A Rapid Electronic Cognitive Assessment Measure for Multiple Sclerosis: Validation of Cognitive Reaction, an Electronic Version of the Symbol Digit Modalities Test.

BACKGROUND: Incorporating cognitive testing into routine clinical practice is a challenge in multiple sclerosis (MS), given the wide spectrum of both cognitive and physical impairments people can have and the time that testing requires. Shortened paper and verbal assessments predominate but still are not used routinely. Computer-based tests are becoming more widespread; however, changes in how a paper test is implemented can impact what exactly is being assessed in an individual. The Symbol Digit Modalities Test (SDMT) is one validated test that forms part of the cognitive batteries used in MS and has some computer-based versions. We developed a tablet-based SDMT variant that has the potential to be ultimately deployed to patients' own devices. OBJECTIVE: This paper aims to develop, validate, and deploy a computer-based SDMT variant, the Cognition Reaction (CoRe) test, that can reliably replicate the characteristics of the paper-based SDMT. METHODS: We carried out analysis using Pearson and intraclass correlations, as well as a Bland-Altman comparison, to examine consistency between the SDMT and CoRe tests and for test-retest reliability. The SDMT and CoRe tests were evaluated for sensitivity to disability levels and age. A novel metric in CoRe was found: question answering velocity could be calculated. This was evaluated in relation to disability levels and age for people with MS and compared with a group of healthy control volunteers. RESULTS: SDMT and CoRe test scores were highly correlated and consistent with 1-month retest values. Lower scores were seen in patients with higher age and some effect was seen with increasing disability. There was no learning effect evident. Question answering velocity demonstrated a small increase in speed over the 90-second duration of the test in people with MS and healthy controls. CONCLUSIONS: This study validates a computer-based alternative to the SDMT that can be used in clinics and beyond. It enables accurate recording of elements of cognition relevant in MS but offers additional metrics that may offer further value to clinicians and people with MS.

Personal and societal costs of multiple sclerosis in the UK: A population-based MS Registry study.

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.

The Life Science Exchange: a case study of a sectoral and sub-sectoral knowledge exchange programme.

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.

The physical and psychological impact of multiple sclerosis using the MSIS-29 via the web portal of the UK MS Register.

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.

Protocol for a population-based ankylosing spondylitis (PAS) cohort in Wales.

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.

The SAIL Databank: building a national architecture for e-health research and evaluation.

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.

The SAIL databank: linking multiple health and social care datasets.

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.