Assessing outcomes for cost-utility analysis in mental health interventions: mapping mental health specific outcome measure GHQ-12 onto EQ-5D-3L. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Lindkvist, Marie; Feldman, Inna
• Is Part Of: Health and quality of life outcomes. Volume 14:Issue 1(2016)
• Page Start: 1
• Page End: 9
• Publication Date: 2016-12
• Subjects: Mapping -- Preference-based measures -- Mental health -- Quality of life -- Utilities; Outcome assessment (Medical care) -- Periodicals; Quality of life -- Periodicals; 362.1
• DOI: 10.1186/s12955-016-0535-2
• Languages: English
• ISSNs: 1477-7525

Abstract

Abstract 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.