Discrete Choice Experiments in Health State Valuation: A Systematic Review of Progress and New Trends

Abstract

Background Discrete choice experiments (DCEs) are increasingly used in health state valuation studies. Objective This systematic review updates the progress and new findings of DCE studies in the health state valuation, covering the period since the review of June 2018 to November 2022. The review reports the methods that are currently being used in DCE studies to value health and study design characteristics, and, for the first time, reviews DCE health state valuation studies published in the Chinese language. Methods English language databases PubMed and Cochrane, and Chinese language databases Wanfang and CNKI were searched using the self-developed search terms. Health state valuation or methodology study papers were included if the study used DCE data to generate a value set for a preference-based measure. Key information extracted included DCE study design strategies applied, methods for anchoring the latent coefficient on to a 0-1 QALY scale and data analysis methods. Results Sixty-five studies were included; one Chinese language publication and 64 English language publications. The number of health state valuation studies using DCE has rapidly increased in recent years and these have been conducted in more countries than prior to 2018. Wide usage of DCE with duration attributes, D-efficient design and models accounting for heterogeneity has continued in recent years. Although more methodological consensus has been found than in studies conducted prior to 2018, this consensus may be driven by valuation studies for common measures with an international protocol (the 'model' valuation research). Valuing long measures with well-being attributes attracted attention and more realistic design strategies (e.g., inconstant time preference, efficient design and implausible states design) were identified. However, more qualitative and quantitative methodology study is still necessary to evaluate the effect of those new methods. Conclusions The use of DCEs in health state valuation continues to grow dramatically and the methodology progress makes the method more reliable and pragmatic. However, study design is driven by international protocols and method selection is not always justified. There is no gold standard for DCE design, presentation format or anchoring method. More qualitative and quantitative methodology study is recommended to evaluate the effect of new methods before researchers make methodology decisions.

United States Value Set for the Functional Assessment of Cancer Therapy-General Eight Dimensions (FACT-8D), a Cancer-Specific Preference-Based Quality of Life Instrument

“…The inclusion of survival duration in the DCE enabled a functional form for utilities that was consistent with standard QALY model restrictions. This was first proposed by Bansback et al in 2012 [ 26 ] and has been used widely since, as illustrated in Wang et al’s systematic review, in which 29 out of 65 (45%) included a duration attribute [ 57 ].…”

Danish value sets for the EORTC QLU-C10D utility instrument

“…In a recent review of DCE studies in health state valuation by Wang et al [ 41 ], the majority of studies (48/65, 74%) used conditional logit models. In our study, we also relied on a conditional logit models because its parameterization is more suited our purpose (for public decision-making) compared to mixed logit models that focus on the distribution of individual preferences.…”