采用离散选择实验对退伍军人 RAND 12 项健康调查进行加拿大偏好评分算法的估计：一项基于人群的调查。
Estimation of a Canadian preference-based scoring algorithm for the Veterans RAND 12-Item Health Survey: a population survey using a discrete-choice experiment.
机构信息
School of Population and Public Health (Bansback), University of British Columbia; Centre for Health Evaluation and Outcome Sciences (Bansback, Trenaman, Metcalfe, Sawatzky), Vancouver, BC; Centre for Health Economics Research and Evaluation (Mulhern), University of Technology Sydney, Sydney, New South Wales, Australia; School of Health and Related Research (Mulhern, Brazier, Rowen), University of Sheffield, Sheffield, UK; School of Public Health (Norman), Curtin University, Perth, Western Australia, Australia; School of Nursing (Sawatzky), Trinity Western University, Langley, BC; Faculty of Health Sciences (Whitehurst), Simon Fraser University, Burnaby, BC
School of Population and Public Health (Bansback), University of British Columbia; Centre for Health Evaluation and Outcome Sciences (Bansback, Trenaman, Metcalfe, Sawatzky), Vancouver, BC; Centre for Health Economics Research and Evaluation (Mulhern), University of Technology Sydney, Sydney, New South Wales, Australia; School of Health and Related Research (Mulhern, Brazier, Rowen), University of Sheffield, Sheffield, UK; School of Public Health (Norman), Curtin University, Perth, Western Australia, Australia; School of Nursing (Sawatzky), Trinity Western University, Langley, BC; Faculty of Health Sciences (Whitehurst), Simon Fraser University, Burnaby, BC.
出版信息
CMAJ Open. 2022 Jul 5;10(3):E589-E598. doi: 10.9778/cmajo.20210113. Print 2022 Jul-Sep.
BACKGROUND
The Veterans RAND 12-Item Health Survey (VR-12) is a generic patient-reported outcome measure derived from the widely used 36- and 12-item Short Form Health Surveys. We aimed to estimate a Canadian preference-based scoring algorithm for the VR-12, enabling the derivation of health utility values for generating quality-adjusted life years (QALYs).
METHODS
We conducted a discrete-choice experiment in a sample of the Canadian population in January and February 2019. Participants - recruited from a consumer research panel - completed an online survey, in English or French, that included 11 discrete-choice questions, each comprising 2 health profiles. We defined the health profiles using 8 VR-12 items and a duration attribute. Using conditional logit regressions, where each level of the respective VR-12 items was interacted with duration, we applied the coefficients to estimate health utility values interpretable on a scale of 0 (dead) to 1 (full health). Negative values reflect states considered worse than dead.
RESULTS
A total of 3380 individuals completed the survey. Of these, 1688 (49.9%) were females, and 3101 (91.7%) completed the English version of the survey. Across all models, "feel downhearted and blue all of the time" and "pain interferes with your normal work extremely" were associated with the largest decrements in health utility. Excluding the 685 respondents (20.3%) who provided inconsistent responses had a negligible effect on the results. The recommended model, weighted to match population demographics, had health utility values ranging from -0.589 to 1.000.
INTERPRETATION
Health utility values that reflect the preferences of the Canadian population can now be derived from responses to the VR-12. These values can be used to generate QALYs in future analyses.
背景
退伍军人兰德 12 项健康调查（VR-12）是一种源自广泛使用的 36 项和 12 项简短形式健康调查的通用患者报告结局测量。我们旨在为 VR-12 估计一个加拿大偏好基础评分算法，从而为生成质量调整生命年（QALY）得出健康效用值。
方法
我们于 2019 年 1 月至 2 月在加拿大人群样本中进行了一项离散选择实验。参与者 - 从消费者研究小组中招募 - 完成了一项在线调查，该调查包括 11 个离散选择问题，每个问题都包含 2 个健康状况。我们使用 VR-12 的 8 个项目和持续时间属性来定义健康状况。使用条件逻辑回归，其中每个 VR-12 项目的水平与持续时间相互作用，我们应用系数来估计健康效用值，可在 0（死亡）到 1（完全健康）的范围内进行解释。负值反映出比死亡状态更差的状态。
结果
共有 3380 人完成了调查。其中，1688 人（49.9%）为女性，3101 人（91.7%）完成了调查的英语版本。在所有模型中，“一直感到沮丧和忧郁”和“疼痛严重干扰了你的正常工作”与健康效用的最大下降相关。排除提供不一致回复的 685 名受访者（20.3%）对结果几乎没有影响。经加权以匹配人口统计学的推荐模型具有从-0.589 到 1.000 的健康效用值。
解释
现在可以从 VR-12 的回复中得出反映加拿大人口偏好的健康效用值。这些值可用于未来分析中生成 QALY。
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