Background: The main objective is to present health state utility estimates for a broad range of mental health conditions including anxiety, depression, long-term depression, obsessive compulsive disorder, phobia, panic disorder, psychosis, alcohol and drug dependency that can be used in economic models.
Methods: This study uses pooled data from the Adult Psychiatric Morbidity Surveys carried out in 2000 and 2007 of a representative sample of the general population in England. Health state utility values measured by the SF-6D and EQ-5D indices are the dependent variables. Independent variables include background characteristics, mental health and physical health conditions. Regression models were estimated using OLS for the SF-6D and tobit for EQ-5D. Further regressions were carried out to consider the impact of mental health and physical health morbidities and the impact of severity of conditions on utility values.
Results: Mental health conditions tend to have a larger impact on health state utility values than physical health conditions. The mental health conditions associated with the highest decrements in utility are: depression, mixed anxiety and depressive disorders and long-term depression. Interaction terms used to model the effect of co-morbidities are generally found to be positive implying that simply adding the utility decrements for two mental health conditions overestimates the burden of the disease.
Conclusions: This paper presents reliable and representative community based mean SF-6D and EQ-5D estimates with standard errors for health state utility values across a broad range of mental health conditions that can be used in cost effectiveness modelling.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3901021 | PMC |
http://dx.doi.org/10.1186/1477-7525-12-6 | DOI Listing |
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