Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .
Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm.
In contrast to the recent proliferation of studies incorporating ordinal methods to generate health state values from adults , to date relatively few studies have utilised 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 design ed 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 on-line format in which consenting community based Australian adolescents aged 11 - 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 r and om 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 population
Conclusions The last 10 years has seen a substantial increase in the number of mapping studies and some evidence of advancement in methods with consideration of models beyond OLS and greater reporting of predictive ability of mapping functions
Background Mapping is an increasingly common method used to predict instrument-specific preference-based health-state utility values ( HSUVs ) from data obtained from another health-related quality of life ( HRQoL ) measure .
There have been several method ological developments in this area since a previous review up to 2007 .