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To reduce harm to the environment resulting from the production, use, and disposal of health technologies, there are different options for how health technology assessment (HTA) agencies can consider environmental information. We identified four approaches that HTA agencies can use to take environmental information into account in healthcare decision making and the challenges associated with each approach. Republishing data that is in the public domain or has been submitted to an HTA agency we term the “information conduit” approach. Analyzing and presenting environmental data separately from established health economic analyses is described as “parallel evaluation.” Integrating environmental impact into HTAs by identifying or creating new methods that allow clinical, financial, and environmental information to be combined in a single quantitative analysis is “integrated evaluation.” Finally, evidence synthesis and analysis of health technologies that are not expected to improve health-related outcomes but claim to have relative environmental benefits are termed “environment-focused evaluation.”

This article provides the context for the ambition outlined in the the National Institute for Health and Care Excellence (NICE) 2021–2026 strategy to ‘lead globally on the potential to include environmental impact data in its guidance to reduce the carbon footprint of health and care’. Anthropogenic environmental changes pose a catastrophic risk to human health, with potential to widen national and global health inequalities. Recognising the fact that NICE guidance influences the way health and care is delivered and its consequent environmental impact, NICE has included environmental sustainability among its strategic priorities. This article outlines the work underway to meet this sustainability agenda at NICE.

Healthcare systems account for a substantial proportion of global carbon emissions and contribute to wider environmental degradation. This scoping review aimed to summarize the evidence currently available on incorporation of environmental and sustainability considerations into health technology assessments (HTAs) and guidelines to support the National In stitute for Health and Care Excellence and analogous bodies in other jurisdictions developing theirown methods and processes. Overall, 7,653 articles were identified, of which 24 were included in this review and split into three key areas – HTA (10 studies), healthcare guidelines (4 studies), and food and dietary guidelines (10 studies). Methodological reviews discussed the pros and cons of different approaches to integrate environmental considerations into HTAs, including adjustments to conventional cost-utility analysis (CUA), cost–benefit analysis, and multicriteria decision analysis. The case studies illustrated the challenges of putting this into practice, such as lack of disaggregated data to evaluate the impact of single technologies and difficulty in conducting thorough life cycle assessments that consider the full environmental effects. Evidence was scant on the incorporation of environmental impacts in clinical practice and public health guidelines. Food and dietary guidelines used adapted CUA based on life cycle assessments, simulation modeling, and qualitative judgments made by expert panels. There is uncertainty on how HTA and guideline committees will handle trade-offs between health and environment, especially when balancing environmental harms that fall largely on society with health benefits for individuals. Further research is warranted to enable integration of environmental considerations into HTA and clinical and public health guidelines.

This study examines the comparative equivalence, feasibility and acceptability of video and in-person interviews in generating time trade-off (TTO) values. Sample participants in England were recruited using a blended approach of different methods and sampled based on age, gender, ethnicity, and index of multiple deprivation. Participants were randomly allocated to be interviewed either via video or in-person. Participants completed TTO tasks for the same block of 10 EQ-5D-5L health states using the EQ-VTv2 software. Feasibility, acceptability and equivalence was assessed across mode using: sample representativeness; participant understanding, engagement and feedback; participant preferred mode of interview; data quality; mean utility and distribution of values for each health state; and regression analyses assessing the impact of mode whilst controlling for participant characteristics. The video and in-person samples had statistically significant differences in ethnicity and income but were otherwise broadly similar. Video interviews generated marginally lower quality data across some criteria. Participant understanding and feedback was positive and similar across modes. TTO values were similar across modes; whilst mean in-person TTO values were lower for the more severe states, mode was insignificant in most regression analyses. There was no clear preference of mode across all participants, though the characteristics of participants preferring to be interviewed in-person or by video differs. Video and in-person TTO interviews were feasible, acceptable and generated good-quality data, though video interviews had lower quality data across some criteria. Whilst TTO values differed across modes for the more severe states, mode does not appear to be the cause. The study found that the characteristics of people preferring each mode differed, and this should be taken into account in future valuation studies since sample representativeness for some characteristics, and therefore potentially TTO values, could be affected by the choice of mode.

Objective To generate a value set for the Mexican adult general population to support and facilitate the inclusion of quality-adjusted life years (QALYs) into the health technology assessment process of the Mexican healthcare authorities. Methods A representative sample of the Mexican adult population stratified by age, sex and socio-economic status was used. Following version 2.0 of the EuroQol EQ-5D-5L valuation protocol, trained interviewers guided participants in completing composite time trade-off (cTTO) and discrete-choice experiment (DCE) tasks included in the EQ-VT software. Generalized least squares, Tobit and Bayesian models were used for cTTO data. The choice of value set model was based on criteria that included: theoretical considerations, parsimony, logical ordering of coefficients, and statistical significance. Results Based on quality control criteria and interviewer judgment, 1000 out of 1032 participants provided useable responses. Participants’ demographic characteristics were similar to the 2010 Mexican Population Census and followed the socioeconomic structure defined by the Mexican Association of Marketing Research and Public Opinion Agencies (AMAI). The predicted index values in the final cTTO model (a heteroscedastic censored model with Bayesian estimation) ranged from − 0.5960 to 1, with 19.7% of all predicted health state scores less than 0 (i.e., worse than dead). Conclusion This study has generated the first value set representing the stated preferences of the Mexican adult population for use in estimating QALYs. The resulting EQ-5D-5L value set is technically robust and will facilitate health economic analyses as well as quality-of-life studies. Supplementary Information The online version contains supplementary material available at 10.1007/s40258-021-00658-0.

