Background: Fatigue has a major influence on the quality of life of people with multiple sclerosis. The Fatigue Severity Scale is a frequently used patient-reported measure of fatigue impact, but does not generate the health state utility values required to inform cost-effectiveness analysis, limiting its applicability within decision-making contexts. The objective of this study was to use statistical mapping methods to convert Fatigue Severity Scale scores to health state utility values from three preference-based measures: the EQ-5D-3L, SF-6D and Multiple Sclerosis Impact Scale-8D.

Methods: the relationships between the measures were estimated through regression analysis using cohort data from 1056 people with multiple sclerosis in South West England. Estimation errors were assessed and predictive performance of the best models were tested in a separate sample (n=352).

Results: for the EQ-5D and the Multiple Sclerosis Impact Scale-8D, the best performing models used a censored least absolute deviation specification, with Fatigue Severity Scale total score, age and gender as predictors. For the SF-6D, the best performing model used an ordinary least squares specification, with Fatigue Severity Scale total score as the only predictor.

Conclusions: Here we present algorithms to convert Fatigue Severity Scales scores into health state utility values based on three preference-based measures. These values may be used to estimate quality adjusted life-years for use in cost-effectiveness analyses and to consider the health-related quality of life of people with multiple sclerosis, thereby informing health policy decisions.

INTRODUCTION: in the UK, alcohol use is the main driver of chronic liver disease and each year results in over 1 million unplanned hospital admissions and over 25 000 deaths from alcohol-related liver disease (ArLD). The only effective treatment to prevent progression of liver damage is reducing or ceasing alcohol consumption. Psychological and pharmacological therapies for alcohol misuse are ineffective in patients with ArLD. Functional imagery training (FIT) is a novel psychological therapy that builds on motivational interviewing techniques with multisensory imagery. This pilot trial aims to test the feasibility of training alcohol liaison nurses to deliver FIT therapy and of recruiting and retaining patients with ArLD and alcohol dependence to a randomised trial of FIT and treatment as usual (TAU) versus TAU alone. METHODS AND ANALYSIS: This is a randomised pilot trial of FIT and TAU versus TAU alone in 90 patients with ArLD and alcohol dependence admitted to one of four UK centres. The primary objectives are to estimate rates of screening, recruitment, randomisation, retention, adherence to FIT/TAU and a preliminary assessment of the FIT intervention in the ArLD population. Data from the pilot study will be used to finalise the design of a definitive randomised controlled trial to assess the effectiveness and cost-effectiveness of FIT. The proposed primary outcome measure for the definitive trial is self-reported alcohol use assessed using timeline follow-back. ETHICS AND DISSEMINATION: Research ethics approval was given by the Yorkshire and Humber-Bradford Leeds Research Ethics Committee (reference: 21/YH/0044). Eligible patients will be approached and written informed consent obtained prior to participation. Results will be disseminated through peer-reviewed open access journals, international conferences and a lay summary published on the Trials Unit website and made available to patient groups. TRIAL REGISTRATION NUMBER: ISRCTN41353774.

AbstractPurpose Research indicates that employment is beneficial for people with multiple sclerosis (MS). However, people with MS typically face reduced workforce participation compared to the general population. Using a discrete choice experiment (DCE) we explored which factors are most important in influencing employment choices of people with MS, and whether the relative importance of factors differs between subgroups. Methods Attributes and levels for the DCE were developed using a systematic literature review and public involvement techniques with people with MS. In an online survey, respondents were asked to choose between two hypothetical job scenarios described using six attributes. We used a large, national register (the UK MS Register), to recruit participants aged 18–64 years with a diagnosis of MS. Choice data were analysed using multinomial logit and latent class models. Results Analyses were based on responses from 2350 people with MS. The preferred model specification was a latent class model, with three classes of respondent. The relative importance of attributes varied between classes, with one giving the greatest weight to the impact of work on other aspects of their lives, the second to having supportive bosses and colleagues, and the third to job flexibility. The classes differed significantly in terms of age and gender, type of MS, and socio-economic status. Conclusions Significant heterogeneity was apparent among people with MS regarding the factors that influence their employment decisions. Attributes concerning the impact of work, attitudes in the workplace and job flexibility appear more influential than those concerning physical workplace adaptations.

