General population health state values are used in healthcare resource allocation, including health technology assessment. We examine whether UK general population health valuations changed during the COVID-19 pandemic. Ratings of EQ-5D-5L health states 11111 (no problems), 55555 (extreme problems), and dead were collected in a UK general population survey during the pandemic (April–May 2020) using the 0 = worst imaginable health, 100 = best imaginable health visual analog scale (EQ-VAS). Ratings for 55555 were transformed to a full health = 1, dead = 0 scale. Responses were compared to similar data collected pre-pandemic (2018). After propensity score matching to minimize sample differences, EQ-VAS responses were analyzed using Tobit regressions. On the 0–100 scale, 11111 was rated on average 8.67 points lower, 55555 rated 9.56 points higher, and dead rated 7.45 points lower post-pandemic onset compared to pre-pandemic. On the full health = 1, dead = 0 scale, 55555 values were 0.09 higher post-pandemic onset. There was evidence of differential impacts of COVID-19 by gender, age, and ethnicity, although only age impacted values on the 1–0 scale. COVID-19 may have affected how people value health. It is unknown whether the effect is large enough to have policy relevance, but caution should be taken in assuming pre-COVID-19 values are unchanged.

中文翻译：

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健康危机会改变我们对健康的评价吗？

一般人口健康状态值用于医疗资源分配，包括卫生技术评估。我们研究了在 COVID-19 大流行期间英国的一般人口健康估值是否发生了变化。在大流行期间（2020 年 4 月至 2020 年 5 月）的英国一般人口调查中收集了 EQ-5D-5L 健康状态 11111（没有问题）、55555（极端问题）和死亡的评级，使用 0 = 可想象的最糟糕的健康状况，100 =可以想象的最佳健康视觉模拟量表（EQ-VAS）。55555 的评级被转换为完全健康 = 1，死亡 = 0 等级。将响应与大流行前（2018 年）收集的类似数据进行了比较。在倾向得分匹配以最小化样本差异后，使用 Tobit 回归分析 EQ-VAS 反应。在 0-100 的范围内，11111 的评分平均低 8.67 分，55555 的评分平均高 9.56 分，与大流行前相比，大流行后发病率低 7.45 分。在完全健康 = 1、死亡 = 0 量表上，55555 个值在大流行后发病率高 0.09。有证据表明 COVID-19 对性别、年龄和种族的影响不同，尽管只有年龄对 1-0 范围内的值有影响。COVID-19 可能影响了人们重视健康的方式。目前尚不清楚这种影响是否大到足以具有政策相关性，但在假设 COVID-19 之前的值没有变化时应谨慎。COVID-19 可能影响了人们重视健康的方式。目前尚不清楚这种影响是否大到足以具有政策相关性，但在假设 COVID-19 之前的值没有变化时应谨慎。COVID-19 可能影响了人们重视健康的方式。目前尚不清楚这种影响是否大到足以具有政策相关性，但在假设 COVID-19 之前的值没有变化时应谨慎。