From a different angle: a novel approach to health valuation

Preference heterogeneity in health valuation: a latent class analysis of the Peru EQ-5D-5L values

BACKGROUND

Preference heterogeneity in health valuation has become a topic of greater discussion among health technology assessment agencies. To better understand heterogeneity within a national population, valuation studies may identify latent groups that place different absolute and relative importance (i.e., scale and taste parameters) on the attributes of health profiles.

OBJECTIVE

Using discrete choice responses from a Peruvian valuation study, we estimated EQ-5D-5L values on a quality-adjusted life-year (QALY) scale accounting for latent heterogeneity in scale and taste, as well as controlling heteroskedasticity at task level variation.

METHOD

We conducted a series of latent class analyses, each including the 20 main effects of the EQ-5D-5L and a power function that relaxes the constant proportionality assumption (i.e., discounting) between value and lifespan. Taste class membership was conditional on respondent-specific characteristics and their experience with the composite time trade-off (cTTO) tasks. Scale class membership was conditional on behavioral characteristics such as survey duration and self-stated difficulty level in understanding tasks. Each analysis allowed the scale factor to vary by task type and completion time (i.e., heteroskedasticity).

RESULTS

The results indicated three taste classes: a quality-of-life oriented class (33.35%) that placed the highest value on levels of severity, a length-of-life oriented class (26.72%) that placed the highest value on lifespan, and a middle class (39.71%) with health attribute effects lower than the quality class and lifespan effect lower than the length-of-life oriented class. The EQ-5D-5L values ranged from - 2.11 to 0.86 (quality-of-life oriented class), from - 0.38 to 1.02 (middle class), and from 0.36 to 1.01 (length-of-life oriented class). The likelihood of being a member of the quality-of-life class was highly dependent on whether the respondent completed the cTTO tasks (p-value < 0.001), which indicated that the cTTO tasks might cause the Peru respondents to inflate the burden of health problems on a QALY scale compared to those who did not complete the cTTO tasks. The results also showed two scale classes as well as heteroskedasticity within each scale class.

CONCLUSION

Accounting for taste and scale classes simultaneously improveds understanding of preference heterogeneity in health valuation. Future studies may confirm the differences in taste between classes in terms of the effect of quality of life and lifespan attributes. Furthermore, confirmatory evidence is needed on how behavioral variables captured within a study protocol may enhance analyses of preference heterogeneity.

Patients' Self-Reported Disability Weights of Top-Ranking Diseases in Thailand: Do They Differ by Socio-Demographic and Illness Characteristics?

Little is known about the impact of methodological decisions on estimating disability weights among patients with mental and physical disorders, and the effects of socio-demographic status on the estimation of these weights. A cross-sectional study was conducted in three hospitals in southern Thailand to describe the disability weights based on different valuation methods. Altogether, 150 patients with major depressive disorder, 150 with alcohol use disorder, and 150 with osteoarthritis with varying levels of severity were recruited. Using a face-to-face interview, all patients completed a visual analogue scale (VAS) and were randomly assigned to complete either the European Quality of Life-5 Dimensions (EQ-5D) or Time-trade-off (TTO) instrument to estimate their current utility score, which was consequently transformed to a disability weight. Significant differences were found between disability weights derived from the three instruments for the same disease, with the VAS providing the highest and EQ-5D the lowest weights. Patients with major depressive disorder had the highest disability weight while those with osteoarthritis had lowest by most methods. Patients’ socio-demographics do not affect how they perceive their disability or health condition. Our findings highlight the importance of carefully selecting methods of valuing disability weights, which can rely on disease specific conditions.

Valuation and Modeling of EQ-5D-5L Health States Using a Hybrid Approach

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Background:

The EQ-5D instrument is the most widely used preference-based health-related quality of life questionnaire in cost-effectiveness analysis of health care technologies. Recently, a version called EQ-5D-5L with 5 levels on each dimension was developed. This manuscript explores the performance of a hybrid approach for the modeling of EQ-5D-5L valuation data.

Methods:

Two elicitation techniques, the composite time trade-off, and discrete choice experiments, were applied to a sample of the Spanish population (n=1000) using a computer-based questionnaire. The sampling process consisted of 2 stages: stratified sampling of geographic area, followed by systematic sampling in each area. A hybrid regression model combining composite time trade-off and discrete choice data was used to estimate the potential value sets using main effects as starting point. The comparison between the models was performed using the criteria of logical consistency, goodness of fit, and parsimony.

Results:

Twenty-seven participants from the 1000 were removed following the exclusion criteria. The best-fitted model included 2 significant interaction terms but resulted in marginal improvements in model fit compared to the main effects model. We therefore selected the model results with main effects as a potential value set for this methodological study, based on the parsimony criteria. The results showed that the main effects hybrid model was consistent, with a range of utility values between 1 and −0.224.

