Abstract
BackgroundThe 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.MethodsThis 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.ResultsMental 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.ConclusionsThis 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.
Highlights
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
Health State Utility Values (HSUV) are scarce for more complex conditions like psychosis, phobia and panic disorder [4] and disutility associated with different levels of severity. Decision makers such as the National Institute for Health and Care Excellence (NICE) in the UK recommend that the results of economic evaluations in healthcare are presented in terms of quality adjusted life years (QALYs) which are a composite measure of health related quality of life and life expectancy
The most commonly used measures for putting the ‘Q’ into the QALY are generic preference-based measures of health, such as the EQ-5D [5] and SF-6D [6].This paper seeks to address the lack of available HSUVs associated with mental health conditions by providing estimates that can be used in economic evaluation from a representative community based sample
Summary
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. The most commonly used measures for putting the ‘Q’ into the QALY are generic preference-based measures of health, such as the EQ-5D [5] and SF-6D [6].This paper seeks to address the lack of available HSUVs associated with mental health conditions by providing estimates that can be used in economic evaluation from a representative community based sample. Another important feature of mental health conditions is the common existence of co-morbidities, arising from other mental health conditions as well as physical ones. While attempts have been made to calculate HSUVs for comorbid physical conditions [9], for example by adding or multiplying the effects of separate conditions, there is still overall very little empirical research on comorbidities for those with mental health conditions
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