Introduction Carer quality of life (QoL) can be included in economic evaluations and captured using EQ-5D. Traditional valuation tasks require participants to imagine living in a health state for a number of years, without being told what to consider. This pilot study sought to investigate whether participants implicitly consider the impact of the health state on others, and the extent to which this may impact health state valuations. Methods Composite time trade-off (TTO) interviews were conducted with a convenience sample. Each interview included a ‘traditional’ TTO exercise to value three health states, and a ‘combined’ TTO exercise, where participants valued the same health states again, having been informed that they would require a carer living in a particular health state. Qualitative feedback was collected after each exercise. Paired t-test comparisons of the utilities elicited in each exercise were made. Results Thirty-three participants enrolled in the pilot. Mean differences between exercises were not statistically significant and differed in direction, although considerable heterogeneity was observed in individual response trajectories. Overall, 36% (n = 12) of participants expressed an unprompted concern about being a burden on others in the traditional exercise, and 67% (n = 22) of participants would have responded differently had the carer been in full health in the combined exercise. Conclusion Providing contextual information about carers may impact valuations. Further research is required to better understand the reasons behind the variation in individual response trajectories observed in this pilot study. The insights from this study may be useful for informing the design of related future studies. Supplementary Information The online version contains supplementary material available at 10.1007/s41669-021-00270-x.

IntroductionInvolving and engaging the public is an essential step to engender trust and confidence in HTA organizations. In 2021 the National Institute for Health and Care Excellence (NICE) launched NICE Listens, a new programme of deliberative public engagement seeking to address topics that have complex social, moral, or ethical dimensions. Health inequalities (HI), defined as unfair and avoidable differences in health across populations, was the first topic. The aim was to understand how the public would like NICE to act in regard to HI. Despite repeated attempts to tackle HI in England, the gaps in life expectancy between the most and least deprived continue to widen. NICE has committed to addressing HI in its five-year strategy and NICE Listens forms part of a comprehensive engagement strategy to understand how best to do this.MethodsTwenty-eight (28) members of the public from across England took part in four iterative two-hour online workshops, held fortnightly in late 2021. They consisted of both plenary and breakout sessions and incorporated a range of stimuli including trade-off exercises and interview clips with HI experts.ResultsThe findings show clear public support for HI being a high priority for NICE, albeit with limits on how and when HI should be addressed. Actions towards reducing HI should focus on supporting a preventative and systemic response. Importantly, there is a need for a transparent process for incorporating HI within NICE guidance as well as rigorous staff training in understanding and addressing HI. Recommending technologies that benefit the majority even when not accessible for all is acceptable if there are clear plans to manage access gaps.ConclusionsReducing health inequalities should be a high priority for NICE and other HTA organizations. Organizations should seek to have clear processes for embedding HI in decision-making. Priority should be given to actions that focus on prevention of ill health and those that have wider system impacts.

IntroductionAssessing the cost utility of health technologies for pediatric patients requires robust utility values for child health states, but the methods for valuing these pediatric health states are much less established than those for valuing adult health states. This is partly because the elicitation of preferences for child health states poses many normative, ethical, and practical challenges.MethodsThis presentation examines the conceptual issues in the valuation of health states in children by addressing the following questions.(i)Normative theories of health state values: What are we attempting to elicit?(ii)Sources of preferences: Whose preferences should we elicit, and from which perspective?(iii)Valuation methodologies: How should we elicit preferences?(iv)Attaching different values to child and adult health: Is a lack of consistency problematic?To answer these questions, we used desk research (non-systematic literature reviews) and findings from a two-part workshop held in April 2021. The workshop included 25 participants with expertise in health economics, health state valuation, child health, health technology assessment (HTA) decision-making, and ethics.ResultsWe identified a lack of consensus on what is being elicited for both adults and children. Many HTA agencies recommend that the public be involved in utility generation exercises, but some criteria for defining who constitutes a member of the public exclude children. Of the many candidate sample types, perspectives, and methodologies, only a few were deemed relevant, acceptable, and feasible for use in the child health context. In addition, there were diverging views on whether it is possible to compare and integrate adult and child value sets with different properties.ConclusionsSeveral questions remain to be answered before the public and other stakeholders can have confidence in child health state valuation protocols. We propose a research agenda, including both empirical and conceptual work, to inform future methodological development and to help HTA agencies make recommendations about how child utility values should be generated.

IntroductionPatient preferences (PPs) are an important source of evidence in health technology assessment (HTA). However, a methodological framework to achieve their integration in decision-making is lacking. We aim to investigate the potential role of evaluative frameworks to integrate PP evidence into HTA and decision-making.MethodsWe undertook a scoping review to identify potential methodological frameworks to consider PP evidence in HTA and evidence of the acceptability of these frameworks for decision-makers. We searched PubMed, Cochrane, and the grey literature to identify relevant studies, reports, or guidance documents. We restricted our search to the use of PP rather than patient experience data and excluded articles solely relating to deliberative approaches.ResultsFrameworks identified as having the potential to integrate PP evidence included cost-utility analysis, cost-consequence analysis (CCA), the efficiency-frontier approach, and multi-criteria decision analysis. All have been used in various HTA contexts, but not necessarily for inclusion of PP evidence. Distinct benefits and challenges of integrating PP data were identified for each framework. These included the theoretical basis of the frameworks, their ability to consider non-health as well as health outcomes, and their ability to separate outcomes based on PPs from outcomes based on population preferences. There is limited evidence and no consensus on the application of these frameworks to consider PPs in HTA or on their acceptability for decision-makers. However, CCA has the advantage that it is both based on economic decision theory and it leaves patient preferences disaggregated from population preferences in an HTA.ConclusionsThe frameworks identified in this review offer potential approaches to systematically and transparently integrate PPs into HTA and decision-making. Based on the review findings, we propose a research agenda to explore the potential of CCA in particular. We anticipate that our findings will augment the recommendations of the Innovative Medicines Initiative PREFER project, which are expected to report in 2022.