Conclusion:

This paper shows the feasibility of using a hybrid approach to estimate a value set for EQ-5D-5L valuation data.

EuroQol Protocols for Time Trade-Off Valuation of Health Outcomes

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.

Unchained melody: revisiting the estimation of SF-6D values

PURPOSE

In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions.

METHODS

Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under three alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England.

RESULTS

Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9 % more).

CONCLUSIONS

Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates.

The Value Adults Place on Child Health and Functional Status

OBJECTIVES

To summarize the value adults place on child health and functional status and provide a new quantitative tool that enhances our understanding of the benefits of new health technologies and illustrates the potential contributions of existing data sets for comparative effectiveness research in pediatrics.

METHODS

Respondents, ages 18 years and older, were recruited from a nationally representative panel between August 2012 and February 2013 to complete an online survey. The survey included a series of paired comparisons that asked respondents to choose between child health and functional status outcomes, which were described using the National Survey of Children with Special Health Care Needs, a 14-item descriptive system of child health outcomes. Using respondent choices regarding an unnamed 7- or 10-year-old child, generalized linear model analyses estimated the value of child health and functional status on a quality-adjusted life-year scale.

RESULTS

Across the domains of health and functional status, repeated or chronic physical pain, feeling anxious or depressed, and behavioral problems (such as acting out, fighting, bullying, or arguing) were most valuable, as indicated by adult respondents' preference of other health problems to avoid outcomes along these domains.

DISCUSSION

These findings may inform comparative effectiveness research, health technology assessments, clinical practice guidelines, and public resource allocation decisions by enhancing understanding of the value adults place on the health and functional status of children.

CONCLUSIONS

Improved measurement of public priorities can promote national child health by drawing attention to what adults value most and complementing conventional measures of public health surveillance.

US valuation of the SF-6D

BACKGROUND

The original SF-6D valuation study collected 3503 standard gambled responses from 611 UK respondents to predict quality-adjusted life year (QALY) values.

METHODS

Using 19,980 paired comparison responses from 666 US respondents and a stacked probit model, the 25 coefficients of the original SF-6D multiattribute utility (MAU) regression were estimated, such that each coefficient represents a QALY decrement. The US QALY predictions were compared with UK predictions using 8428 SF-6D states in the US Medicare Health Outcomes Survey (MHOS), 1998 to 2003.

RESULTS

Twenty-two of the 25 decrements in the SF-6D MAU regression are statistically significant. The remaining decrements are insignificant based on US and UK results. The US and UK QALY predictions for the MHOS SF-6D states are remarkably similar given differences in experimental design, format, and sampling (Lin's coefficient of agreement, 0.941; absolute mean difference, 0.043). Limitations. The underlying theoretical framework for the

STUDY DESIGN

and econometric analysis builds from the episodic random utility model and the concept of QALYs and inherits their limitations.

CONCLUSIONS

This study enhances the potential for US comparative effectiveness research by translating SF-6D states into US QALYs as well as improves upon discrete choice experiment design and econometric methods for health valuation.

Constructing indirect utility models: some observations on the principles and practice of mapping to obtain health state utilities

The construction of mapping models is an increasingly popular mechanism for obtaining health state utility data to inform economic evaluations in health care. There is great variation in the sophistication of the methods utilized but to date very little discussion of the appropriate theoretical framework to guide the design and evaluation of these models. In this paper, we argue that recognizing mapping models as a form of indirect health state valuation allows the use of the framework described by Dolan for the measurement of social preferences over health. Using this framework, we identify substantial concerns with the method for valuing health states that is implicit in indirect utility models (IUMs), the conflation of two sets of respondents' values in such models, and the lack of a structured and statistically reasonable approach to choosing which states to value and how many observations per state to require in the estimation dataset. We also identify additional statistical challenges associated with clustering and censoring in the datasets for IUMs, additional to those attributable to the descriptive systems, and a potentially significant problem with the systematic understatement of uncertainty in predictions from IUMs. Whilst recognizing that IUMs appear to meet the needs of reimbursement organizations that use quality-adjusted life years in their appraisal processes, we argue that current proposed quality standards are inadequate and that IUMs are neither robust nor appropriate mechanisms for estimating utilities for use in cost-effectiveness analyses.

Lead versus lag-time trade-off variants: does it make any difference?

OBJECTIVES

The traditional time trade-off (TTO) method has some problems in the valuation of health states considered worse than dead. The aim of our study is to compare two TTO variants that address this issue: lead-time and lag-time TTO.

METHODS

Quota sampling was undertaken in June 2011 in Buenos Aires as part of the EQ-5D-5L Multinational Pilot Study. Respondents were randomly assigned to one of the TTO variants with two blocks of five EQ-5D-5L health states. Tasks were administered using a web-based digital aid (EQ-VT) administered in a group interview.

