Abstract
ObjectivesEconomic evaluations often use preference-based value sets (tariffs) for health-related quality of life to quantify health effects. For wellbeing at the end of life, issues beyond health-related quality of life may be important. Therefore, the ICECAP Supportive Care Measure (ICECAP-SCM), based on the capability approach, was developed. A validated German ICECAP-SCM version was published recently. However, tariffs for the German ICECAP-SCM are not available. Therefore, the aim was to determine tariffs for the ICECAP-SCM based on preferences of the German general population.MethodsAn online sample of 2996 participants completed a best–worst scaling (BWS) and a discrete choice experiment (DCE). BWSs required participants to choose the best and worst statement within the same capability state, whereas DCEs required participants to trade-off between two capability states. First, BWS and DCE data were analyzed separately. Subsequently, combined data were analyzed using scale-adjusted conditional logit latent class models. Models were selected based on the stability of solutions and the Bayesian information criterion.ResultsThe two latent class model was identified to be optimal for the BWS, DCE, and combined data, and was used to derive tariffs for the ICECAP-SCM capability states. BWS data captured differences in ICECAP-SCM scale levels, whereas DCE data additionally explained interactions between the seven ICECAP-SCM attributes.DiscussionThe German ICECAP-SCM tariffs can be used in addition to health-related quality of life to quantify effectiveness in economic evaluations. The tariffs based on BWS data were similar for Germany and the UK, whereas the tariffs based on combined data varied. We would recommend to use tariffs based on combined data in German evaluations. However, only results on BWS data are comparable between Germany and the UK, so that tariffs based on BWS data should be used when comparing results between Germany and the UK.
Highlights
According to current guidelines for clinical trials and economic evaluations, patient-reported outcomes should be evaluated in addition to clinical outcomes [1]
The final design consisted of 16 sets to be completed by each respondent with each set accompanied by both a best–worst scaling (BWS) and discrete choice experiment (DCE) task
Between reaching the representative population size of German federal states and closing the survey for particular federal states, another 101 (2%) participants living in the particular federal states were interviewed, they were excluded from analysis
Summary
According to current guidelines for clinical trials and economic evaluations, patient-reported outcomes should be evaluated in addition to clinical outcomes [1]. Most patient-reported outcomes focus on health-related quality of life. Studies focusing on health outcomes like health-related quality of life neglect other relevant issues of wellbeing, such as personal wishes or needs [2, 3]. The exclusive focus on aspect of healthrelated quality of life becomes less relevant for informing decision-making at the end of life. Measures of health-related quality of life may be less suitable to assess effects of interventions at the end of life [7]. Other concepts are important to measure effects in economic evaluations of interventions at the end of life, especially for groups of people whose needs are insufficiently reflected by the concept of healthrelated quality of life
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call