453 research outputs found

    Using a discrete choice experiment to estimate societal health state utility values

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    In this study we explore a novel application of the Discrete Choice Experiment (DCE) that resembles the Time Trade Off (TTO) task to estimate values on the health utility scale for the EQ-5D. The DCE is tested in a survey alongside the TTO in respondents largely representative of the Canadian general population. The study finds that the DCE is able to derive logical and consistent values for health states valued on the full health – dead scale. The DCE overcame some issues identified in the version of TTO currently used to value EQ-5D, notably whether to exclude respondents who fail to understand the task and incorporating values considered worse than dead without transformation. This has important implications for providing values that represent the preferences of all respondents

    Preparatory study for the revaluation of the EQ-5D tariff: methodology report.

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    BACKGROUND: EQ-5D is a widely used generic measure of health with a 'tariff', or preference weights, obtained from the general population, using time trade-off (TTO). PRET (Preparatory study for the Re-valuation of the EQ-5D Tariff project) contributes towards the methodology for its revaluation. METHODS: Stage 1 examined key assumptions typically involved in health-state valuations through a series of binary choice exercises, namely that health-state preferences are independent of (1) duration of the state; (2) whose health it is (i.e. perspective); (3) length of 'lead time' (a mechanism to value all states on the same scale, including those who are worse than being dead); (4) when health events take place (time preference); and (5) satisfaction associated with the state. Further topics addressed were (6) exhaustion of lead time in the worst state; (7) health-state valuation using discrete choice experiments (DCEs) with a duration attribute; and (8) binary choice administration of lead time - time trade-off (LT-TTO). Stage 1 consisted of an online survey with 6000 respondents. Stage 2 compared the results above to those of an identical survey conducted in 200 face-to-face computer-assisted personal interviews (CAPIs), covering topics (1) to (7). Stages 3 and 4 examined - in more detail and depth - issues taken from stage 1. Stage 3 consisted of CAPI surveys of a representative UK sample of 300, using examples of TTO, LT-TTO, and DCE with duration, each followed by extensive feedback questions. Stage 4 was a more intensive exercise involving a qualitative analysis of people's thought processes during both binary choice and iterative health-state valuation exercises. Data were collected through 'think-aloud' methods in 30 interviews of a convenience sample. RESULTS: Stage 1 found that health-state values are not independent of (1) duration of the state but there is no clear pattern; (2) whose health it is; (3) the duration of 'lead time' but there was no clear pattern; (4) when health events take place; or (5) satisfaction associated with the state. Furthermore, (6) exhaustion of lead time in the worst state was subject to substantial framing effects; (7) the five-level version of the EQ-5D (EQ-5D-5L) can be valued using DCE with duration as an attribute; and (8) binary choice LT-TTO can be administered in an online environment. Stage 2 found that although online surveys and CAPI surveys resulted in different compositions of respondents, at the aggregate, their responses to the experimental questions covering (1) to (7) above were not statistically significantly different from each other. Stages 3 and 4 found that TTO and LT-TTO were easier than DCE with duration; respondents did not necessarily trade across all attributes of EQ-5D; some respondents found it difficult to distinguish between the two worst levels of EQ-5D-5L, and some respondents may be thinking about the impact of their ill health on their family. CONCLUSIONS: In order for the National Institute for Health and Care Excellence to make the most appropriate decisions, the EQ-5D tariff needs to incorporate the latest understanding of health-state preferences. PRET contributed to the knowledge base on the conduct of health-state valuation studies. FUNDING: The Medical Research Council (MRC)-National Institute for Health Research (NIHR) Methodology Research Programme funded the PRET project (MRC ref. G0901500), and the EuroQol Group funded the PRET-AS project (Preparatory study for the Re-valuation of the EQ-5D Tariff project - Additional Sample) as an extension to the PRET project with formal agreement from the MRC

    The relationship between EQ-5D, HAQ and pain in patients with rheumatoid arthritis: further validation and development of the limited dependent variable, mixture model approach

