Developing a New Region-Specific Preference-Based Measure in East and Southeast Asia

Comparison of four value sets derived using different TTO and DCE approaches: application to the new region-specific PBM, AP-7D

BACKGROUND

AP-7D is a newly developed preference-based measure (PBM) in East and Southeast Asia. However, no value set has been established yet. Comparison of the characteristics of value sets obtained by different methods is necessary to consider the most appropriate methodology for valuation survey of AP-7D.

METHOD

We surveyed the general population's preference of AP-7D health states by four valuation methods (a) composite time trade-off (cTTO); (b) simple discrete choice experiment (DCE); (c) DCE with duration; and (d) ternary DCE. In Japan, we collected approximately 1,000 samples for cTTO tasks through a face-to-face survey and 2,500 samples for each of the three DCE tasks. Respondents were selected through quota sampling based on the sex and age. The cTTO data were analyzed using a linear mixed and tobit model; the DCE data were analyzed using a simple and panel conditional logit model. Where the results of the analysis showed inconsistencies, a constrained model was used.

RESULTS

Since all the unconstrained models, except simple DCE, showed one or more inconsistencies, the constrained model was used for the analyses. The minimum values for the models were as follows: TTO model, -0.101; simple DCE model, -0.106; DCE with duration model, -0.706; ternary DCE model, -0.306. The score for the DCE with the duration model was much lower than that for the other models. Although the value sets for AP-7D differed among the four valuation methods, the ternary DCE model showed intermediate characteristics between those of the cTTO and DCE with duration models. As compared with to EQ-5D-5L, the distributions of all the scores on the Japanese AP-7D moved to the left. Although "Energy" was one of the domains with the least influence on the AP-7D score in all four models, "Burden to others" had the largest impact on the preferences.

CONCLUSION

We constructed four value sets using different TTO and DCE methods. Our findings are expected not only to contribute to the development of AP-7D, but also other preference-based measures.

Fifteen Lessons from Fifteen Years of the Health Intervention and Technology Assessment Program in Thailand

The Health Intervention and Technology Assessment Program (HITAP) was established in 2007. This article highlights 15 lessons from over 15 years of experience, noting five achievements about what HITAP has done well, five areas that it is currently working on, and five aims for work in the future. HITAP built capacity for HTA and linked research to policy and practice in Thailand. With collaborators from academic and policy spheres, HITAP has mobilized regional and global support, and developed global public goods to enhance the field of HTA. HITAP's semi-autonomous structure has facilitated these changes, though they have not been without their challenges. HITAP aims to continue its work on HTA for public health interventions and disinvestments, effectively engaging with stakeholders and strategically managing its human resources. Moving forward, HITAP will develop and update global public goods on HTA, work on emerging topics such as early HTA, address issues in digital health, real-world evidence and equity, support HTA development globally, particularly in low-income settings, and seek to engage more effectively with the public. HITAP seeks to learn from its experience and invest in the areas identified so that it can grow sustainably. Its journey may be relevant to other countries and institutions that are interested in developing HTA programs.