Objectives:\ud There has been some debate about the choice of perspective and the age of the child considered when completing preference elicitation tasks in the 3-level version of EQ-5D-Y (EQ-5D-Y-3L) valuation protocol. This study aimed to clarify the impact on latent scale EQ-5D-Y-3L values of varying the age of the child experiencing the health state considered by respondents completing the discrete choice experiment (DCE) tasks of the protocol.\ud \ud Methods:\ud We conducted an online DCE with a representative sample of 1000 adults in the United Kingdom and 1000 adults in the United States. Respondents selected the health state they prefer from a series of DCE paired EQ-5D-Y-3L health state comparisons using their own perspective and that of a hypothetical child from the following age groups: “5-7 years old,” “8-10 years old,” “11-13 years old,” and “14-15 years old.” Data analysis was conducted using separate multinomial logit models for each perspective and country. We also estimated combined models including data from each possible pair of perspectives and used interactions between EQ-5D-Y-3L levels and perspective to determine whether any differences were statistically significant.\ud \ud Results:\ud No statistically significant differences in coefficients between perspectives were found in the United States. In the United Kingdom, there were differences between the own perspective and the 5 to 7 years old perspective (looking after myself level 3) and between the 5 to 7 years old perspective and the 8 to 10 years old perspective (usual activities level 3).\ud \ud Conclusions:\ud Our results suggest that there is minimal impact on latent scale values when using different ages of the hypothetical child in the current EQ-5D-Y-3L valuation protocol.

Background An important question in the valuation of children’s health is whether the preferences of younger individuals should be captured within value sets for measures that are aimed at them. This depends on whether younger individuals can complete valuation exercises and whether their preferences differ from those of adults. This study compared the preferences of adults and adolescents for EQ-5D-Y-3L health states using latent scale values elicited from a discrete choice experiment (DCE). Methods An online DCE survey, comprising 15 pairwise choices, was provided to samples of UK adults and adolescents (aged 11–17 y). Adults considered the health of a 10-year-old child, whereas adolescents considered their own health. Mixed logit models were estimated, and comparisons were made using relative attribute importance (RAI) scores and a pooled model. Results In total, 1000 adults and 1005 adolescents completed the survey. For both samples, level 3 in pain/discomfort was most important, and level 2 in self-care the least important, based on the relative magnitudes of coefficients. The RAI scores (normalized on self-care) indicated that adolescents gave less weight relative to adults to usual activities (1.18 v. 1.51; P < 0.05), pain/discomfort (1.77 v. 3.12; P < 0.01), and anxiety/depression (1.64 vs. 2.65; P < 0.01). The pooled model indicated evidence of differences between the two samples in both levels in pain/discomfort and anxiety/depression. Limitations The perspective of the DCE task differed between the 2 samples, and no data were collected to anchor the DCE data to generate value sets. Conclusions Adolescents could complete the DCE, and their preferences differed from those of adults taking a child perspective. It is important to consider whether their preferences should be incorporated into value sets.

Purpose ‘Bolt-on’ dimensions are additional items added to multi-attribute utility instruments (MAUIs) such as EQ-5D that measure constructs not included in the core descriptive system. The use of bolt-ons has been proposed to improve the content validity and responsiveness of the descriptive system in certain settings and health conditions. EQ-5D bolt-ons serve a particular purpose and thus satisfy a certain set of criteria. The aim of this paper is to propose a set of criteria to guide the development, assessment and selection of candidate bolt-on descriptors. Methods Criteria were developed using an iterative approach. First, existing criteria were identified from the literature including those used to guide the development of MAUIs, the COSMIN checklist and reviews of existing bolt-ons. Second, processes used to develop bolt-ons based on qualitative and quantitative approaches were considered. The information from these two stages was formalised into draft development and selection criteria. These were reviewed by the project team and iteratively refined. Results Overall, 23 criteria for the development, assessment and selection of candidate bolt-ons were formulated. Development criteria focused on issues relating to i) structure, ii) language, and iii) consistency with the existing EQ-5D dimension structure. Assessment and selection criteria focused on face and content validity and classical psychometric indicators. Conclusion The criteria generated can be used to guide the development of bolt-ons across different health areas. They can also be used to assess existing bolt-ons, and inform their inclusion in studies and patient groups where the EQ-5D may lack content validity.

Objectives To respond to the ‘quality assurance’ of the EQ-5D-5L value set for England study. Methods We provide a point-by-point response to the issues raised by the authors of the quality assurance paper, drawing on theoretical arguments, empirical analyses and practical considerations. Results We provide evidence to show that many of the points made by the authors of the quality assurance are misleading, suggest misunderstandings, or are irrelevant. Conclusions The modeling approaches which were used appropriately address the characteristics of the data and provide a reasonable representation of the average stated preferences of general public in England. We provide reflections on the conduct of stated preference studies, and suggestions for the way forward.

IntroductionA source of debate among the health technology assessment (HTA) community is what perspective should be taken in health economic evaluations. Many stakeholders advocate that a societal perspective is taken in order to include a comprehensive range of costs and outcomes and (in theory) make societally optimal decisions. The Second Panel on Cost-Effectiveness in Health and Medicine recommended that a societal perspective be presented alongside a health sector one. The Second Panel included environment as one item on its impact inventory—alongside productivity, education, and others—intended to support the use of a societal perspective. However, many HTA agencies, including the National Institute for Health and Care Excellence (NICE), have continued to use health sector-specific evaluations to inform decision-making. The presentation seeks to examine whether consideration of the environmental impact of healthcare requires/implies the formal adoption of a societal perspective in health economic analyses.MethodsThe presentation will provide an overview of the societal perspective, explaining how it differs from a health sector perspective and describing its main strengths and weaknesses. We then present policy analysis undertaken by NICE’s Science Policy and Research team to identify reasons for measuring environmental impact in HTAs and examine whether these align with the broader arguments for or against adopting a societal perspective in economic analyses.ResultsThree reasons for considering environmental impact are identified: (i) to support parallel policies which demand healthcare system transformation against emissions targets; (ii) to ensure planetary and human health, in the future as well as the present; and (iii) to offset future healthcare resource use. We show that only the third reason aligns with arguments related to the choice of perspective for economic analyses. Moreover, this reason is arguably better aligned to maintaining a (potentially modified) health sector perspective. The implications of the results will be discussed with reference to updating reimbursement decision-making frameworks, such as those used by NICE, to account for the environmental consequences of healthcare.

