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.

Fig. 1

Study selection (PRISMA STANDARD). Our review was conducted in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA [100])

Fig. 2

Measures used in identified articles. AD-5D Alzheimer’s Disease Five Dimensions, ASCOT Adult Social Care Outcomes Toolkit, CARIES-QC-U Caries Impacts and Experiences Questionnaire for Children, CarerQol-7D Care related quality of life-7 dimensions, CP-6D cerebral palsy quality of life-6 dimensions, CQ-11D Chinese medicine quality of life-11 dimensions, DMD-QoL Duchenne muscular dystrophy quality of life, DRU-I Diabetic Retinopathy Utility Index, EQ-5D-3L/5L European Quality of Life 5 Dimensions 3 Level/5 Level Version, EQ-5D-Y European Quality of Life 5 Dimensions Youth Bolt on/off EQ-5D with bolt on/off dimensions, FACT-8D Functional Assessment of Cancer Therapy Eight Dimension, HASMID Health and Self-Management in Diabetes, ICECAP-SCM ICECAP Supportive Care Measure, IQI Infant health-related quality of life instrument, QLU-C10D European Organisation for Research and Treatment of Cancer (EORTC) cancer utility measure instrument, QOL-ACC quality-of-life aged care consumers, QOLIBRI-OS Quality of Life after Brain Injury overall scale, NDI neck disability index, SF-6D v2 Short-Form Six-Dimension Version 2, SOSGOQ-8D Spine Oncology Study Group Outcomes Questionnaire-8 dimensions, WOOP well-being of older people. Note Shah et al. [73] used EQ-5D-Y and EQ-5D-3L