Department of Preventive and Social Medicine, University of Otago, Dunedin, New Zealand.
Department of Economics, University of Otago, Dunedin, New Zealand; 1000minds Ltd, Wellington, New Zealand.
Soc Sci Med. 2020 Feb;246:112707. doi: 10.1016/j.socscimed.2019.112707. Epub 2019 Nov 30.
The EuroQol Group's health descriptive systems, the EQ-5D-3L and its successor introduced in 2009, the EQ-5D-5L, are widely used worldwide for valuing health-related quality of life for cost-utility analysis and patient-reported health outcome measures. A new online tool for creating personal and social EQ-5D-5L value sets was recently developed and trialled in New Zealand (NZ). The tool, which includes extensive checks of the quality of participants' data, implements the PAPRIKA method - a novel type of adaptive discrete choice experiment in the present context - and a binary search algorithm to identify any health states worse than dead. After development and testing, the tool was distributed in an online survey in February and March 2018 to a representative sample of NZ adults (N = 5112), whose personal value sets were created. The tool's extensive data quality checks resulted in a 'high-quality' sub-sample of 2468 participants whose personal value sets were, in effect, averaged to create a social value set for NZ. These results overall as well as feedback from participants indicates that the new valuation tool is feasible and acceptable to participants, enabling valuation data to be relatively easily and cheaply collected. The tool could also be used in other countries, tested against other methods for creating EQ-5D-5L value sets, applied in personalised medicine and adapted to create value sets for other health descriptive systems.
欧洲五维健康量表（EQ-5D）及其 2009 年推出的后续版本 EQ-5D-5L 是欧洲五维健康量表组开发的健康描述性系统，被广泛用于成本效用分析和患者报告的健康结果测量中的健康相关生活质量的评估。最近，新西兰（NZ）开发并试用了一种用于创建个人和社会 EQ-5D-5L 值集的新在线工具。该工具包括对参与者数据质量的广泛检查，实现了 PAPRIKA 方法 - 一种在当前背景下新颖的自适应离散选择实验类型 - 以及二进制搜索算法，以确定任何比死亡更差的健康状态。在开发和测试后，该工具于 2018 年 2 月至 3 月在新西兰成年人（N=5112）的代表性样本中进行在线调查分发，为他们创建了个人值集。该工具广泛的数据质量检查导致 2468 名参与者的“高质量”子样本，实际上平均了他们的个人值集，为 NZ 创建了一个社会值集。这些结果以及参与者的反馈表明，新的估值工具对参与者来说是可行且可接受的，能够相对轻松且廉价地收集估值数据。该工具也可以在其他国家使用，与创建 EQ-5D-5L 值集的其他方法进行测试，应用于个性化医疗，并进行调整以创建其他健康描述性系统的价值集。
