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BackgroundClinical free-text data (eg, outpatient letters or nursing notes) represent a vast, untapped source of rich information that, if more accessible for research, would clarify and supplement information coded in structured data fields. Data usually need to be deidentified or anonymized before they can be reused for research, but there is a lack of established guidelines to govern effective deidentification and use of free-text information and avoid damaging data utility as a by-product. ObjectiveThis study aimed to develop recommendations for the creation of data governance standards to integrate with existing frameworks for personal data use, to enable free-text data to be used safely for research for patient and public benefit. MethodsWe outlined data protection legislation and regulations relating to the United Kingdom for context and conducted a rapid literature review and UK-based case studies to explore data governance models used in working with free-text data. We also engaged with stakeholders, including text-mining researchers and the general public, to explore perceived barriers and solutions in working with clinical free-text. ResultsWe proposed a set of recommendations, including the need for authoritative guidance on data governance for the reuse of free-text data, to ensure public transparency in data flows and uses, to treat deidentified free-text data as potentially identifiable with use limited to accredited data safe havens, and to commit to a culture of continuous improvement to understand the relationships between the efficacy of deidentification and reidentification risks, so this can be communicated to all stakeholders. ConclusionsBy drawing together the findings of a combination of activities, we present a position paper to contribute to the development of data governance standards for the reuse of clinical free-text data for secondary purposes. While working in accordance with existing data governance frameworks, there is a need for further work to take forward the recommendations we have proposed, with commitment and investment, to assure and expand the safe reuse of clinical free-text data for public benefit.

BackgroundResearch using genomic data opens up new insights into health and disease. Being able to use the data in association with health and administrative record data held in safe havens can multiply the benefits. However, there is much discussion about the use of genomic data with perceptions of particular challenges in doing so safely and effectively. ObjectiveThis study aimed to work toward a risk-utility data governance framework for research using genomic and phenotypic data in an anonymized form for research in safe havens. MethodsWe carried out a multifaceted review drawing upon data governance arrangements in published research, case studies of organizations working with genomic and phenotypic data, public views and expectations, and example studies using genomic and phenotypic data in combination. The findings were contextualized against a backdrop of legislative and regulatory requirements and used to create recommendations. ResultsWe proposed recommendations toward a risk-utility model with a flexible suite of controls to safeguard privacy and retain data utility for research. These were presented as overarching principles aligned to the core elements in the data sharing framework produced by the Global Alliance for Genomics and Health and as practical control measures distilled from published literature and case studies of operational safe havens to be applied as required at a project-specific level. ConclusionsThe recommendations presented can be used to contribute toward a proportionate data governance framework to promote the safe, socially acceptable use of genomic and phenotypic data in safe havens. They do not purport to eradicate risk but propose case-by-case assessment with transparency and accountability. If the risks are adequately understood and mitigated, there should be no reason that linked genomic and phenotypic data should not be used in an anonymized form for research in safe havens.

Data derived from the plethora of networked digital devices hold great potential for public benefit. Among these, mobile phone call detail records (CDRs) present novel opportunities for research and are being used in a variety of health geography studies. Research suggests that the public is amenable to the use of anonymized CDRs for research; however, further work is needed to show that such data can be used appropriately. This study works toward an ethically founded data governance framework with social acceptability. Using a multifaceted approach, this study draws upon data governance arrangements in published health research using CDRs, with a consideration of public views and the public’s information expectations from mobile network operators, and data use scenarios of CDRs in health research. The findings were considered against a backdrop of legislative and regulatory requirements. CDRs can be used at various levels of data and geographic granularity and may be integrated with additional, publicly available or restricted datasets. As such, there may be a significant risk of identity disclosure, which must be mitigated with proportionate control measures. An indicative relative risk of the disclosure model is proposed to aid this process. Subsequently, a set of recommendations is presented, including the need for greater transparency, accountability, and incorporation of public views for social acceptability. This study addresses the need for greater clarity and consistency in data governance for CDRs in health research. While recognizing the need to protect commercial interests, we propose that these recommendations be used to contribute toward an ethically founded practical framework to promote the safe, socially acceptable use of CDR data for public benefit. This pattern needs to be repeated for the appropriate use of new and emerging data types from other networking devices and the wider internet of things.