It is important that patient-reported outcome (PRO) measures used to assess cancer therapies adequately capture the benefits and risks experienced by patients, particularly when adverse event profiles differ across therapies. This study explores the case for augmenting preference-based utility measures to capture the impact of cancer treatment-related symptoms. Additional cancer treatment-related items could be specific (e.g., rash) or global. While specific items are easier to describe and understand, their use may miss rarer symptoms and those that are currently unknown but will arise from future medical advancements. The appropriate number of additional items, the independence of those items, and their impact on the psychometric properties of the core instrument require consideration. Alternatively, a global item could encompass all potential treatment-related symptoms, of any treatments for any disease. However, such an item may not be well understood by general public respondents in valuation exercises. Further challenges include the decision about whether to generate de novo value sets for the modified instrument or to map to existing tariffs. The fluctuating and transient nature of treatment-related symptoms may be inconsistent with the methods used in conventional valuation exercises. Fluctuating symptoms could be missed by sub-optimal measure administration timing. The addition of items also poses double-counting risks. In summary, the addition of treatment-related symptom items could increase the sensitivity of existing utility measures to capture known and unknown treatment effects in oncology, while retaining the core domains. However, more research is needed to investigate the challenges, particularly regarding valuation.

Like the rest of the world, the pandemic has reshaped the lives and livelihoods of scientists in the health economics and outcomes research community. Many investigators in health preference research reacted by conducting empirical studies to better understand the value of health and health-related alternatives affected by COVID-19. The group identified 18 health preference studies currently under review or ongoing. On 17 June 2020, the first COVID-19 health preference research roundtable was held as an open meeting of the minds, allowing a healthy exchange of ideas between these study teams and other attendees interested in the area. From that discussion, this summary characterizes the state of science for the broader scientific community and for regulators and other decision makers looking for preference evidence regarding COVID-19.

BACKGROUND: Differences in healthcare use could relate to differences in the values assigned health as well as to differences in access. We sought to establish whether there existed evidence of differences in values assigned health states between individuals with and without insurance in Ireland.METHODS: Using the EuroQol Valuation Technology (EQ-VT), EQ-5D-5 L valuation tasks were administered to a sample of 1160 residents of Ireland in 2015/16. Censored panel regression analyses were used to estimate the values assigned health states. Private insurance was entered among a range of covariates to explain health preferences as a binary variable. A range of confirmatory analyses were undertaken.RESULTS: In the primary analysis, possession of private health insurance was not a significant determinant of health preferences. Across a range of confirmatory analyses limited evidence of any difference in values related to health insurance emerged.CONCLUSIONS: Insurance status has been shown to be a significant determinant of healthcare utilization in Ireland after need has been controlled for. Our analysis provides no compelling evidence that meaningful differences exist in the values accorded health between those with and without health insurance.

Objectives Discrete choice experiments (DCEs) can be used to obtain latent scale values for the EQ-5D-Y, but these require anchoring at 0 = dead to meet the conventions of quality-adjusted life year (QALY) estimation. The primary aim of this study is to compare four preference elicitation methods for obtaining anchors for latent scale EQ-5D-Y values. Methods Four methods were tested: visual analogue scale (VAS), DCE (with a duration attribute), lag-time time trade-off (TTO) and the location-of-dead (LOD) approach. In computer-assisted personal interviews, UK general public respondents valued EQ-5D-3L health states from an adult perspective and EQ-5D-Y health states from a 10-year-old child perspective. Respondents completed valuation tasks using all four methods, under both perspectives. Results 349 interviews were conducted. Overall, respondents gave lower values under the adult perspective compared to the child perspective, with some variation across methods. The mean TTO value for the worst health state (33333) was about equal to dead in the child perspective and worse than dead in the adult perspective. The mean VAS rescaled value for 33333 was also higher in the child perspective. The DCE produced positive child perspective values and negative adult perspective values, though the models were not consistent. The LOD median rescaled value for 33333 was negative under both perspectives and higher in the child perspective. Discussion There was broad agreement across methods. Potential criteria for selecting a preferred anchoring method are presented. We conclude by discussing the decision-making circumstances under which utilities and QALY estimates for children and adults need to be commensurate to achieve allocative efficiency.

This last decade has been marked by significant advances in the development of cell and gene (C&G) therapies, such as gene targeting or stem cell-based therapies. C&G therapies offer transformative benefits to patients but present a challenge to current health technology decision-making systems because they are typically reviewed when clinical efficacy data are very limited and when there is uncertainty about the long-term durability of outcomes. These challenges are not unique to C&G therapies, but they face more of these barriers, reflecting the need for adapting existing value assessment frameworks. Still, C&G therapies have the potential to be cost-effective even at very high price points. The impact on healthcare budgets will depend on the success rate of pipeline assets and on the extent to which C&G therapies will expand to wider pathologies beyond rare or ultra-rare diseases. Getting pricing and reimbursement models right is important for incentivising research and development investment while not jeopardising the sustainability of healthcare systems. Payers and manufacturers therefore need to acknowledge each other’s constraints—limitations in the evidence generation on the manufacturer side, budget considerations on the payer side—and embrace innovative thinking and approaches to ensure timely delivery of therapies to patients. Several experts in health technology assessment and clinical experts have worked together to produce this publication and identify methodological and policy options to improve the assessment of C&G therapies, and make it happen better, faster and sustainably in the coming years.

Supplemental material, MDM-19-321_online_supp for Using EQ-5D Data to Measure Hospital Performance: Are General Population Values Distorting Patients’ Choices? by Nils Gutacker, Thomas Patton, Koonal Shah and David Parkin in Medical Decision Making

