مقایسه بین المللی در ارزش نهادن به EQ-5D ایالات سلامتی: نقد و بررسی و تجزیه و تحلیل

Objective To identify the key methodological issues in the construction of population-level EuroQol 5-dimensions (EQ-5D)/time trade-off (TTO) preference elicitation studies. Method This study involved three components. The first was to identify existing population-level EQ-5D TTO studies. The second was to illustrate and discuss the key areas of divergence between studies, including the international comparison of tariffs. The third was to portray the relative merits of each of the approaches and to compare the results of studies across countries. Results While most articles report use of the protocol developed in the original UK study, we identified three key areas of divergence in the construction and analysis of surveys. These are the number of health states valued to determine the algorithm for estimating all health states, the approach to valuing states worse than immediate death, and the choice of algorithm. The evidence on international comparisons suggests differences between countries although it is difficult to disentangle differences in cultural attitudes with random error and differences as a result of methodological divergence. Conclusions Differences in methods may obscure true differences in values between countries. Nevertheless, population-specific valuation sets for countries engaging in economic evaluation would better reflect cultural differences and are therefore more likely to accurately represent societal attitudes.

Cost-utility analysis (CUA), where outcomes are measured in terms of quality-adjusted life-years (QALYs), is the main approach used to measure and value the impacts of treatments. The US Panel on Cost-Effectiveness in Health and Medicine recommends the use of QALYs [1]; the UK National Institute of Health and Clinical Excellence has most commonly used CUA [2,3] and has recently recommended that it should be the preferred outcome measure; and CUA is increasingly used in Australia in the evaluation of pharmaceuticals and medical services. In the recently released PBAC guidelines, a preference is expressed for the use of CUA [4]. While CUA is simple in concept, it presents challenges in practice. QALYs are designed to allow comparisons across interventions with disparate outcomes across different health-care conditions and population groups. Eliciting valuations for all health states that may be relevant to a disease or intervention is time consuming and costly, and comparison of valuations across interventions and diseases requires comparability of methods. Multiattribute utility instruments (MAUIs), which comprise a generic descriptive quality of life instrument and a scoring algorithm that covers all health states described by the instrument (e.g., the EQ-5D, the Short Form-6 dimensions (SF-6D), Health Utilities Index, and Assessment of Quality of Life), have facilitated comparability [5,6]. The scoring algorithm for these instruments is usually generated from a stated preference experiment, typically time trade-off (TTO), standard gamble conducted in a population sample The key advantage of the MAU approach is that it provides community-based valuation of health states for patients who are experiencing the state. The role of MAUIs in economic evaluation is increasing. For example, the National Institute of Clinical Excellence has recommended the use of the EQ-5D, and the Pharmaceutical Benefits Advisory Committee in Australia has stated a preference for utility weights generated from the use of a MAUI in a clinical trial setting (without specifying a preference for a particular MAUI). Nevertheless, recent reviews have noted that there are significant differences in the performance of different MAUIs [7], which can be attributed to differences in the dimensions covered by the instruments, differences in preference elicitation techniques, and differences in the methods used to derive the scoring algorithm. These differences can have significant impact on valuations of health states and the resulting cost-effectiveness of interventions [8]. There has been relatively little critical appraisal of the methods of development of MAUIs scoring algorithms. In this article, we examine these issues by considering the EQ-5D [9]. We chose the EQ-5D because it is widely used, and there have been a number of different studies undertaken to develop country-specific scoring algorithms. Because the focus of this review is on one MAUI, we do not consider the psychometric aspects of the instrument but, rather, focus on the methods for development of the scoring algorithm. Many of the issues we raise are relevant to other MAUIs.

This article identifies a number of key methodological questions in the construction of population-level EQ-5D/TTO value sets. The number of states that need to be directly valued is considered, and the best solution may depend on whether it is worthwhile to look for interaction terms. We identified study design issues with the sets of states most commonly selected to be directly valued. The decision regarding number of states leads into a number of questions regarding the choice of algorithm. Then, we identified competing approaches for the valuation of states considered to be worse than death and identified that the approach used by Shaw et al. [20] makes valuations heavily dependent on a parameter of model design (specifically the minimum period of the state considered in the TTO) that should have no effect on the valuation. Whether country-specific algorithms are necessary is a difficult question that we have only partly addressed. There are clear divergences between countries in their valuations, in terms of both their willingness to trade quantity of life for quality and their relative importance of the five dimensions of the EQ-5D. Our findings indicate that a proportion of the divergences in algorithms are likely to be attributable to genuine cultural differences rather to than methodological differences between studies, which suggests that country-specific algorithms are of importance. This is particularly true in countries that engage in substantial economic evaluation such as Canada and Australia, which are currently reliant on using algorithms derived from countries asserted to be comparably similar in terms of attitude to health. Source of financial support: Financial support for this study was provided entirely by NHMRC Project Grant (403303). The funding agreement ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.