BackgroundMobile phone call detail records (CDRs) are increasingly being used in health research. The location element in CDRs is used in various health geographic studies, for example, to track population movement and infectious disease transmission. Vast volumes of CDRs are held by multinational organizations, which may make them available for research under various data governance regimes. However, there is an identified lack of public engagement on using CDRs for health research to contribute to an ethically founded framework. ObjectiveThis study aimed to explore public views on the use of call detail records in health research. MethodsViews on using CDRs in health research were gained via a series of three public workshops (N=61) informed by a pilot workshop of 25 people. The workshops included an initial questionnaire to gauge participants’ prior views, discussion on health research using CDRs, and a final questionnaire to record workshop outcome views. The resulting data were analyzed for frequencies and emerging themes. ResultsAt the outset, most participants (66%, 40/61) knew that location data were collected by operators, but only 3% (2/61) knew they were being used for health research. Initially, the majority of the participants (62%, 38/61) was content for their anonymous CDRs to be used, and this increased (80%, 49/61) after the discussion explained that safeguards were in place. Participants highlighted that terms and conditions should be clearer, as should information to phone users on data collection, privacy safeguards, sharing, and uses in research. ConclusionsThis is the first known study exploring public views of using mobile phone CDRs in health research. It revealed a lack of knowledge among the public on uses of CDRs and indicated that people are generally amenable to the use of anonymized data for research, but they want to be properly informed and safeguarded. We recommend that public views be incorporated into an ethically founded framework for the use of CDRs in health research to promote awareness and social acceptability in data use.

BackgroundCall detail records (CDRs) are collected by mobile network operators in the course of providing their service. CDRs are increasingly being used in research along with other forms of big data and represent an emerging data type with potential for public good. Many jurisdictions have infrastructures for health data research that could benefit from the integration of CDRs with health data. ObjectiveThe objective of this study was to review how CDRs have been used in health research and to identify challenges and potential opportunities for their wider use in conjunction with health data. MethodsA literature review was conducted using structured search terms making use of major search engines. Initially, 4066 items were identified. Following screening, 46 full text articles were included in the qualitative synthesis. Information extracted included research topic area, population of study, datasets used, information governance and ethical considerations, study findings, and data limitations. ResultsThe majority of published studies were focused on low-income and middle-income countries. Making use of the location element in CDRs, studies often modeled the transmission of infectious diseases or estimated population movement following natural disasters with a view to implementing interventions. CDRs were used in anonymized or aggregated form, and the process of gaining regulatory approvals varied with data provider and by jurisdiction. None included public views on the use of CDRs in health research. ConclusionsDespite various challenges and limitations, anonymized mobile phone CDRs have been used successfully in health research. The use of aggregated data is a safeguard but also a further limitation. Greater opportunities could be gained if validated anonymized CDRs were integrated with routine health records at an individual level, provided that permissions and safeguards could be put in place. Further work is needed, including gaining public views, to develop an ethically founded framework for the use of CDRs in health research.

Objective: This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. Methods: We linked whole‐exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)‐derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom. Results: We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty‐six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure‐free. There was no significant difference between the outcome groups in terms of the exome‐wide and gene‐based burden of rare and deleterious genetic variants. Significance: We successfully uploaded, annotated, and linked genetic sequence data and NLP‐derived seizure frequency data to anonymized health care records in this proof‐of‐concept study. We did not detect a genetic influence on real‐world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes. [ABSTRACT FROM AUTHOR]

This article outlines the value of administrative data for family justice research. Although socio-legal scholars have extended their research beyond purely theoretical or doctrinal analyses, studies using large-scale digital datasets remain few in number. As new opportunities arise to link large-scale administrative datasets across health, education, welfare and justice, it is vital that the community of family justice researchers and analysts are supported to deliver research based on entire service or family court populations. In this context, this article provides a definition of administrative data, before outlining the potential of single, linked or blended administrative data sets for family justice research. The remaining sections of the article speak to questions that are pertinent to this particular academic community, including the distinctive contribution of the socio-legal scholar to interdisciplinary teams and the place of data providers in collaborative research. Drawing on the sociological concept of 'publics', the final section considers the multiple interest groups whose social licence must be secured, when personal records are used to understand the relationship between law and family life. [ABSTRACT FROM AUTHOR]

Abstract 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 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 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 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 record-linkage 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.

