Exploring the Issues of Valuing Child and Adolescent Health States Using a Mixed Sample of Adolescents and Adults

Understanding UK public views on normative decisions made to value health-related quality of life in children: A qualitative study

Developing methodology for measuring and valuing child health-related quality of life (HRQoL) is a priority for health technology agencies. One aspect of this is normative decisions that are made in child HRQoL valuation. This qualitative study aimed to better understand adult public opinion on the normative questions of whose preferences to elicit (adults, children, or both) and from which perspective (who should be imagined living in impaired health), when valuing child HRQoL. Opinions of the adult UK public (N = 32) were solicited using online semi-structured focus groups, featuring a breadth of age, sex, ethnicities, and responsibility for children under 18 years. Participants were provided with bespoke informational material on health state valuation and were probed for their views. Arguments for and against different positions were discussed. Data was analysed using framework analysis. Participants demonstrated near-to-universal agreement that children should be involved in valuation in some form, yet this should differ depending on age or maturity. There was strong support for approaches combining involvement from children and adults (e.g., their parents), especially for younger children. There was little intuitive support for the 'taxpayer argument' for asking taxpaying adults. In the context of greater involvement of children in valuation, most participants supported using an 'own' perspective. Most participants thought that valuation study participants should know the exercise is about valuing child health states for ethical reasons. Informed views from the UK public on who should be asked and with what perspective when valuing child HRQoL appear to differ from normative positions previously advocated by some health economists, such as prioritising the preferences of taxpaying adults. In contrast, the results suggest including adults and children in valuation, with the proviso that the children are of an appropriate age and level of maturity, and that an own perspective is used wherever possible.

Whose Time Trade-Off Should Be Used? Anchoring Discrete Choice Experiment Latent Utilities in Health State Valuation

OBJECTIVES

To compare anchored discrete choice experiment (DCE) utility values using own versus others' time trade-off (TTO) responses in the valuation of SF-6Dv2.

METHODS

A representative sample of the general population was recruited in China. Through face-to-face interviews, both DCE and TTO data were collected from a randomly selected half of the respondents (own TTO sample), whereas only TTO data were collected from the other half (others' TTO sample). Conditional logit model was used to estimate DCE latent utilities. Three anchoring methods, including using the observed and the modeled TTO values for the worst state, and mapping DCE values onto TTO, were used to scale the latent utilities to health utilities. Prediction accuracy was assessed using intraclass correlation coefficient, mean absolute difference, and root mean squared difference compared with the mean observed TTO values between the anchoring results using the own versus others' TTO data.

RESULTS

Demographic characteristics were comparable between the own TTO sample (n = 252) and the others' TTO sample (n = 251). The mean (SD) observed TTO value for the worst state was -0.259 (0.591) for the own TTO sample and -0.236 (0.616) for the others' TTO sample. Anchoring DCE using own TTOs consistently showed a better prediction accuracy than using others' TTOs across the 3 anchoring methods in terms of the intraclass correlation coefficient (0.835-0.873 vs 0.771-0.804), mean absolute difference (0.127-0.181 vs 0.146-0.203), and root mean squared difference (0.164-0.237 vs 0.192-0.270).

CONCLUSION

When anchoring DCE-derived latent utilities onto the health utility scale, respondents' own TTO data would be preferred to TTO data obtained from a different sample.

Understanding the valuation of paediatric health-related quality of life: a qualitative study protocol

INTRODUCTION

There is evidence from previous studies that adults value paediatric health-related quality of life (HRQoL) and adult HRQoL differently. Less is known about how adolescents value paediatric HRQoL and whether their valuation and decision-making processes differ from those of adults. Discrete choice experiments (DCEs) are widely used to develop value sets for measures of HRQoL, but there is still much to understand about whether and how the methods choices in the implementation of DCE valuation tasks, such as format, presentation and perspective, affect the decision-making process of participants. This paper describes the protocol for a qualitative study that aims to explore the decision-making process of adults and adolescents when completing DCE valuation tasks. The study will also explore the impact of methodological choices in the design of DCE studies (including decisions about format and presentation) on participants' thinking process.