RESULTS

A total of 387 participants were included [mean age 38.85 (SD: 13.97); 53.14 % females]. The mean observed values ranged from 0.44 (0.59) for state 21111 to 0.02 (0.76) for state 53555 in the lead-time group and between 0.53 (0.52) and 0.08 (0.76) in the lag-time group. There were no statistically significant differences in the values between TTO variants, except for a significant difference of 0.19 for state 33133. In both variants, marked peaks were observed around the value 0 across all states, with a higher percentage of 0 responses in the last state valued, suggesting ordering effects.

CONCLUSIONS

No important differences were found between TTO variants regarding values for EQ-5D-5L health states, suggesting that they could be equivalent variants. However, differences between the two methods may have been obscured by other aspects of the study design affecting the characteristics of the data.

Lead versus lag-time trade-off variants: does it make any difference?

OBJECTIVES

The traditional time trade-off (TTO) method has some problems in the valuation of health states considered worse than dead. The aim of our study is to compare two TTO variants that address this issue: lead-time and lag-time TTO.

METHODS

Quota sampling was undertaken in June 2011 in Buenos Aires as part of the EQ-5D-5L Multinational Pilot Study. Respondents were randomly assigned to one of the TTO variants with two blocks of five EQ-5D-5L health states. Tasks were administered using a web-based digital aid (EQ-VT) administered in a group interview.

RESULTS

A total of 387 participants were included [mean age 38.85 (SD: 13.97); 53.14 % females]. The mean observed values ranged from 0.44 (0.59) for state 21111 to 0.02 (0.76) for state 53555 in the lead-time group and between 0.53 (0.52) and 0.08 (0.76) in the lag-time group. There were no statistically significant differences in the values between TTO variants, except for a significant difference of 0.19 for state 33133. In both variants, marked peaks were observed around the value 0 across all states, with a higher percentage of 0 responses in the last state valued, suggesting ordering effects.

CONCLUSIONS

No important differences were found between TTO variants regarding values for EQ-5D-5L health states, suggesting that they could be equivalent variants. However, differences between the two methods may have been obscured by other aspects of the study design affecting the characteristics of the data.

Time trade-off: one methodology, different methods

There is no scientific consensus on the optimal specification of the time trade-off (TTO) task. As a consequence, studies using TTO to value health states may share the core element of trading length of life for quality of life, but can differ considerably on many other elements. While this pluriformity in specifications advances the understanding of TTO from a methodological point of view, it also results in incomparable health state values. Health state values are applied in health technology assessments, and in that context comparability of information is desired. In this article, we discuss several alternative specifications of TTO presented in the literature. The defining elements of these specifications are identified as being either methodological, procedural or analytical in nature. Where possible, it is indicated how these elements affect health state values (i.e., upward or downward). Finally, a checklist for TTO studies is presented, which incorporates a list of choices to be made by researchers who wish to perform a TTO task. Such a checklist enables other researchers to align methodologies in order to enhance the comparability of health state values.

Lead time TTO: leading to better health state valuations?

Preference elicitation tasks for better than dead (BTD) and worse than dead (WTD) health states vary in the conventional time trade-off (TTO) procedure, casting doubt on uniformity of scale. 'Lead time TTO' (LT-TTO) was recently introduced to overcome the problem. We tested different specifications of LT-TTO in comparison with TTO in a within-subject design. We elicited preferences for six health states and employed an intertemporal ranking task as a benchmark to test the validity of the two methods. We also tested constant proportional trade-offs (CPTO), while correcting for discounting, and the effect of extending the lead time if a health state is considered substantially WTD. LT-TTO produced lower values for BTD states and higher values for WTD states. The validity of CPTO varied across tasks, but it was higher for LT-TTO than for TTO. Results indicate that the ratio of lead time to disease time has a greater impact on results than the total duration of the time frame. The intertemporal ranking task could not discriminate between TTO and LT-TTO.

Impact of transformation of negative values and regression models on differences between the UK and US EQ-5D time trade-off value sets

BACKGROUND

National EQ-5D value sets are developed because preferences for health may vary in different populations. UK values are lower than US values for most of the 243 possible EQ-5D health states. Although similar protocols were used for data collection, analytic choices regarding how to model values from the collected data may also influence national value sets. Participants in the UK and US studies assessed the same subset of 42 EQ-5D health states using the time trade-off (TTO) method. However, different methods were used to transform negative values to a range bounded by 0 and -1, and values for all 243 health states were estimated using two different regression models. The transformation of negative values is inconsistent with expected utility theory, and the choice of which transformation method to use lacks a theoretical foundation.

OBJECTIVES

Our objectives were to assess how much of the observed difference between the UK and US EQ-5D value sets may be explained by the choice of transformation method for negative values relative to the choice of regression model and the differences between elicited TTO values in the respective national studies (datasets).