The concept of precision medicine aims to tailor treatment based on data unique to the patient. An example is the use of genetic data from malignant tumours to select the most appropriate oncological treatment. The competing interests of utilitarianism and egoism create dilemmas for decisions regarding investment in precision medicine. The need to balance the perceived rights and needs of individuals against those of society as a whole is an on-going challenge in the distribution of limited health service resources. There is need for proper planning, organisation and investment into precision medicine to cope with the consequences of both direct-to-consumer and healthcare-directed genetic testing for genetic counselling, therapeutics and diagnostic networks. Consideration needs to be given to providing adequate time and training to allow for meaningful shared decision-making with patients and there is a strong case in support of a hub-and-spoke model to provide rapid, solid tumour genetic mutational analysis to prevent patients missing out on beneficial treatments. [ABSTRACT FROM AUTHOR]

Introduction Child maltreatment involves acts of omission (neglect) or commission (abuse) often by caregivers that results in potential or actual harm to a child. The Building Blocks trial (ISRCTN23019866) assessed the short-term impact of an intensive programme of antenatal and postnatal visiting by specially trained nurses to support young pregnant women in England. The Building Blocks: 2-6 Study will assess the medium-term impacts of the programme for mothers and children (n=1562), through the linkage of routinely collected data to the trial data, with a particular emphasis on the programme's impact on preventing child maltreatment. Methods and analysis We have developed a bespoke model of data linkage whereby outcome data for the trial cohort will be retrieved by linked anonymous data abstraction from NHS Digital, Office for National Statistics and the Department for Education's National Pupil Database. Participants will be given reasonable opportunity to opt out of this study prior to data transfer. The information centres will match participants to the information held in their databases using standard identifiers and send extracts to a third-party safe haven. The study will have 80% power to detect a 4% difference (4%vs8%) for the binary primary outcome of child in need status (from birth to key stage 1) at a two-sided 5% alpha level by following up 602 children in each trial arm. Analysis will be by intention to treat using logistic multilevel modelling. A cost-and-consequences analysis will extend the time frame of the economic analysis from the original trial. Ethics and dissemination The study protocol has been approved by the National Health Service Wales Research Ethics Committee and the Health Research Authority's Confidentiality Advisory Group. Methods of innovative study design and findings will be disseminated through peer-reviewed journals and conferences; results will be of interest to clinical and policy stakeholders in the UK. [ABSTRACT FROM AUTHOR]

Although inequalities in health and socioeconomic status have an important influence on childhood educational performance, the interactions between these multiple factors relating to variation in educational outcomes at micro-level is unknown, and how to evaluate the many possible interactions of these factors is not well established. This paper aims to examine multi-dimensional deprivation factors and their impact on childhood educational outcomes at micro-level, focusing on geographic areas having widely different disparity patterns, in which each area is characterised by six deprivation domains (Income, Health, Geographical Access to Services, Housing, Physical Environment, and Community Safety). Traditional health statistical studies tend to use one global model to describe the whole population for macro-analysis. In this paper, we combine linked educational and deprivation data across small areas (median population of 1500), then use a local modelling technique, the Takagi-Sugeno fuzzy system, to predict area educational outcomes at ages 7 and 11. We define two new metrics, “Micro-impact of Domain” and “Contribution of Domain”, to quantify the variations of local impacts of multidimensional factors on educational outcomes across small areas. The two metrics highlight differing priorities. Our study reveals complex multi-way interactions between the deprivation domains, which could not be provided by traditional health statistical methods based on single global model. We demonstrate that although Income has an expected central role, all domains contribute, and in some areas Health, Environment, Access to Services, Housing and Community Safety each could be the dominant factor. Thus the relative importance of health and socioeconomic factors varies considerably for different areas, depending on the levels of each of the other factors, and therefore each component of deprivation must be considered as part of a wider system. Childhood educational achievement could benefit from policies and intervention strategies that are tailored to the local geographic areas' profiles. [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: 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: 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]

