Child health valuation protocol for a discrete choice experiment comparing paired comparison and kaizen tasks and estimating US EQ-5D-Y-3L values on an experience scale

儿童健康评估方案,用于一项离散选择实验,该实验比较了配对比较任务和改善任务,并根据经验量表估计了美国 EQ-5D-Y-3L 值。

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Abstract

INTRODUCTION: A decade ago, the first national valuation study of the EQ-5D-Y-3L (Y-3L) involved a discrete choice experiment (DCE) that asked 4155 US adult respondents to complete 40 paired comparisons, choosing between two dying children. Instead of choosing between dying children, the respondents in this novel protocol are asked whether 'being in a coma' is better or worse than experiencing 'health problems' (ie, experience scale) and how they would relieve health problems (ie, kaizen tasks). Our aims are to compare the preference evidence of the paired comparison and kaizen tasks and to conduct a DCE for the valuation of Y-3L profiles on an experience scale. METHODS AND ANALYSIS: Under this protocol, we will conduct an online survey that collects preference evidence from 600 US adult respondents on the health of a 10-year-old child for a week. Across all scenarios, each child will be described as either being 'in a coma' or having 'health problems', namely five three-level attributes (Y-3L). In this DCE, each respondent will be randomly assigned to one of four D-efficient blocks, including five coma comparisons (ie, Y-3L vs coma), 10 paired comparisons (Y-3L vs Y-3L) and 10 kaizen tasks (preference paths). In addition to comparing evidence by task (aim 2), the analysis plan includes the estimation of main-effects conditional logit models to create a Y-3L value set on an 'experience scale' where positive (negative) experiences have positive (negative) values (0 is 'being in a coma' and 1 is full health). ETHICS AND DISSEMINATION: The institutional review board (IRB) (Advarra) determined that this project (Pro00072276) is exempt from IRB oversight based on DHHS 45 CFR 46.104(d)(2) and is not subject to requirements for continuing review. The results will be prepared for publication in peer-reviewed journals and presented at scientific meetings. The data and code will be made available on reasonable request.

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