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OP55 Health Technology Assessment In Children And Adolescents: Adolescent Preferences For Child Health Utility 9D Health States

  • Julie Ratcliffe, Gang Chen, Elisabeth Huynh, Frank Xu, Katherine Stevens, John Brazier and Joffre Swait...



Preference-based measures of health-related quality of life play a key role in the calculation of Quality-Adjusted Life Years (QALYs) for Health Technology Assessment (HTA). The Child Health Utility 9D (CHU9D) is a new preference-based instrument designed specifically for application in children and adolescents (aged 7 to 17 years). This study aimed to compare Chinese and Australian adolescent population preferences for CHU9D health states using profile case best worst scaling (BWS) methods.


Fifty CHU9D health states (blocked into five survey versions) were generated for valuation using a fractional factorial design. Study participants were recruited through an online panel company in Australia, and through primary and secondary schools in China. A latent class modelling framework was adopted for econometric analysis.


A total of 1,982 respondents (51 percent female) in Australia and 902 respondents (43 percent female) in China provided useable survey responses. Latent class analysis indicated the existence of preference heterogeneity for both population groups. In the Australian sample, respondents in Class I placed the most importance on the mental health dimensions of the CHU9D (for example, Worried and Annoyed) and the least importance on daily activities (for example, Activities, Daily routine, Sleep), whilst respondents in Class II placed equal weights on all attributes. In the Chinese sample, respondents in Class I placed the most importance on the Activities dimension of the CHU9D and the least importance on the Annoyed dimension, whist Class II placed the most importance on the Schoolwork dimension and the least importance on Pain.


This study has provided important cross-country insights into the use of profile case BWS methods to elicit health state preferences with young people for application in HTA in children and adolescents. The differential latent classes identified between Australia and China highlights the necessity to derive country-specific adolescent scoring algorithms for the CHU9D instrument for application in HTA.


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