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    Objective: To provide robust estimates of EQ-5D as a function of the Health Assessment Questionnaire (HAQ) and pain in patients with rheumatoid arthritis. Method: Repeated observations of patients diagnosed with RA in a US observational cohort (n=100,398 observations) who provided data on HAQ, pain on a visual analogue scale and the EQ-5D questionnaire. We use a bespoke mixture modelling approach to appropriately reflect the characteristics of the EQ-5D instrument and compare this to results from linear regression. Results: The addition of pain alongside HAQ as an explanatory variable substantially improves explanatory power. The preferred model is a four component mixture. Unlike the linear regression it exhibits very good fit to the data, does not suffer from problems of bias or predict values outside the feasible range. Conclusions: It is appropriate to model the relationship between HAQ and EQ-5D but only if suitable statistical methods are applied. Linear models underestimate the QALY benefits, and therefore the cost effectiveness, of therapies. The bespoke mixture model approach outlined here overcomes this problem. The addition of pain as an explanatory variable greatly improves the estimates

    Implausible states: prevalence of EQ-5D-5L states in the general population and its effect on health state valuation

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    The EQ-5D is made up of health state dimensions and levels, in which some combinations seem less “plausible” than others. If “implausible” states are used in health state valuation exercises, then respondents may have difficulty imagining them, causing measurement error. There is currently no standard solution: some valuation studies exclude such states, whereas others leave them in. This study aims to address 2 gaps in the literature: 1) to propose an evidence-based set of the least prevalent two-way combinations of EQ-5D-5L dimension levels and 2) to quantify the impact of removing perceived implausible states from valuation designs. For the first aim, we use data from 2 waves of the English General Practitioner Patient Survey (n = 1,639,453). For the second aim, we remodel a secondary data set of a Discrete Choice Experiment (DCE) with duration that valued EQ-5D-5L and compare across models that drop observations involving different health states: 1) implausible states as defined in the literature, 2) the least prevalent states identified in stage 1, and 3) randomly select states, alongside 4) a model that does not drop any observations. The results indicate that two-way combinations previously thought to be implausible actually exist among the general population; there are other combinations that are rarer, and removing implausible states from an experimental design of a DCE with duration leads to value sets with potentially different characteristics depending on the criterion of implausible states. We advise against the routine removal of implausible states from health state valuation studies

    Using Discrete Choice Experiment with duration to model EQ-5D-5L health state preferences: Testing experimental design strategies

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    Background: Discrete choice experiments incorporating duration can be used to derive health state values for EQ-5D-5L. Yet, methodological issues relating to the duration attribute and the optimal way to select health states remain. The aims of this study were to: test increasing the number of duration levels and choice sets where duration varies (aim 1); compare designs with zero and non-zero prior values (aim 2); and investigate a novel, two-stage design to incorporate prior values (aim 3). Methods: Informed by zero and non-zero prior values, two efficient designs were developed, each consisting of 120 EQ-5D-5L health profile pairs with one of six duration levels (aims 1 and 2). Another 120 health state pairs were selected, with one of six duration levels allocated in a second stage based on existing estimated utility of the states (aim 3). An online sample of 2,002 members of the UK general population completed 10 choice sets each. Differences across the regression coefficients from the three designs were assessed. Results: The zero prior value design produced a model with coefficients that were generally logically ordered, but the non-zero prior value design resulted in a set of less ordered coefficients where some differed significantly. The two-stage design resulted in ordered and significant coefficients. The non-zero prior value design may include more “difficult” choice sets, based on the proportions choosing each profile. Conclusions: There is some indication of compromised “respondent efficiency”, suggesting that the use of non-zero prior values will not necessarily result in better overall precision. It is feasible to design discrete choice experiments in two stages by allocating duration values to EQ-5D-5L health state pairs based on estimates from prior studies

    Respondent Understanding in Discrete Choice Experiments : A Scoping Review

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    Acknowledgements The authors would like to acknowledge the contributions of Brendan Mulhern, who gave feedback on the initial project proposal and helped with the full-text reviews, and Bernadette Carr, the librarian who gave assistance developing and implementing the search strategy. Funding During part of this project, Alison Pearce was supported by a University of Technology Sydney Chancellor’s Postdoctoral Research Fellowship and the University of Technology Sydney International Researcher Development Scheme. Mark Harrison is supported by a Michael Smith Foundation for Health Research Scholar Award 2017 (#16813), and holds the UBC Professorship in Sustainable Health Care, which, between 2014 and 2017, was funded by Amgen Canada, AstraZeneca Canada, Eli Lilly Canada, GlaxoSmithKline, Merck Canada, Novartis Pharmaceuticals Canada, Pfizer Canada, Boehringer Ingelheim (Canada), Hoffman-La Roche, LifeScan Canada, and Lundbeck Canada. The Health Economics Research Unit (HERU) receives funding from the Chief Scientist Office (CSO) of the Scottish Government Health and Social Care Directorates.Peer reviewedPublisher PD
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