Revisiting the Valuation of Child Health-Related Quality of Life: Replacing Paired Comparisons With Kaizen Tasks and QALY Scaling With Experience Scaling

重新审视儿童健康相关生活质量的评估:以改善任务取代成对比较,以经验尺度取代质量调整生命年尺度

阅读:1

Abstract

OBJECTIVES: In 2013, the EQ-5D-Y-3L valuation study conducted by Craig and colleagues (ie, the original study) of child health-related quality of life (HRQoL) revealed that U.S. respondents often found it burdensome and guilt-inducing to choose between hypothetical health problems of children. This study introduces an alternative approach where respondents sequentially relieve the health problems of a 10-year-old child for 1 week. METHODS: We conducted a discrete choice experiment (DCE) survey (N=631) with paired comparisons and kaizen tasks. Each kaizen task displayed a single profile of a child's HRQoL using the EQ-5D-Y-3L descriptive system and asked respondents to select first, second, and third improvements for the child's problems. Combining the preference evidence, a conditional logit model was estimated to produce EQ-5D-Y-3L values on an "experience" scale, where positive values signify experiences better than "being in a coma" and negative values worse. RESULTS: All 10 main effects were statistically significant ( P <0.01), with the highest value placed on alleviating pain and discomfort. The worst-case scenario (33333) had a value of -0.337 on the experience scale, indicating it is worse than a coma. These new estimates highly correlate with the original U.S. EQ-5D-Y-3L values (Pearson correlation=0.726; Spearman correlation=0.794). CONCLUSION: This innovative approach to child health valuation replaces paired comparisons with Kaizen tasks, reducing respondent burden and study costs. Its use of experience scaling, instead of QALYs, aligns with U.S. guidelines (eg, the Inflation Reduction Act of 2022) and summarizes child HRQoL gains for health technology assessment.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。