Discussion of public and patient involvement (PPI) in health economics (HE) research is growing. There is much literature on PPI principles and standards, but little specifically regarding involving patients in HE research. Here, we outline "PACTS", a set of principles, developed with a PPI group, for considering patient involvement in HE research. Planning: Involvement is best built in to research plans from the outset. This includes setting specific goals for involvement activities, and clearly communicating the background and purpose of involvement. Approach selection: We describe two main approaches to involvement-discussion-based and task-based. Discussion-based approaches are useful for generating broad insights and revealing "unknown unknowns". Task-based approaches offer a more focused means of shedding light on "known unknowns". Continuous involvement: Involving patients throughout the research process and across a range of projects helps build expertise for patients and insight for HE researchers. Team building: Meaningful involvement creates a shared sense of ownership of the research and, over time, helps to develop a team ethos, enhancing the positive impacts of involvement. Sensitivity: HE research can be perceived as technical and impersonal. Addressing this requires sensitivity, clarity, and an honest and open approach. There is increased recognition that patient contributors are experts at providing a "lived experience" perspective, in the way that clinicians are experts at providing an overview of conditions and HEs are experts in the methodology of their discipline. We hope these "PACTS Principles" complement existing PPI approaches and provide a useful foundation for health economists considering patient involvement.

Abstract
. Background
. Symptoms arising from vestibular system dysfunction are observed in 49–59% of people with Multiple Sclerosis (MS). Symptoms may include vertigo, dizziness and/or imbalance. These impact on functional ability, contribute to falls and significant health and social care costs. In people with MS, vestibular dysfunction can be due to peripheral pathology that may include Benign Paroxysmal Positional Vertigo (BPPV), as well as central or combined pathology. Vestibular symptoms may be treated with vestibular rehabilitation (VR), and with repositioning manoeuvres in the case of BPPV. However, there is a paucity of evidence about the rate and degree of symptom recovery with VR for people with MS and vestibulopathy. In addition, given the multiplicity of symptoms and underpinning vestibular pathologies often seen in people with MS, a customised VR approach may be more clinically appropriate and cost effective than generic booklet-based approaches. Likewise, BPPV should be identified and treated appropriately.
.
. Methods/ design
. People with MS and symptoms of vertigo, dizziness and/or imbalance will be screened for central and/or peripheral vestibulopathy and/or BPPV. Following consent, people with BPPV will be treated with re-positioning manoeuvres over 1–3 sessions and followed up at 6 and 12 months to assess for any re-occurrence of BPPV. People with central and/or peripheral vestibulopathy will be entered into a randomised controlled trial (RCT). Trial participants will be randomly allocated (1:1) to either a 12-week generic booklet-based home programme with telephone support or a 12-week VR programme consisting of customised treatment including 12 face-to-face sessions and a home exercise programme. Customised or booklet-based interventions will start 2 weeks after randomisation and all trial participants will be followed up 14 and 26 weeks from randomisation. The primary clinical outcome is the Dizziness Handicap Inventory at 26 weeks and the primary economic endpoint is quality-adjusted life-years. A range of secondary outcomes associated with vestibular function will be used.
.
. Discussion
. If customised VR is demonstrated to be clinically and cost-effective compared to generic booklet-based VR this will inform practice guidelines and the development of training packages for therapists in the diagnosis and treatment of vestibulopathy in people with MS.
.
. Trial registration
. ISRCTN Number: 27374299
. Date of Registration 24/09/2018
. Protocol Version 15 25/09/2019
.

