This paper reports the results of a best–worst scaling (BWS) study to value the Investigating Choice Experiments Capability Measure for Adults (ICECAP-A), a new capability measure among adults, in a UK setting. A main effects plan plus its foldover was used to estimate weights for each of the four levels of all five attributes. The BWS study was administered to 413 randomly sampled individuals, together with sociodemographic and other questions. Scale-adjusted latent class analyses identified two preference and two (variance) scale classes. Ability to characterize preference and scale heterogeneity was limited, but data quality was good, and the final model exhibited a high pseudo-r-squared. After adjusting for heterogeneity, a population tariff was estimated. This showed that ‘attachment’ and ‘stability’ each account for around 22% of the space, and ‘autonomy’, ‘achievement’ and ‘enjoyment’ account for around 18% each. Across all attributes, greater value was placed on the difference between the lowest levels of capability than between the highest. This tariff will enable ICECAP-A to be used in economic evaluation both within the field of health and across public policy generally. © 2013 The Authors. Health Economics published by John Wiley & Sons Ltd.

In contrast to the recent proliferation of studies incorporating ordinal methods to generate health state values from adults, to date relatively few studies have utilized ordinal methods to generate health state values from adolescents. This paper reports upon a study to apply profile case best worst scaling methods to derive a new adolescent specific scoring algorithm for the Child Health Utility 9D (CHU9D), a generic preference based instrument that has been specifically designed for the estimation of quality adjusted life years for the economic evaluation of health care treatment and preventive programs targeted at young people. A survey was developed for administration in an online format in which consenting community based Australian adolescents aged 11 to 17 years (N=1982) indicated the best and worst features of a series of 10 health states derived from the CHU9D descriptive system. The data were analyzed using latent class conditional logit models to estimate values (part worth utilities) for each level of the nine attributes relating to the CHU9D. A marginal utility matrix was then estimated to generate an adolescent-specific scoring algorithm on the full health = 1 and dead = 0 scale required for the calculation of QALYs. It was evident that different decision processes were being used in the best and worst choices. Whilst respondents appeared readily able to choose 'best' attribute levels for the CHU9D health states, a large amount of random variability and indeed different decision rules were evident for the choice of 'worst' attribute levels, to the extent that the best and worst data should not be pooled from the statistical perspective. The optimal adolescent-specific scoring algorithm was therefore derived using data obtained from the best choices only. The study provides important insights into the use of profile case best worst scaling methods to generate health state values with adolescent populations.3

The main objective of this study was to compare and contrast adolescent and adult values for the Child Health Utility-9D (CHU9D), a new generic preference-based measure of health-related quality of life designed for application in the economic evaluation of treatment and preventive programmes for children and adolescents. Previous studies have indicated that there may be systematic differences in adolescent and adult values for identical health states. An online survey including a series of best-worst scaling discrete choice experiment questions for health states defined by the CHU9D was administered to two general population samples comprising adults and adolescents, respectively. The results highlight potentially important age-related differences in the values attached to CHU9D dimensions. Adults, in general, placed less weight upon impairments in mental health (worried, sad, annoyed) and more weight upon moderate to severe levels of pain relative to adolescents. The source of values (adults or adolescents) has important implications for economic evaluation and may impact significantly upon healthcare policy.

The study results are encouraging and illustrate the potential for both the CHU9D and the EQ-5D-Y to be more widely used for measuring and valuing the HRQOL of adolescent populations in Australia and internationally. Generating adolescent-specific scoring algorithms pertaining to each instrument and an empirical comparison of the resulting utilities is a natural next step. More evidence is required from the application of the CHU9D and the EQ-5D-Y in specific patient groups in adolescent health settings to inform the choice of instrument for measuring and valuing the HRQOL for the economic evaluation of adolescent health care treatments and services.

End of life care may have elements of value that go beyond health. A generic measure of the benefits of end of life care could be helpful to decision makers. Such a measure, based on the capability approach, has recently been developed: the ICECAP Supportive Care Measure. This paper reports the first valuation exercise for that measure, with data from 6020 individuals collected from an on-line general population panel during June 2013. Individuals were asked to complete a stated choice experiment that combined best-worst scaling and a standard discrete choice experiment. Analysis of the best-worst data used limited dependent variable models within the random utility framework including the multinomial logit models and latent class choice model analysis. Exploratory steps were taken to determine the similarity of the best-worst and DCE data before formal testing and pooling of the two data sources. Combined data were analysed in a heteroscedastic conditional logit model adjusting for continuous scale. Two sets of tariffs were generated, one from the best-worst data capturing only main effects, and a second from the pooled data allowing for two-way interactions. Either tariff could be used in economic evaluation of interventions at the end of life, although there are advantages and disadvantages with each. This extensive valuation exercise for the ICECAP Supportive Care Measure, with a large number of members of the general public, could be complemented in the future with best-worst scaling studies amongst those experiencing the end of life.