METHODS

We applied both transformation methods and both regression models to each of the two datasets, resulting in eight comparable value sets. We arranged these value sets in pairs in which one source of difference (transformation method, regression model or dataset) was varied. For each of these paired value sets, we calculated the mean difference between the two matching values for each of the 243 health states. Finally, we calculated the mean utility gain for all possible transitions between pairs of EQ-5D health states within each value set and used the difference in transition scores as a measure of impact from changing transformation method, regression model or dataset.

RESULTS

The mean absolute difference in values was 1.5 times larger when changing the transformation method than when using different datasets. The choice of transformation method had a 3.2 times larger effect on the mean health gain (transition score) than the choice of dataset. The mean health gain in the UK value set was 0.09 higher than in the US value set. Using the UK transformation method on the US dataset reduced this absolute difference to 0.02. The choice of regression model had little overall impact on the differences between the value sets.

CONCLUSIONS

Most of the observed differences between the UK and US value sets were caused by the use of different transformation methods for negative values, rather than differences between the two study populations as reflected in the datasets. Changing the regression model had little impact on the differences between the value sets.

A shortcut to mean-based time tradeoff tariffs for the EQ-5D?

BACKGROUND

EQ-5D valuation studies are usually performed using the time tradeoff (TTO) method, which is costly and time consuming. We focused on 2 properties that particularly characterize TTO: the initial choice task categorizing health states as better than death (BTD), worse than death (WTD), or equal to death (ETD), and unwillingness to trade (UTT) lifetime to improve health. The aim of this study was to estimate the value of the information to be gained from continuing the conventional TTO tasks beyond the initial question and the extent to which mean-based EQ-5D tariff values could be predicted through a simplified method of categorizing health states into BTD, WTD, ETD, and UTT.

METHODS

We used data from the UK EQ-5D valuation study (n = 2997). We designed an abbreviated system with only 4 values (collapsed TTO [cTTO]) based on the 4 response categories and assigned values as follows: WTD = -.5, ETD = 0, BTD = .5, and UTT = 1. Based on the mean cTTO scores for the valued health states, we created a regression-based cTTO tariff, which was compared with the conventional (full) TTO tariff (fTTO) by regressing 1) the fTTO means on cTTO means and 2) the fTTO tariff on the cTTO tariff.

RESULTS

WTD values were unrelated to health state severity. Correlation between the means of fTTO and means of cTTO was >.999, and tariff values from fTTO correlated with tariff values from cTTO at r > .999.

CONCLUSIONS

Once respondents have classified health states as UTT, BTD, ETD, or WTD, the TTO procedure adds little further information to the tariff values. The WTD task fails to discriminate between good and bad health states. TTO valuation could likely be simplified using cTTO.

Non-monotonicity in the episodic random utility model

The time trade-off (TTO) is widely used in population-based surveys to estimate health-state valuations. Typically, respondents may characterize states as being better than or worse than dead. However, worse-than-dead responses can produce strongly negative mean values, so various analytic transformations of these responses have been suggested. The episodic random utility model (eRUM), operationalized using a linear regression estimator, was proposed as an alternative to these transformations, in part because of its theoretical appeal. We analyzed the eRUM estimator's mathematical properties and found that it violates monotonicity under certain patterns of survey responses, such that improvement in some individual valuations would imply a lower overall valuation for a given health state. Consequently, it is possible that orderings of alternative strategies based on eRUM valuations could lead a decision-maker to choose a strictly dominated strategy. Re-analyzing data from a large population-based EQ-5D valuation survey in the United Kingdom, we found 27% of all TTO responses (63% of all worse-than-dead responses) met the conditions for violation of monotonicity, and 74% of all respondents had at least one such response. These results present some challenge to the use of the eRUM estimator in generating health-state valuations for population health measurement and economic evaluation.

Revisiting United States valuation of EQ-5D states

In the original US valuation study of EQ-5D states, all worse-than-dead time trade-off responses (26% of the sample) were divided by 39 to increase the QALY estimates. This transformation has no theoretical justification and motivates this re-examination. Using the publically available dataset, we compared three alternative random utility models: instant (IRUM), angular (ARUM), and episodic (ERUM) models. Each leads to a distinct econometric estimator: mean ratio, ratio of means, and coefficient, respectively. IRUM suggests that 203 of the 243 EQ-5D states are worse-than-dead, which has little face validity compared to ARUM and ERUM (42 and 3 WTD states). ARUM and ERUM estimates are proportionally related such that losses in QALYs are approximately 37% larger under ARUM than ERUM. Compared to ERUM, economic evaluations using ARUM estimates emphasize quality of life, and this difference may influence policy decisions. Either ERUM or ARUM values sets are recommended over the original, transformed set.