METHODS AND ANALYSIS

An interview protocol has been developed using DCE valuation tasks. Interviews will be conducted online via Zoom with both an adolescent and adult sample. In the interview, the participant will be asked to go through some DCE valuation tasks while 'thinking aloud'. After completion of the survey, participants will then be asked some predetermined questions in relation to various aspects of the DCE tasks. Interviews will be recorded and transcribed and analysed using a thematic analysis approach.

ETHICS AND DISSEMINATION

Ethics approval for this study has been received for the adult sample (UTS ETH20-9632) as well as the youth sample (UTS ETH22-6970) from the University of Technology Sydney Human Research Ethics Committee. Results from this study will inform the methods to be used in development of value sets for use in the health technology assessment of paediatric interventions and treatments. Findings from this study will also be disseminated through national/international conferences and peer-reviewed journals.

Value Set for the EQ-5D-Y-3L in Hungary

BACKGROUND

The Hungarian health technology assessment guidelines recommend the use of the EuroQol instrument family in quality-adjusted life-year calculations. However, no national value set exists for the EQ-5D-Y-3L or any other youth-specific instrument.

OBJECTIVE

This study aims to develop a national value set of the EQ-5D-Y-3L for Hungary based on preferences of the general adult population.

METHODS

This study followed the international valuation protocol for the EQ-5D-Y-3L. Two independent samples, representative of the Hungarian general adult population in terms of age and sex were recruited to complete online discrete choice experiment (DCE) tasks and composite time trade-off (cTTO) tasks by computer-assisted personal interviews. Adults valued hypothetical EQ-5D-Y-3L health states considering the health of a 10-year-old child. DCE data were modelled using a mixed logit model with random-correlated coefficients. Latent DCE utility estimates were mapped onto mean observed cTTO utilities using ordinary least squares regression.

RESULTS

Overall, 996 and 200 respondents completed the DCE and cTTO surveys, respectively. For each domain, the value set resulted in larger utility decrements with more severe response levels. The relative importance of domains by level 3 coefficients was as follows: having pain or discomfort > feeling worried, sad or unhappy > mobility > doing usual activities > looking after myself. Overall, 12.3% of all health states had negative utilities in the value set, with the worst health state having the lowest predicted utility of - 0.485.

CONCLUSION

This study developed a national value set of the EQ-5D-Y-3L for Hungary. The value set enables to evaluate the cost utility of health technologies for children and adolescents based on societal preferences in Hungary.

Analytical Considerations When Anchoring Discrete Choice Experiment Values Using Composite Time Trade-Off Data: The Case of EQ-5D-Y-3L

Discrete choice experiments (DCEs) are becoming increasingly used to elicit preferences for children's health states. However, DCE data need to be anchored to produce value sets, and composite time trade-off (cTTO) data are typically used in the context of EQ-5D-Y-3L valuation. The objective of this paper is to compare different anchoring methods, summarise the characteristics of the value sets they produce, and outline key considerations for analysts. Three anchoring methods were compared using data from published studies: (1) rescaling using the mean value for the worst health state; (2) linear mapping; and (3) hybrid modelling. The worst state rescaling value set had the largest range. The worst state rescaling and linear mapping value sets preserved the relative importance of the dimensions from the DCE, whereas the hybrid model value set did not. Overall, the predicted values from the hybrid model value set were more closely aligned with the cTTO values. These findings are relatively generalisable. Deciding upon which anchoring approach to use is challenging, as there are numerous considerations. Where cTTO data are collected for more than one health state, anchoring on the worst health state will arguably be suboptimal. However, the final choice of approach may require value judgements to be made. Researchers should seek input from relevant stakeholders when commencing valuation studies to help guide decisions and should clearly set out their rationale for their preferred anchoring approach in study outputs.