BACKGROUND: Huntington's Disease (HD) is a hereditary neurodegenerative disorder which affects individuals' ability to walk, talk, think, and reason. Onset is usually in the forties, there are no therapies currently available that alter disease course, and life expectancy is 10-20 years from diagnosis. The gene causing HD is fully penetrant, with a 50% probability of passing the disease to offspring. Although the impacts of HD are substantial, there has been little report of the quality of life of people with the condition in a manner that can be used in economic evaluations of treatments for HD. Health state utility values (HSUVs), used to calculate quality-adjusted life-years (QALYs), are the metric commonly used to inform such healthcare policy decision-making. OBJECTIVES: the aim was to report HSUVs for HD, with specific objectives to use European data to: (i) describe HSUVs by demographic and clinical characteristics; (ii) compare HSUVs of people with HD in the UK with population norms; (iii) identify the relative strength of demographic and clinical characteristics in predicting HSUVs. METHODS: European Huntington's Disease Network REGISTRY study data were used for analysis. This is a multi-centre, multi-national, observational, longitudinal study, which collects six-monthly demographic, clinical, and patient-reported outcome measures, including the SF-36. SF-36 scores were converted to SF-6D HSUVs and described by demographic and clinical characteristics. HSUVs from people with HD in the UK were compared with population norms. Regression analysis was used to estimate the relative strength of age, gender, time since diagnosis, and disease severity (according to the Total Function Capacity (TFC) score, and the UHDRS's Motor score, Behavioural score, and Cognition score) in predicting HSUVs. RESULTS: 11,328 questionnaires were completed by 5560 respondents with HD in 12 European countries. Women generally had lower HSUVs than men, and HSUVs were consistently lower than population norms for those with HD in the UK, and dropped with increasing disease severity. The regression model significantly accounted for the variance in SF-6D scores (n = 1939; F [7,1931] = 120.05; p 

Objective: in economic evaluation, health outcomes are commonly quantified using quality-adjusted life-years (QALYs) derived from the preferences of a sample of the general population. It can be argued that this approach ignores the preferences of people with experience of the condition, and that patient preferences have a place in the valuation of health outcomes. Here we report the estimation of a preference-based index for an existing condition-specific preference-based measure for multiple sclerosis (MS), the MSIS-8D, based on the preferences of people with MS. Study design: Internet time trade-off (TTO) survey, eliciting preferences from people with MS. Methods: We elicited preferences from a sample of people with MS (N = 1635) across 169 MSIS-8D health states, using the TTO technique. We fitted ordinary least squares and random effects models to the survey data to estimate values for all health states described by the MSIS-8D. Results: the new patient-derived index (the MSIS-8D-P) provides values ranging from 0.893 for the best possible health state to 0.138 for the worst state. The MSIS-8D-P exhibits good discriminative validity, identifying expected significant differences between groups based on presence/absence of MS, type of MS, and duration since diagnosis. Conclusions: the MSIS-8D-P index of values for MS-specific health states provides an opportunity to estimate QALYs based on patient preferences, for use in economic evaluations of treatments for MS. More broadly, it adds to the methods and data available to consider the health-related quality of life of people with MS to inform resource allocation and individual-level decisions regarding treatments for MS.

INTRODUCTION: Health state valuation is a key input in many economic evaluations that inform resource allocation across competing healthcare interventions. Empirical evidence has shown that, in preference elicitation surveys, respondents may value a health state differently if they are aware of the condition causing it ('labeling effects'). This study investigates the impact of including a multiple sclerosis (MS) label for valuation of MS health states. METHODS: Health state values for MS were elicited using two internet-based surveys in representative samples of the UK population ( n = 1702; n = 1788). In one survey respondents were not informed that health states were caused by MS. The second survey included a condition label for MS. Surveys were identical in all other ways. Health states were described using a MS-specific eight-dimensional classification system (MSIS-8D), and the time trade-off valuation technique was used. Differences between values for labeled and unlabeled states were assessed using descriptive statistics and multivariate regression methods. RESULTS: Adding a MS condition label had a statistically significant effect on mean health state values, resulting in lower values for labeled MS states v. unlabeled states. The data suggest that the MS label had a more significant effect on values for less severe states, and no significant effect on values for the most severe states. The inclusion of the MS label had a differential impact across the dimensions of the MSIS-8D. Across the MSIS-8D, predicted values ranged from 0.079 to 0.883 for unlabeled states, and 0.066 to 0.861 for labeled states. CONCLUSION: Differences reported in health state values, using labeled and unlabeled states, demonstrate that condition labels affect the results of valuation studies, and can have important implications in decision-analytic modelling and in economic evaluations.

