Using Time Trade-Off Values to Estimate EQ-5D-Y Value Sets: An Exploratory Study

OBJECTIVES

The published international EQ-5D-Y-3L valuation protocol does not recommend the composite time trade-off (cTTO) method as the primary valuation method because of 2 major concerns. First, the cTTO method was shown to generate high values. Second, the cTTO method is not as feasible for valuing children's health as other established methods. This study aimed to explore the feasibility of using cTTO values alone to estimate EQ-5D-Y-3L value sets.

METHODS

We analyzed the cTTO data derived from the recently completed Chinese EQ-5D-Y-3L valuation study in which a total of 28 health states were valued. We assessed the feasibility of the cTTO tasks in terms of survey completion time and participant-reported difficulty of understanding the task, differentiating the health states, and deciding the answer. We also examined the data distribution characteristics and modeled the data using different models.

RESULTS

In total, 418 participants completed the cTTO interview. On average, participants took approximately 35.70 minutes (SD 12.42) to complete the interview and made 13.21 moves (SD 9.00) in the cTTO tasks. There were 74.16%, 59.33%, and 11.48% of participants indicated that it was easy to understand the cTTO tasks, easy to differentiate between the health states, and difficult to decide on an indifference point, respectively. The data distribution was smooth, and a random-effects model performed the best in terms of coefficient significance, monotonicity, and predictive accuracy.

CONCLUSION

Our finding suggests that estimating EQ-5D-Y-3L value sets using cTTO data alone is feasible and therefore could be considered as an option in future valuation studies for EQ-5D-Y-3L.

Use of a Non-parametric Bayesian Method to Model Health State Preferences: An Application to Polish and Irish EQ-5D-5L Valuations

Valuations of preference-based measures for health are conducted in different countries. There is scope to use results from existing countries' valuations to generate better valuation estimates than analyzing the data from each country separately. We analyse data from two smaller design EQ-5D-5L valuation studies where a sample of 119 Polish migrants and 123 native Irish valued 30 common health states using similar composite time trade-off protocols. We apply a non-parametric Bayesian method to provide better predictions of the Polish (Irish) population utility function when the existing Irish (Polish) results were used as informative priors. The resultant new estimates were then compared to those obtained by analyzing the data from each country by itself via different prediction criterions. The results suggest that existing countries' valuations could be used as potential informative priors to produce better valuation estimates under all prediction criterions used. The implications of these results will be hugely important in countries where valuation studies are expensive and hard to conduct. Future application to other countries and to other preference-based health measures are encouraged.

Accounting for Unobservable Preference Heterogeneity and Evaluating Alternative Anchoring Approaches to Estimate Country-Specific EQ-5D-Y Value Sets: A Case Study Using Spanish Preference Data

OBJECTIVES

The EuroQol Group published the EQ-5D-Y valuation protocol that recommends 2 valuation techniques to elicit preferences: composite time trade-off (C-TTO) and discrete choice experiments (DCEs). The protocol left the decision of what modeling approach to use open for researchers. Our aims were to explore modeling strategies allowing generation of EQ-5D-Y value sets and to produce an EQ-5D-Y Spanish value set.

METHODS

We used EQ-5D-Y DCE and C-TTO data collected in Spain following the protocol and adopted a staged approach for our modeling exercise. First, we selected the best performing DCE latent class model and evaluated models from 2 to 10 classes. We selected the preferred model based on best goodness of fit in terms of the Bayesian information criterion. We considered 2 anchoring approaches to estimate utility values: (1) pits state anchoring and (2) hybrid models (using all available C-TTO responses). All analysis were weighted to be representative of the Spanish population.

RESULTS

We collected 1005 DCE and 200 C-TTO interviews. We selected a DCE model including 4 classes. Hybrid models using all available C-TTO observations produced a narrower range of values than the pits state anchoring approach.

CONCLUSIONS

In this article, we have presented an EQ-5D-Y value set that can be used for cost-utility analysis in Spain. The international EQ-5D-Y valuation protocol should be updated to include a different set of health states for the C-TTO experiment if researchers wish to use alternative anchoring approaches to the "pits state."

Parallel Valuation of the EQ-5D-3L and EQ-5D-5L by Time Trade-Off in Hungary

OBJECTIVES

The wording of the Hungarian EQ-5D-3L and EQ-5D-5L descriptive systems differ a great deal. This study aimed to (1) develop EQ-5D-3L and EQ-5D-5L value sets for Hungary from a common sample, and (2) compare how level wording affected valuations.

METHODS

In 2018 to 2019, 1000 respondents, representative of the Hungarian general population, completed composite time trade-off tasks. Pooled heteroscedastic Tobit models were used to estimate value sets. Value set characteristics, single-level transition utilities from adjacent corner health states, and mean transition utilities for all possible health states were compared between the EQ-5D-3L and EQ-5D-5L.

RESULTS

Health utilities ranged from -0.865 to 1 for the EQ-5D-3L and -0.848 to 1 for the EQ-5D-5L. The relative importance of the 5 EQ-5D-5L dimensions was as follows: mobility, pain/discomfort, self-care, anxiety/depression, and usual activities. A similar preference ranking was observed for the EQ-5D-3L with self-care being more important than pain/discomfort. The EQ-5D-5L demonstrated lower ceiling effects (range of utilities for the mildest states: 0.900-0.958 [3L] vs 0.955-0.965 [5L]) and better consistency of mean transition utilities across the range of scale. Changing "confined to bed" (3L) to "unable to walk" (5L) had a large positive impact on utilities. Smaller changes with more negative wording in the other dimensions (eg, "very much anxious/feeling down a lot" [3L] vs "extremely anxious/depressed" [5L]) had a modest negative impact on utilities.

CONCLUSION

This study developed value sets of the EQ-5D-3L and EQ-5D-5L for Hungary. Our findings contribute to the understanding of how the wording of descriptive systems affects the estimates of utilities.

A Head-On Ordinal Comparison of the Composite Time Trade-Off and the Better-Than-Dead Method

OBJECTIVES

The valuation of health states worse than dead is challenging. Currently used time trade-off methods face problems in (1) detecting time-dependent preferences and (2) insensitivity toward severity for states worse than dead. The better-than-dead (BTD) method has the potential to detect time-dependent preferences. This study compares the BTD and composite time trade-off (cTTO) methods at the ordinal level.

METHODS

An experiment was conducted in a convenience sample in which respondents (N = 200) valued the same set of 7 health states in the BTD method and cTTO method. Binary BTD responses were used, with response categories of better than dead and worse than dead. Ternary cTTO responses were used, with the additional equal-to-dead response category. Polychoric correlations were used to determine the agreement between these methods. Consistency and test-retest reliability were assessed within methods.

RESULTS

Overall agreement between the cTTO and BTD method equaled 77.1% and differed between health states and respondents. For both methods, there were few inconsistencies, and the test-retest reliability was comparable (88%). Health states were more often considered worse than dead in the BTD method (BTD: 54.7%, cTTO: 37.2%).

CONCLUSIONS

The high agreement between both methods and the comparable amount of inconsistencies and test-retest reliability suggest that the methods have similar measurement properties. The BTD method yielded higher frequencies of worse-than-dead responses while essentially asking respondents to make similar choices. This accounts for part of the disagreement between the methods. Several explanations are offered for this difference, yet more research is needed to explain this phenomenon.

Evaluation of Split Version and Feedback Module on the Improvement of Time Trade-Off Data

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 < 0.001) in NL and from 31.8% to 22.3% (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.