Objective Our objective was to develop a value set based on Irish utility values for the EuroQol 5-Dimension, 5-Level instrument (EQ-5D-5L). Methods The research design and data collection followed a protocol developed by the EuroQol Group. The EuroQol Valuation Technology (EQ-VT) software was administered using computer-assisted personal interviews to a representative sample of adults resident in Ireland between 2015 and 2016. Utility values were elicited using two stated-preference techniques: time trade-off (TTO) and discrete-choice experiment (DCE). Each respondent completed a valuation exercise in which the EQ-VT system randomly selected one block of ten TTO questions from ten blocks relating to a possible 86 health states. One block of seven DCE pairs from 28 blocks of a possible 196 pairs of health states were randomly selected to accompany this. The relationship between utility values and health states was analysed using a hybrid regression model that combined data from the TTO and DCE techniques and expressed these as a function of the health state presented to the individual. This model estimated coefficients for 20 dummy variables that characterised each health state in the EQ-5D-5L framework, with the lowest level of severity providing the reference category in each domain. The relationship between weighted and unweighted TTO and DCE analyses of main effects was analysed separately. Results Comparison of weighted and unweighted models revealed no substantive differences in results with respect to either DCE or TTO models. The unweighted hybrid model produced estimated effects, the ordering of which was intuitively consistent within each domain: lower levels of health were associated with lower utility values. Differences were evident between domains with respect to valuations; the disutility associated with conditions related to anxiety/depression and pain/discomfort was higher than for other domains. The decrement in utility associated with movement from the highest to the lowest level of health was 0.344 for mobility, 0.287 for self-care, 0.187 for usual activities, 0.510 for pain/discomfort and 0.646 for anxiety/depression. Discussion The results present the first value set based on the EQ-5D-5L framework for a representative sample of residents in Ireland. The set reveals a higher decrement in utility associated with anxiety/depression than with other domains of health. Caution is warranted in comparisons with other value sets. That said, those in England, the Netherlands, Uruguay and China reveal that, whereas Irish values are broadly consistent with respect to mobility, self-care and usual activities, residents of Ireland attach a higher decrement to pain/discomfort and anxiety/depression than do other populations. Electronic supplementary material The online version of this article (10.1007/s40273-018-0690-x) contains supplementary material, which is available to authorized users.

Background EQ-5D-5L valuation studies previously reported many inconsistent responses in time trade-off (TTO) data. A number of possible elements, including ordering effects of the valuation tasks, mistakes at the sorting question, and interviewers' (learning) effects, may contribute to their inconsistency. Objectives This study aimed to evaluate the effect of two modifications on consistency of TTO data in The Netherlands (NL) and Hong Kong (HK): (1) separating the valuation of the Better than Dead (BTD) and Worse than Dead (WTD) states; and (2) Implementation of feedback (FB) module by offering an opportunity to review TTO responses. Methods A crossover design with two study arms was used to test the effect of the modifications. In each jurisdiction, six interviewers were involved where half the interviewers started using the standard version, and the other half started with the split version. Each version was switched after every 25 (NL) or 30 (HK) interviews until 400 interviews were completed. Results In the NL and HK, 404 and 403 respondents participated, respectively. With the use of the FB module, the proportion of respondents with inconsistent responses was lowered from 17.8% to 10.6% ( P P = 0.003) in HK. The result of separating the valuation of BTD and WTD states was not straightforward because it reduced the inconsistency rate in NL but not in HK. Conclusions The results support implementation of the FB module to promote the consistency of the data. The separation of the BTD and WTD task is not supported.

© 2018, The Author(s). Background: Three EQ-5D value sets (EQ-5D-3L, crosswalk, and EQ-5D-5L) are now available for cost-utility analysis in the UK and/or England. The value sets’ characteristics differ, and it is important to assess the implications of these differences. Objective: The aim of this paper is to compare the three value sets. Methods: We carried out analysis comparing the predicted values from each value set, and investigated how differences in health on the descriptive system is reflected in the utility score by assessing the value of adjacent states. We also assessed differences in values using data from patients who completed both EQ-5D-3L and EQ-5D-5L. Results: The distribution of the value sets systematically differed. EQ-5D-5L values were higher than EQ-5D-3L/crosswalk values. The overall range and difference between adjacent states was smaller. In the patient data, the EQ-5D-5L produced higher values across all conditions and there was some evidence that the value sets rank different health conditions in a similar severity order. Conclusions: There are important differences between the value sets. Due to the smaller range of EQ-5D-5L values, the possible change in quality-adjusted life years (QALYs) might be reduced, but they will apply to both control and intervention groups, and will depend on whether the gain is in quality of life, survival, or both. The increased sensitivity of EQ-5D-5L may also favour QALY gains even if the changes in utility are smaller. Further work should assess the impact of the different value sets on cost effectiveness by repeating the analysis on clinical trial data.

© 2017 The Authors Health Economics Published by John Wiley & Sons Ltd. Value sets for the EQ-5D-5L are required to facilitate its use in estimating quality-adjusted life years. An international protocol has been developed to guide the collection of stated preference data for this purpose and has been used to generate EQ-5D-5L valuation data for England. The aim of this paper is report the innovative methods used for modelling those data to obtain a value set. Nine hundred and ninety-six members of the English general public completed time trade-off (TTO) and discrete choice experiment (DCE) tasks. We estimate models, with and without interactions, using DCE data only, TTO data only, and TTO/DCE data combined. TTO data are interpreted as both left and right censored. Heteroskedasticity and preference heterogeneity between individuals are accounted for. We use Bayesian methods in the econometric analysis. The final model is chosen based on the deviance information criterion (DIC). Censoring and taking account of heteroskedasticity have important effects on parameter estimation. For DCE data only, TTO data only, and DCE/TTO data combined, models with parameters for all dimensions and levels perform best, as judged by the DIC. Taking account of heterogeneity improves fit, and the multinomial model reports the lowest DIC. This paper presents approaches that suit observed characteristics of EQ-5D-5L valuation data and recognise respondents' preference heterogeneity. The methods described are potentially relevant to other value set studies.

© 2017, Springer-Verlag Berlin Heidelberg. Background: In health state valuation studies, health states are typically presented as a series of sentences, each describing a health dimension and severity ‘level’. Differences in the severity levels can be subtle, and confusion about which is ‘worse’ can lead to logically inconsistent valuation data. A solution could be to mimic the way patients self-report health, where the ordinal structure of levels is clear. We develop and test the feasibility of presenting EQ-5D-5L health states in the ‘context’ of the entire EQ-5D-5L descriptive system. Methods: An online two-arm discrete choice experiment was conducted in the UK (n = 993). Respondents were randomly allocated to a control (standard presentation) or ‘context’ arm. Each respondent completed 16 paired comparison tasks and feedback questions about the tasks. Differences across arms were assessed using regression analyses. Results: Presenting health states ‘in context’ can significantly reduce the selection of logically dominated health states, particularly for labels ‘severe’ and ‘extreme’ (χ2 = 46.02, p

It is often assumed by health economists that the principal objective of health care is to maximise population health. However, people may be willing to sacrifice overall health in order to direct resources towards high priority disease areas, such as cancer. This paper examines whether society is willing to pay more for cancer prevention and treatment than for other types of health care. The policy context in the UK, where special assessment criteria and funding arrangements are currently in place for certain cancer drugs, is described. Selected empirical studies that have examined the extent of public support for a ‘cancer premium' are then summarised and discussed. The evidence available is not sufficiently strong to conclude whether or not willingness to pay is higher for cancer prevention and treatment.