BACKGROUND: Health state utility values (HSUVs) are required to calculate quality-adjusted life-years (QALYs). They are frequently derived from generic preference-based measures of health. However, such generic measures may not capture health attributes of relevance to specific conditions. In such cases, a condition-specific preference-based measure (CSPBM) may be more appropriate. OBJECTIVE: This systematic review aimed to identify all published accounts of developing CSPBMs to describe and appraise the methods used. METHOD: We undertook a systematic search (of Embase, MEDLINE, PsycINFO, Web of Science, the Cochrane Library, CINAHL, EconLit, ASSIA and the Health Management Information Consortium database) to identify published accounts of CSPBM development up to July 2015. Studies were reviewed to investigate the methods used to design classification systems, estimate HSUVs, and validate the measures. RESULTS: a total of 86 publications were identified, describing 51 CSPBMs. Around two-thirds of these were QALY measures; the remainder were designed for clinical decision making only. Classification systems for 33 CSPBMs were derived from existing instruments; 18 were developed de novo. HSUVs for 34 instruments were estimated using a 'composite' approach, involving statistical modelling; the remainder used a 'decomposed' approach based on multi-attribute utility theory. Half of the papers that described the estimation of HSUVs did not report validating their measures. CONCLUSION: Various methods have been used at all stages of CSPBM development. The choice between developing a classification system de novo or from an existing instrument may depend on the availability of a suitable existing measure, while the choice between a decomposed or composite approach appears to be determined primarily by the purpose for which the instrument is designed. The validation of CSPBMs remains an area for further development.

BACKGROUND: Increasingly, generic preference-based measures of health-related quality of life (HRQOL) are used to estimate quality-adjusted life-years to inform resource allocation decisions. Evidence suggests that generic measures may not be appropriate for multiple sclerosis (MS). OBJECTIVES: to report the first stage in the development of an MS-specific preference-based measure to quantify the impact of MS and its treatment: deriving a health state classification system, which is amenable to valuation, from the 29-item Multiple Sclerosis Impact Scale (MSIS-29), a widely used patient-reported outcome measure in MS. METHODS: the dimensional structure of the MSIS-29 was determined using factor analysis and a conceptual framework of HRQOL in MS. Item performance was assessed, using Rasch analysis and psychometric criteria, to enable the selection of one item to represent each dimension of HRQOL covered by the MSIS-29. Analysis was undertaken using a sample (N = 529) from a longitudinal study of people with MS. Results were validated by repeating the analysis with a second sample (N = 528). RESULTS: Factor analysis confirmed the two-subscale structure of the MSIS-29. Both subscales covered several conceptually independent dimensions of HRQOL. Following Rasch and psychometric analysis, an eight-dimensional classification system named the MSIS-8D was developed. Each dimension was represented by one item with four response levels. CONCLUSIONS: Combining factor analysis with conceptual mapping, and Rasch analysis with psychometric criteria, provides a valid method of constructing a classification system for an MS-specific preference-based measure. The next stage is to obtain preference weights so that the measure can be used in studies investigating MS.

BACKGROUND: Condition-specific measures are frequently used to assess the health-related quality of life of people with multiple sclerosis (MS). Such measures are unsuitable for use in economic evaluations that require estimates of cost per quality-adjusted life-year because they are not based on preferences. OBJECTIVES: to report the estimation of a preference-based single index for an eight-dimensional instrument for MS, the Multiple Sclerosis Impact Scale - Eight Dimensions (MSIS-8D), derived from an MS-specific measure of health-related quality of life, the 29-item Multiple Sclerosis Impact Scale (MSIS-29). METHODS: We elicited preferences for a sample of MSIS-8D states (n = 169) from a sample (n = 1702) of the UK general population. Preferences were elicited using the time trade-off technique via an Internet-based survey. We fitted regression models to these data to estimate values for all health states described by the MSIS-8D. Estimated values were assessed against MSIS-29 scores and values derived from generic preference-based measures in a large, representative sample of people with MS. RESULTS: Participants reported that the time trade-off questions were easy to understand. Observed health state values ranged from 0.08 to 0.89. The best-performing model was a main effects, random effects model (mean absolute error = 0.04). Validation analyses support the performance of the MSIS-8D index: it correlated more strongly than did generic measures with MSIS-29 scores, and it discriminated effectively between subgroups of people with MS. CONCLUSIONS: the MSIS-8D enables health state values to be estimated from the MSIS-29, adding to the methods available to assess health outcomes and to estimate quality-adjusted life-years for MS for use in health technology assessment and decision-making contexts.

