility of linking a prospectively ascertained, well-characterised (linked clinical cohort) of people with psychosis in Wales, UK with large amounts of anonymised routinely collected health record data. We are now additionally linking genetic data. PsyCymru aims to create a research platform and infrastructure for psychosis research in Wales by the establishment of two cohorts. The first is a well characterised clinically-assessed cohort of 490 individuals aged 16 and over, including genetic data. Consented individuals underwent a structured interview using a series of well-validated questionnaires and gave blood for the purpose of DNA extraction for sequencing and candidate gene identification. This data was linked to routinely collected health and social datasets with identity encryption used to protect privacy. The second is a much larger (12,097 individuals) but less well characterised population-based e-cohort of prevalent psychosis cases created using a previously validated algorithm applied to anonymised routine data. Both cohorts can be tracked prospectively and retrospectively using anonymised routinely collected electronic health and administrative data in the Secure Anonymised Information Linkage (SAIL) databank. This unique platform pools data together from multiple sources; linking clinical, psychological, biological, genetic and health care factors to address a wide variety of research questions. This resource will continue to expand over the coming years in size, breadth and depth of data, with continued recruitment and additional measures planned. [ABSTRACT FROM AUTHOR]

Introduction: People with Multiple Sclerosis are known to have a relatively high prevalence of both anxiety and depression. Studies of the relationship between physical disability and mental health in people with MS have reported mixed results, showing the need for further work. Methods: Between May 2011 and April 2012, 4516 people completed the MSIS-29 (v.1) and HADS scales via the dedicated internet site of the UK MS Register within a 7 day time window. These responses were linked with basic demographic and descriptive data and analysed in SPSS (v.20). Results: The proportions of people experiencing anxiety or depression increased with physical disability such that 38.0% of respondents with low, and 66.7% with high disability reported at least mild anxiety, and 17.1% of people with low, and 71.7% with high disability experienced at least mild depression. The multiple regression model explained 18.4% of the variance in anxiety with MSIS-29-PHYS score being the strongest predictor of anxiety. The model for depression explained 37.8% of the variance with MSIS-29-PHYS score being the strongest predictor. Some of the other variables included showed negative associations with anxiety and depression, indicating that the influence of physical disability on mental wellbeing could be underestimated. Conclusions: This study indicates that there is a positive relationship between physical disability and anxiety and depression, that physical disability impacts on anxiety and depression to differing extents, and that the effects vary with gender, age, disease course and disease duration. We have shown that physical disability is a predictor of anxiety and depression, and that other factors may mask the extent of this effect. Whether the causes of anxiety and depression are reactive, organic or a combination, it is essential that mental wellbeing is given due attention in caring for people with MS so that all their health needs can be met. [ABSTRACT FROM AUTHOR]

Background: This review determined the most commonly used, and reliable, measures for assessing clinical outcomes for multiple sclerosis (MS). Objectives: It was anticipated that this would facilitate the development of a common set of metrics, and aid reaching a consensus regarding the outcome measures that are typically used in the field of MS clinical research. Major findings: A thorough literature review of clinical outcome measures for MS produced 166 measures that have been used in this context. This list was then refined by discussion with a panel of consultant neurologists, which reduced the list to 23 commonly employed tools. This shortlist was then further refined through surveying 41 centres for MS treatment, which reduced the shortlist to 16 measures. The properties of these scales, in terms of their symptom/function domains, their specificity for MS, their administration characteristics, and their reliability and validity for MS, are all discussed. Conclusions: Conclusions regarding the development of potential sets of assessment measures for MS, which encompass broad symptom/function domains, and which are sensitive to the practical requirements of administration within clinical contexts, are explored. [ABSTRACT FROM AUTHOR]

Highlights: [•] A qualitative dimension to understanding users’ desires regarding, and expectations of, health registers. [•] That there is a difference between what users think health registers would be used for, and how they want them to be used. [•] Users wish for social contact, exchange, and networking functions, from a health register. [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]

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. [ABSTRACT FROM AUTHOR]

In order to fully understand and explore the effectiveness of any intervention for the management of multiple sclerosis (MS), it is important to have robust, valid, reliable, and universally applied measures. The recent article, ‘Disability outcome measures in multiple sclerosis clinical trials’ by Cohen, Reingold, Polman and Wolinsky (2012), explores this issue in regards to the effective measurement of MS-related disability, and the utilisation of patient-reported outcome measures, whilst highlighting the need for collaboration between the academic and clinical communities. Although it is important to examine disability measures, it is also equally important to recognise that physical function is only one aspect of a person’s experience; for example, quality of life and psychological well-being are also important aspects to assess. The application of e-health technologies and patient registers could be a useful method of gaining additional information, using patient-reported outcomes. This commentary explores these issues in relation to points raised by the Cohen et al. paper. [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]