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用于双重离散选择实验(dual-DCE)调查的健康估值协议,以估计不同情景和属性对主要效应的影响。

Health valuation protocol for dual discrete choice experiment (dual-DCE) surveys to estimate the effects of different scenarios and attributes on main effects.

作者信息

Craig Benjamin Matthew

机构信息

University of South Florida, Tampa, Florida, USA

出版信息

BMJ Open. 2025 Feb 22;15(2):e091097. doi: 10.1136/bmjopen-2024-091097.

Abstract

INTRODUCTION

A typical health preference study conducts a single discrete choice experiment (DCE). For example, a health valuation study may elicit preferences on an individual's health-related quality of life along five EQ-5D-5L attributes (Mobility, Self-care, Usual Activities, Pain/Discomfort, Anxiety/Depression). Using this protocol, researchers can conduct a dual-DCE survey (ie, with two different full-block DCEs completed sequentially). To demonstrate this protocol, we will conduct 12 dual-DCE surveys in two waves and estimate the effects of different scenarios and descriptive systems on main effects (ie, incremental differences in value between levels).

METHODS AND ANALYSIS

Each of the two DCEs in a dual-DCE survey equates to a stand-alone health valuation study. To demonstrate this protocol, each is an EQ-5D-5L valuation study, including d-efficient blocks of 15 kaizen tasks and 5 paired comparisons. In wave 1 (six surveys, 1000 US adults each), the two DCEs will differ by scenario (1-year episodes ending in recovery or death or no duration/ending described). In wave 2 (six surveys, 200 US adults each), the two DCEs will include the same 5 EQ-5D-5L attributes but differ by the number of additional attributes related to cognition: none, one composite attribute (memory/concentration) and two component attributes (memory, concentration). For each DCE, we will estimate a conditional logit model and test for differences in value using cluster bootstrap techniques. We hypothesise that the values will differ by scenarios and systems. As secondary analyses, we assess the effects of sampling, scenario/system order and DCE order.

ETHICS AND DISSEMINATION

The independent review board (IRB) at Advarra determined that this research project (Pro00080475; 11 July 2024) is exempt from IRB oversight based on the Department of Health and Human Services regulations found at 45 CFR 46.104(d)(2). Furthermore, the IRB determined that the project is not subject to requirements for continuing review. To disseminate our findings, we will prepare multiple manuscripts for publication in peer-reviewed journals and present highlights at scientific meetings, such as the EuroQol Plenary Meeting, International Academy of Health Preference Research and ISPOR.

摘要

引言

典型的健康偏好研究进行单一的离散选择实验(DCE)。例如,一项健康估值研究可能会沿着五个EQ-5D-5L属性(行动能力、自我护理、日常活动、疼痛/不适、焦虑/抑郁)引出个体对与健康相关的生活质量的偏好。使用该方案,研究人员可以进行双DCE调查(即依次完成两个不同的全块DCE)。为了演示该方案,我们将分两波进行12次双DCE调查,并估计不同情景和描述系统对主要效应(即各水平之间价值的增量差异)的影响。

方法与分析

双DCE调查中的两个DCE各自相当于一项独立的健康估值研究。为了演示该方案,每个都是EQ-5D-5L估值研究,包括15个改善任务和5对配对比较的d效率块。在第1波(6次调查,每次1000名美国成年人)中,两个DCE在情景方面会有所不同(以康复或死亡或未描述持续时间/结局结束的1年病程)。在第2波(6次调查,每次200名美国成年人)中,两个DCE将包括相同的5个EQ-5D-5L属性,但在与认知相关的额外属性数量方面有所不同:无、一个综合属性(记忆/注意力)和两个组成属性(记忆、注意力)。对于每个DCE,我们将估计一个条件logit模型,并使用聚类自举技术测试价值差异。我们假设价值会因情景和系统而不同。作为次要分析,我们评估抽样、情景/系统顺序和DCE顺序的影响。

伦理与传播

Advarra的独立审查委员会(IRB)根据《美国联邦法规汇编》第45编第46.104(d)(2)条中美国卫生与公众服务部的规定,确定该研究项目(Pro00080475;2024年7月11日)免于IRB监督。此外,IRB确定该项目无需持续审查。为了传播我们的研究结果,我们将准备多篇稿件在同行评审期刊上发表,并在科学会议上展示亮点,如欧洲生活质量小组全会、国际健康偏好研究学会和国际药物经济学与结果研究学会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/104e/11848668/3d5da934af4e/bmjopen-15-2-g001.jpg

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