BACKGROUND: Multiple sclerosis (MS) is a chronic neurological disorder, which can lead to a wide range of disabling symptoms. The condition has a significant negative impact on health-related quality of life, and the economic cost of the disease is substantial. Decision-making regarding treatments for MS, and particularly disease-modifying interventions, has been hampered by limitations in the data and evaluative framework for assessing their cost effectiveness. Whilst attention has been drawn to these weaknesses, the scope and extent of the challenges in this area have not been fully set out to date. AIMS: the aims of this review were to identify all published economic evaluations of MS treatments in order to provide a statement on the scope and characteristics of the cost-effectiveness literature in the area of MS and to provide a basis on which to suggest practical recommendations for future research to aid decision-making. METHOD: a systematic search was undertaken to identify economic evaluations of treatments for people with MS published in English up to December 2011. Included studies were reviewed to provide a comprehensive description of the characteristics of the currently applied framework for cost effectiveness in MS, with the following key methodological components considered: methods for estimating disease progression, the impact of treatment and health outcomes and costs associated with MS. RESULTS: Thirty-seven papers were identified. Most studies (n = 32) were model-based evaluations of disease-modifying drugs. All models used disability stages defined by the Expanded Disability Status Scale (EDSS) to characterise disease progression, and the impact of treatment was based on data from clinical trials and epidemiological cohorts. Outcomes were primarily based on quality-adjusted life-years (n = 22) and/or related to relapse (n = 14). Estimates for health state utility values (HSUVs), costs and the impact of treatment on the course of MS varied considerably between studies, depending on the data sources used and the methods used to incorporate data into models. The scope of the studies was narrow, with a sparsity of economic evaluations of symptomatic and/or non-pharmacological interventions; exclusion of direct non-medical, indirect and informal care costs from analyses; and a narrow view of the potential impact of treatment, concentrating on disability, according to the EDSS, and relapses. In addition, there were issues concerning how to capture losses in HSUVs due to relapses in a way that reflects their salience to people with MS, the wide variation in costs and outcomes from different sources and from potentially unrepresentative samples and modelling disease progression from natural history data from over 30 years ago. CONCLUSION: There are many complexities for those designing and reporting cost-effectiveness studies of treatments for MS. Analysts, and ultimately decision makers, face multiple data and methodological challenges. Policy makers, technology developers, clinicians, patients and researchers need to acknowledge and address these challenges and to consider recommendations that will improve the current scenario. There is a need for further research that can constructively inform decision-making regarding the funding of treatments for MS.

In England from 2002 to 2013, Primary Care Trusts (PCTs) were responsible for commissioning healthcare for their local populations. The NHS has recently undergone rapid organisational change whereby clinicians have assumed responsibility for local commissioning decisions. This change in commissioning arrangements alongside the current financial pressures facing the NHS provides an impetus for considering the use of technical prioritisation methods to enable the identification of savings without having a detrimental effect on the health of the population. This paper reports on the design and implementation of a technical prioritisation method termed PBMA applied within NHS Plymouth, an English PCT responsible for commissioning services for a population of approximately 270,000. We evaluated the effectiveness of the process, the extent to which it was appropriate for local healthcare commissioning and whether it identified budget savings. Using qualitative research methodology, we found the process produced clear strategic and operational priorities for 2010/11, providing staff with focus and structure, and delivered a substantial planned reduction in hospital activity levels. Participants expressed satisfaction with the process. NHS Plymouth adhered to the PBMA process, although concerns were raised about the evidence for some priorities, decibel rationing, and a lack of robust challenge at priority-setting meetings. Further work is required to enhance participants’ understanding of marginal analysis. Participants highlighted several external benefits, particularly in terms of cultural change, and felt the process should encompass the whole local health and social care community. This evaluation indicates that the prioritisation method was effective in producing priorities for NHS Plymouth, and that PBMA provides an appropriate method for allocating resources at a local level. In order for PBMA to identify savings, cultural and structural barriers to disinvestment must be addressed. These findings will interest other healthcare commissioners in developing their own approaches to priority-setting.