Introduction. Health utilities are widely used in health care. The distributions of utilities differ between countries; some countries more often report worse than dead health states, while mild states are valued more or less the same. We hypothesize that cultural values explain these country-related utility differences. Research Question. What is the effect of sociodemographic background, methodological factors, and cultural values on differences in health utilities? Methods and Analyses. Time tradeoff data from 28 EQ-5D valuation studies were analyzed, together with their sociodemographic variables. The dependent variable was (Formula presented.), the utility difference between mild and severe states. Country-specific cultural variables were taken from the World Values Survey. Multilevel models were used to analyze the effect of sociodemographic background, methodology (3L v. 5L), and cultural values on (Formula presented.). Intraclass correlation (ICC) for country variation was used to assess the impact of the predicting variables on the variation between countries. Results. Substantial variation in (Formula presented.) was found between countries. Adding cultural values did not reduce ICCs for country variation. Sociodemographic background variables were only weakly associated with (Formula presented.) and did not affect the ICC. (Formula presented.) was 0.118 smaller for EQ-5D-5L studies. Discussion. (Formula presented.) varies between countries. These differences were not explained by national cultural values. In conclusion, despite correction for various variables, utility differences between countries remain substantial and unexplained. This justifies the use of country-specific value sets for instruments such as the EQ-5D. Fil: Roudijk, Bram. Radboud University Medical Center; Países Bajos Fil: Donders, A. Rogier T.. Radboud University Medical Center; Países Bajos Fil: Stalmeier, Peep F. M.. Radboud University Medical Center; Países Bajos Fil: Luo, Nan. Radboud University Medical Center; Países Bajos Fil: Viney, Rosalie. Radboud University Medical Center; Países Bajos Fil: Andrade, Monica Viegas. Radboud University Medical Center; Países Bajos Fil: Gudex, Claire. Radboud University Medical Center; Países Bajos Fil: de Pouvourville, Gerard. Radboud University Medical Center; Países Bajos Fil: Greiner, Wolfgang. Radboud University Medical Center; Países Bajos Fil: Scalone, Luciana. Radboud University Medical Center; Países Bajos Fil: Tsuchiya, Aki. Radboud University Medical Center; Países Bajos Fil: Golicki, Dominik. Radboud University Medical Center; Países Bajos Fil: Ferreira, Pedro. Radboud University Medical Center; Países Bajos Fil: Prevolnik-Rupel, Valentina. Radboud University Medical Center; Países Bajos Fil: Badia, Xavier. Radboud University Medical Center; Países Bajos Fil: Hsieh, Ching-Lin. Radboud University Medical Center; Países Bajos Fil: Jelsma, Jennifer. Radboud University Medical Center; Países Bajos Fil: Santos, Marisa. Radboud University Medical Center; Países Bajos Fil: Xie, Feng. Radboud University Medical Center; Países Bajos Fil: Purba, Fredrick. Radboud University Medical Center; Países Bajos Fil: Ikeda, Shunya. Radboud University Medical Center; Países Bajos Fil: Shiroiwa, Takeru. Radboud University Medical Center; Países Bajos Fil: Stolk, Elly. Radboud University Medical Center; Países Bajos Fil: Jo, Min-Woo. Radboud University Medical Center; Países Bajos Fil: Ramos Goñi, Juan Manuel. Radboud University Medical Center; Países Bajos Fil: Augustovski, Federico Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentina Fil: Rey Ares, Lucila. Radboud University Medical Center; Países Bajos Fil: Devlin, Nancy. Radboud University Medical Center; Países Bajos Fil: Shah, Koonal. Radboud University Medical Center; Países Bajos Fil: Pattanaphesaj, Juntana. Radboud University Medical Center; Países Bajos Fil: Tongsiri, Sirinart. Radboud University Medical Center; Países Bajos

Background Global Engagement works with health partnerships to establish workforce and educational translation on a global scale to support the National Health Service (NHS). There is growing evidence on how international experiences (through volunteering, exchanges and placements) benefit the NHS through an innovative workforce that develops international best practice and promotes lifelong learning. Most of this evidence has been captured though surveys to returned international volunteers. However, there is limited evidence about how to quantify the value that returned international healthcare volunteers bring back to their country of residence. Methods This paper identifies the various benefits to the NHS from returned international healthcare volunteers. The outcomes from returned international volunteers, which have been identified as relevant form a NHS perspective, are linked to three key areas in a multisector analytical framework used by the World Bank to evaluate labour market programmes: (1) Investment climate and Infrastructure, (2) Labor market regulations and institutions, and (3) Education and skills development. The monetary value of these outcomes is quantified through productivity indices which capture the economic value that the achievement of these outcomes have on the quality of the NHS labor force. This model is applied to a dataset of international volunteers provided by the Global Engagement health partnerships. Results The results suggest that international volunteering generates average productivity gains of up to 37% for doctors and up to 62% for nurses. Average productivity gains estimated from health partnerships data vary depending on duration of volunteering periods and occupational category mix. Conclusions Our analysis offers a value for money rationale for international volunteering programmes purely from a domestic and NHS perspective. The valuation method considers only one of the aims of international volunteering programmes: the development of the existing and future NHS workforce. Broader benefits for health system strengthening at a global level are acknowledged but not accounted for. Overall, we conclude that if the acquisition of volunteering outcomes is realised, the NHS can accrue a productivity increase of between 24 and 41% per volunteer, with a value ranging from £13,215 to £25,934 per volunteer. Electronic supplementary material The online version of this article (10.1186/s12992-019-0473-y) contains supplementary material, which is available to authorized users.