We describe and reflect on the work of a Consumer Panel for a data linkage research unit in Wales, and show how the members are inputting into plans for the future. Our work is centred on conducting health-related data linkage research using anonymously linked, routinely collected data from across Wales via the Secure Anonymous Information Linkage system. In recognition of the importance of including patients and the public in health-related research, we have established a Consumer Panel to strengthen this voice in our work, and there are currently 10 members (4 men and 6 women) from across Wales, with a range of health-related areas of interest. A review of Panel activities was carried out after the first year, and all members were invited to provide their views via a questionnaire survey using structured and free-text responses. Initial feedback, obtained after the first meeting, was tentatively positive, and the questionnaire survey identified practical measures for improvement and future work. We have found the Consumer Panel to be a valuable addition to our work in the rapidly growing area of data linkage research. The views of Panel members provide a positive outlook and a fresh, and sometimes unexpected, perspective on various issues. The lessons we have learned, and our experience of involving the Panel in various aspects of our work, may be of value to others seeking to work with consumers in data linkage research, to researchers in general and to consumers themselves. [ABSTRACT FROM AUTHOR]

OBJECTIVES:To examine the incidence of Campylobacter and Salmonella infection in patients prescribed proton pump inhibitors (PPIs) compared with controls.METHODS:Retrospective cohort study using anonymous general practitioner (GP) data. Anonymised individual-level records from the Secure Anonymised Information Linkage (SAIL) system between 1990 and 2010 in Wales were selected. Data were available from 1,913,925 individuals including 358,938 prescribed a PPI. The main outcome measures examined included incidence of Campylobacter or Salmonella infection following a prescription for PPI.RESULTS:The rate of Campylobacter and Salmonella infections was already at 3.1-6.9 times that of non-PPI patients even before PPI prescription. The PPI group had an increased hazard rate of infection (after prescription for PPI) of 1.46 for Campylobacter and 1.2 for Salmonella, compared with baseline. However, the non-PPI patients also had an increased hazard ratio with time. In fact, the ratio of events in the PPI group compared with the non-PPI group using the prior event rate ratio was 1.17 (95% CI 0.74-1.61) for Campylobacter and 1.00 (0.5-1.5) for Salmonella.CONCLUSIONS:People who go on to be prescribed PPIs have a greater underlying risk of gastrointestinal (GI) infection beforehand and they have a higher prevalence of risk factors before PPI prescription. The rate of diagnosis of infection is increasing with time regardless of PPI use, and there is no evidence that PPI is associated with an increase in diagnosed GI infection. It is likely that factors associated with the demographic profile of the patient are the main contributors to increased rate of GI infection for patients prescribed PPIs. [ABSTRACT FROM AUTHOR]

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]

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]

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: 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: Advancing the use of genomic data with routinely collected health data holds great promise for health care and research. Increasing the use of these data is a high priority to understand and address the causes of disease.Objective: This study aims to provide an outline of the use of genomic data alongside routinely collected data in health research to date. As this field prepares to move forward, it is important to take stock of the current state of play in order to highlight new avenues for development, identify challenges, and ensure that adequate data governance models are in place for safe and socially acceptable progress.Methods: We conducted a literature review to draw information from past studies that have used genomic and routinely collected data and conducted interviews with individuals who use these data for health research. We collected data on the following: the rationale of using genomic data in conjunction with routinely collected data, types of genomic and routinely collected data used, data sources, project approvals, governance and access models, and challenges encountered.Results: The main purpose of using genomic and routinely collected data was to conduct genome-wide and phenome-wide association studies. Routine data sources included electronic health records, disease and death registries, health insurance systems, and deprivation indices. The types of genomic data included polygenic risk scores, single nucleotide polymorphisms, and measures of genetic activity, and biobanks generally provided these data. Although the literature search showed that biobanks released data to researchers, the case studies revealed a growing tendency for use within a data safe haven. Challenges of working with these data revolved around data collection, data storage, technical, and data privacy issues.Conclusions: Using genomic and routinely collected data holds great promise for progressing health research. Several challenges are involved, particularly in terms of privacy. Overcoming these barriers will ensure that the use of these data to progress health research can be exploited to its full potential. [ABSTRACT FROM AUTHOR]

This article discusses possible improvements to the Balanced Scorecard (BSC) management tool to develop and refine its use in a health care environment. The BSC is a measurement-based strategic management and learning system that is applicable in all organizations. It is used to translate an organization's vision into a set of performance indicators distributed among four perspectives. These are financial, customer, internal business process and learning and growth.

