OBJECTIVES

There are increasing concerns about the use of a generic preference based measure to capture health benefits in the area of mental health. We present the preference weights for a new preference-based measure for mental health, the ReQoL-UI, derived from Recovering Quality of Life (ReQoL-10), a recovery measure developed with mental health service users

METHODS

Item response theory analyses were undertaken using survey responses from a sample of mental health service users (n = 4266) to derive a health state classification system from ReQoL-10 and to select health states amenable to valuation. A valuation survey with 305 members of the UK general population representative in terms of age, gender and region was conducted using face-to-face interviewer administered time-trade-off (TTO) with props. To produce utility values for every health state described by the ReQoL-UI a series of regression models including random effects models were fitted to the data.

RESULTS

The ReQoL-UI health state classification system comprises six mental health themes (activity; belonging; choice, control and autonomy; hope; self-perception and well-being) and one physical health item, with 5 severity levels for each item. Sixty-four health states were valued. The selected model was a random effects model involving squared terms and interactions between mental health and the physical health item. The model had significant and consistent coefficients, RMSE of 0.07 and lowest Akaike and Bayesian Information Criterion.

CONCLUSIONS

ReQoL-UI has been generated using a novel method to select health state values and widely accepted interviewer administered TTO to elicit preferences. The valuation of the ReQoL-UI produced a valid set of preference weights that can be used to generate QALYs for use in cost-utility analysis of interventions in the area of mental health.