OBJECTIVESEvidence suggests that, in specific circumstances, the EQ-5D is insensitive to changes or differences in health status. One possible solution is to add 'bolt-on' dimensions to the core EQ-5D dimensions, to provide additional information about the impact of certain conditions or symptoms on health. In this study, we developed EQ-5D-5L bolt-ons for cognition (5L-Cog) and vision (5L-Vis).METHODSThe development process involved three stages. First, systematic literature reviews were conducted for outcome measures used in cognitive impairment and visual impairment. Items were extracted from existing measures and mapped to a set of dimensions.Common terminology was also recorded. Second, we conducted focus groups in the UK with people who have experience of either impairment. Participants were encouraged to describe the impact of their own experience of cognitive impairment or visual impairment, with reference to dimensions and terminologies identified in the literature reviews. The findings were used to develop candidate 5L-Cog and 5L-Vis descriptors. Third, we conducted interviews in the UK and Australia with people who have experience of either impairment. Interviewees were asked to complete the EQ-5D-5L with candidate 5L-Cog or 5L-Vis descriptors,followed by cognitive debriefing.RESULTSCandidate descriptors related to dimensions such as memory (for 5L-Cog), visual acuity (for 5L-Vis), mood (for both), and social functioning (for both). Various terminologies were identified in the review, with 'problems', 'limitations', 'difficulties', and 'feelings' being used in both contexts. Focus group participants expressed preferences for different terms and identified problematic words.CONCLUSIONSQualitative research methods can be used to develop bolt-on descriptors for the EQ-5D that are meaningful to people with lived experience. However, it is challenging to identify a suitable range of participants where people with relevant lived experience constitute a heterogeneous population. In a subsequent phase of the study, 5L-Cog and 5L-Vis descriptors will be tested quantitatively.

To extend existing analyses of whether and how the age of respondents is related to their time trade-off (TTO) valuations of hypothetical EQ-5D-3L health states, and to contribute to the existing debate about the rationale and implications for using age-specific utilities in health technology assessment (HTA).We use data from the MVH UK valuation study. For each profile, the mean TTO value-adjusted by sex, education, self-reported health and personal experience of serious illness-is pairwise compared across the different age groups. A Bonferroni correction is applied to the multiple testing of significant differences between means. Smile plots illustrate the results. A debate regarding whether there is a case for using age-specific utilities in HTAs complements the analysis.Results show that the oldest respondents value health profiles lower than younger age groups, particularly for profiles describing problems in the mobility dimension.The findings raise the possibility of using age-specific value sets in HTAs, since a technology may not be cost-effective on average but cost-effective for a sub-group whose preferences are more closely aligned to the benefits offered by the technology.

The time trade-off (TTO) valuation technique is widely used to determine utility values of health outcomes to inform quality-adjusted life-year (QALY) calculations for use in economic evaluation. Protocols for implementing TTO vary in aspects such as the trade-off framework, iteration procedure and its administration model and method, training of respondents and interviewers, and quality control of data collection. The most widely studied and utilized TTO valuation protocols are the Measurement and Valuation of Health (MVH) protocol, the Paris protocol and the EuroQol Valuation Technology (EQ-VT) protocol, all developed by members of the EuroQol Group. The MVH protocol and its successor, the Paris protocol, were developed for valuation of EQ-5D-3L health states. Both protocols were designed for a trained interviewer to elicit preferences from a respondent using the conventional TTO framework with a fixed time horizon of 10 years and an iteration procedure combining bisection and titration. Developed for valuation of EQ-5D-5L health states, the EQ-VT protocol adopted a composite TTO framework and made use of computer technology to facilitate data collection. Training and monitoring of interviewers and respondents is a pivotal component of the EQ-VT protocol. Research is underway aiming to further improve the EuroQol protocols, which form an important basis for the current practice of health technology assessment in many countries.

Background Health states defined by multiattribute instruments such as the EuroQol five-dimensional questionnaire with five response levels (EQ-5D-5L) can be valued using time trade-off (TTO) or discrete choice experiment (DCE) methods. A key feature of the tasks is the order in which the health state dimensions are presented. Respondents may use various heuristics to complete the tasks, and therefore the order of the dimensions may impact on the importance assigned to particular states. Objective To assess the impact of different EQ-5D-5L dimension orders on health state values. Methods Preferences for EQ-5D-5L health states were elicited from a broadly representative sample of members of the UK general public. Respondents valued EQ-5D-5L health states using TTO and DCE methods across one of three dimension orderings via face-to-face computer-assisted personal interviews. Differences in mean values and the size of the health dimension coefficients across the arms were compared using difference testing and regression analyses. Results Descriptive analysis suggested some differences between the mean TTO health state values across the different dimension orderings, but these were not systematic. Regression analysis suggested that the magnitude of the dimension coefficients differs across the different dimension orderings (for both TTO and DCE), but there was no clear pattern. Conclusions There is some evidence that the order in which the dimensions are presented impacts on the coefficients, which may impact on the health state values provided. The order of dimensions is a key consideration in the design of health state valuation studies.

Background Three EQ-5D value sets (EQ-5D-3L, crosswalk, and EQ-5D-5L) are now available for cost-utility analysis in the UK and/or England. The value sets’ characteristics differ, and it is important to assess the implications of these differences. Objective The aim of this paper is to compare the three value sets. Methods We carried out analysis comparing the predicted values from each value set, and investigated how differences in health on the descriptive system is reflected in the utility score by assessing the value of adjacent states. We also assessed differences in values using data from patients who completed both EQ-5D-3L and EQ-5D-5L. Results The distribution of the value sets systematically differed. EQ-5D-5L values were higher than EQ-5D-3L/crosswalk values. The overall range and difference between adjacent states was smaller. In the patient data, the EQ-5D-5L produced higher values across all conditions and there was some evidence that the value sets rank different health conditions in a similar severity order. Conclusions There are important differences between the value sets. Due to the smaller range of EQ-5D-5L values, the possible change in quality-adjusted life years (QALYs) might be reduced, but they will apply to both control and intervention groups, and will depend on whether the gain is in quality of life, survival, or both. The increased sensitivity of EQ-5D-5L may also favour QALY gains even if the changes in utility are smaller. Further work should assess the impact of the different value sets on cost effectiveness by repeating the analysis on clinical trial data.

