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Assessing outcomes for cost-utility analysis in mental health interventions : mapping mental health specific outcome measure GHQ-12 onto EQ-5D-3L

机译：评估心理健康干预措施中成本-效用分析的结果：将针对心理健康的具体结果测量GHQ-12映射到EQ-5D-3L

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Background: Many intervention-based studies aiming to improve mental health do not include a multi-attribute utility instrument (MAUI) that produces quality-adjusted life-years (QALYs) and it limits the applicability of the health economic analyses. This study aims to develop 'crosswalk' transformation algorithm between a measure for psychological distress General Health Questionnaire (GHQ-12) and MAUI EuroQoL (EQ-5D-3L). Methods: The study is based on a survey questionnaire sent to a random sample in four counties in Sweden in 2012. The survey included GHQ-12 and EQ-5D instruments, as well as a question about self-rated health. The EQ-5D index was calculated using the UK and the Swedish tariff values. Two OLS models were used to estimate the EQ-5D health state values using the GHQ-12 as exposure, based on the respondents (n = 17, 101) of two counties. The algorithms were applied to the data from two other counties, (n = 15, 447) to check the predictive capacity of the models. Results: The final models included gender, age, self-rated health and GHQ-12 scores as a quantitative variable. The regression equations explained 40 % (UK tariff) and 46 % (Swedish tariff) of the variances. The model showed a satisfying predictive capacity between the observed and the predicted EQ-5D index score, with Pearson correlation = 0.65 and 0.69 for the UK and Swedish models, respectively. Conclusion: The algorithms developed in this study can be used to determine cost-effectiveness of services or interventions that use GHQ-12 as a primary outcome where the utility measures are not collected.
机译：背景：许多旨在改善心理健康的基于干预的研究并未包括产生质量调整生命年（QALY）的多属性效用工具（MAUI），它限制了健康经济分析的适用性。这项研究的目的是在心理困扰综合健康问卷（GHQ-12）和MAUI EuroQoL（EQ-5D-3L）之间开发一种“人行横道”转换算法。方法：该研究基于2012年向瑞典四个县的随机样本发送的调查问卷。该调查包括GHQ-12和EQ-5D仪器以及有关自我评估健康的问题。 EQ-5D指数是使用英国和瑞典的关税值计算得出的。基于两个县的受访者（n = 17，101），使用两个OLS模型以GHQ-12作为暴露量来估算EQ-5D健康状态值。该算法已应用于来自其他两个县（n = 15、447）的数据，以检查模型的预测能力。结果：最终模型包括性别，年龄，自我评估的健康状况和GHQ-12得分作为定量变量。回归方程式解释了40％（英国关税）和46％（瑞典关税）的差异。该模型显示了在观测到的EQ-5D指数得分与预期EQ-5D指数得分之间令人满意的预测能力，英国模型和瑞典模型的Pearson相关性分别为0.65和0.69。结论：本研究开发的算法可用于确定以GHQ-12作为主要结果（未收集效用措施）的服务或干预措施的成本效益。

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