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]

Objectives: To investigate through survey and data linkage, healthcare resource use and costs (except drugs), including who bears the cost, of multiple sclerosis in the United Kingdom by disease severity and type. Methods: The United Kingdom Multiple Sclerosis Register deployed a cost of illness survey, completed by people with multiple sclerosis and linked this with data within the United Kingdom Multiple Sclerosis Register and from their hospital records. Resource consumption was categorised as being medical or non-medical and costed by National Health Service and social services estimates for 2018. Results: We calculated £509,003 in non-medical costs over a year and £435,488 in medical costs generated over 3 months. People with multiple sclerosis reported self-funding 75% of non-medical costs with non-medical interventions having long-term potential benefits. Costs increased with disability as measured by patient-reported Expanded Disability Status Score and Multiple Sclerosis Impact Scale, with Multiple Sclerosis Impact Scale physical being a more powerful predictor of costs than the patient-reported Expanded Disability Status Score. Two distinct groups were identified: medical and non-medical interventions (n = 138); and medical interventions only (n = 399). The medical and non-medical group reported increased disease severity and reduced employment but incurred 80% more medical costs per person than the medical-only group. Conclusions: The importance of disability in driving costs is illustrated with balance between medical and non-medical costs consistent with the United Kingdom health environment. People with multiple sclerosis and their families fund a considerable proportion of non-medical costs but non-medical interventions with longer term impact could affect future medical costs. [ABSTRACT FROM AUTHOR]

Background: The literature abounds with increasing numbers of research studies using genomic data in combination with health data (eg, health records and phenotypic and lifestyle data), with great potential for large-scale research and precision medicine. However, concerns have been raised about social acceptability and risks posed for individuals and their kin. Although there has been public engagement on various aspects of this topic, there is a lack of information about public views on data access models.Objective: This study aimed to address the lack of information on the social acceptability of access models for reusing genomic data collected for research in conjunction with health data. Models considered were open web-based access, released externally to researchers, and access within a data safe haven.Methods: Views were ascertained using a series of 8 public workshops (N=116). The workshops included an explanation of benefits and risks in using genomic data with health data, a facilitated discussion, and an exit questionnaire. The resulting quantitative data were analyzed using descriptive and inferential statistics, and the qualitative data were analyzed for emerging themes.Results: Respondents placed a high value on the reuse of genomic data but raised concerns including data misuse, information governance, and discrimination. They showed a preference for giving consent and use of data within a safe haven over external release or open access. Perceived risks with open access included data being used by unscrupulous parties, with external release included data security, and with safe havens included the need for robust safeguards.Conclusions: This is the first known study exploring public views of access models for reusing anonymized genomic and health data in research. It indicated that people are generally amenable but prefer data safe havens because of perceived sensitivities. We recommend that public views be incorporated into guidance on models for the reuse of genomic and health data. [ABSTRACT FROM AUTHOR]

The value of using population data to answer important questions for individual and societal benefit has never been greater. Governments and research funders world-wide are recognizing this potential and making major investments in data-intensive initiatives. However, there are challenges to overcome so that safe, socially-acceptable data sharing can be achieved. This paper outlines the field of population data science, the International Population Data Linkage Network (IPDLN), and their roles in advancing data-intensive research. We provide an overview of core concepts and major challenges for data-intensive research, with a particular focus on ethical, legal, and societal implications (ELSI). Using international case studies, we show how challenges can be addressed and lessons learned in advancing the safe, socially-acceptable use of population data for public benefit. Based on the case studies, we discuss the common ELSI principles in operation, we illustrate examples of a data scrutiny panel and a consumer panel, and we propose a set of ELSI-based recommendations to inform new and developing data-intensive initiatives.We conclude that although there are many ELSI issues to be overcome, there has never been a better time or more potential to leverage the benefits of population data for public benefit. A variety of initiatives, with different operating models, have pioneered the way in addressing many challenges. However, the work is not static, as the ELSI environment is constantly evolving, thus requiring continual mutual learning and improvement via the IPDLN and beyond. [ABSTRACT FROM AUTHOR]