© 2017, © The Author(s) 2017. Background. Discrete Choice Experiments including duration (DCETTO) can be used to generate utility values for health states from measures such as EQ-5D-5L. However, methodological issues concerning the optimum way to present choice sets remain. The aim of the present study was to test a range of task presentation approaches designed to support the DCETTO completion process. Methods. Four separate presentation approaches were developed to examine different task features including dimension level highlighting, and health state severity and duration level presentation. Choice sets included 2 EQ-5D-5L states paired with 1 of 4 duration levels, and a third “immediate death” option. The same design, including 120 choice sets (developed using optimal methods), was employed across all approaches. The online survey was administered to a sample of the Australian population who completed 20 choice sets across 2 approaches. Conditional logit regression was used to assess model consistency, and scale parameter testing investigated poolability. Results. Overall 1,565 respondents completed the survey. Three approaches, using different dimension level highlighting techniques, produced mainly monotonic coefficients that resulted in a larger disutility as the severity level increased (excepting usual activities levels 2/3). The fourth approach, using a level indicator to present the severity levels, has slightly more non-monotonicity and produced larger ordered differences for the more severe dimension levels. Scale parameter testing suggested that the data cannot be pooled. Conclusions. The results provide information regarding how to present DCE tasks for health state valuation. The findings improve our understanding of the impact of different presentation approaches on valuation, and how DCE questions could be presented to be amenable to completion. However, it is unclear if the task presentation impacts online respondent engagement.

Background Standard methods for eliciting the preference data upon which ‘value sets’ are based generally have in common an aim to ‘uncover’ people’s preferences by asking them to evaluate a subset of health states, then using their responses to infer their preferences over all dimensions and levels. An alternative approach is to ask people directly about the relative importance to them of the dimensions, levels and interactions between them. This paper describes a new stated preference approach for directly eliciting personal utility functions (PUFs), and reports a pilot study to test its feasibility for valuing the EQ-5D. Methods A questionnaire was developed, designed to directly elicit PUFs from general public respondents via computer-assisted personal interviews, with a focus on helping respondents to reflect and deliberate on their preferences. The questionnaire was piloted in England. Results Seventy-six interviews were conducted in December 2015. Overall, pain/discomfort and mobility were found to be the most important of the EQ-5D dimensions. The ratings for intermediate improvements in each dimension show heterogeneity, both within and between respondents. Almost a quarter of respondents indicated that no EQ-5D health states are worse than dead. Discussion The PUF approach appears to be feasible, and has the potential to yield meaningful, well-informed preference data from respondents that can be aggregated to yield a value set for the EQ-5D. A deliberative approach to health state valuation also has the potential to complement and develop existing valuation methods. Further refinement of some elements of the approach is required. Electronic supplementary material The online version of this article (10.1007/s10198-018-0993-z) contains supplementary material, which is available to authorized users.

Table S1. Regression results for bivariate probit models with ‘Equal to Dead’ grouped with ‘Worse than Dead’. Table S2. Regression results for probit model with attitudes to euthanasia substituted for religiosity. (DOCX 23 kb)

Today's healthcare decision makers, including payers, patients, and doctors, face an increasingly large choice of new drug therapies and a greater need to understand the comparative safety, effectiveness and costs of available treatment options (1;2). Meanwhile, manufacturers are faced with a disconnect between the evidence requirements of regulatory agencies and payers, making it difficult to meet all demands. In the United States, drug efficacy trials for U.S. Food and Drug Administration (FDA) approval are usually not representative of real-world patient populations, often lacking appropriate comparators and assessing outcomes of limited relevance to payers (3–6). FDA trials can offer some insights into the relative efficacy of different drugs studied, however, regulations do not require comparative effectiveness research (CER) for new drugs (7), and the utility of results to decision makers remains unclear for studies that do compare alternative treatments (6). Evidence requirements, including appropriate comparators, are also inconsistent across European regulators, payers, and health technology assessment (HTA) bodies (8–11). While European HTA agencies still regard randomized controlled trials (RCTs) as the gold standard, many recognize some use for non-RCT data in HTA (12). As evidence requirements shift, the cost of bringing a new drug to market continues to rise (2). Simply adding CER/relative effectiveness (RE) studies on top of regulatory evidence is most likely unsustainable, and many worry the escalating costs of drug development may soon limit innovation (1). According to Schneeweiss et al. (5), the increasing demand from payers for CER evidence may slow the process of bringing new drugs to market, unless manufacturers can build in modifications to anticipate CER scenarios in the future. Given economic pressure on payers and providers to allocate health resources effectively and a growing demand for stakeholder-driven evidence, CER in the United States and RE research in Europe may play a critical role for future drug development to ensure coverage and competitive pricing of new drugs (1;3–5;13). We refer to CER and RE as defined by the Institute of Medicine (14) and High Level Pharmaceutical Forum (15), respectively, but use these terms interchangeably as CER/RE throughout this study. We also consider the role of patient-centered outcomes research (PCOR), tradeoffs between different CER/RE designs, and the reliability of existing methods for adjusting for bias in observational research, which remains a major challenge to its acceptability by payers (5;16–18). Our aim was to gather perspectives from a diverse group of payers on the rapidly evolving fields of CER/RE. In particular, we focused on the acceptability and use of CER/RE evidence for access decisions on new drugs in the future healthcare environments of the United States and Europe. We considered study designs and methods used or potentially useful for CER/RE, the extent to which they are used within the current paradigm of coverage decision making for new drugs, and how current trends might lead to greater (or less) acceptability by payers in 2020. We grounded our questions in hypothetical reference cases of products we expect payers to encounter frequently in the future to help identify conditions that might modify payers' evidentiary requirements.