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29-10-2018

Scoring the Child Health Utility 9D instrument: estimation of a Chinese child and adolescent-specific tariff

Auteurs: Gang Chen, Fei Xu, Elisabeth Huynh, Zhiyong Wang, Katherine Stevens, Julie Ratcliffe

Gepubliceerd in: Quality of Life Research | Uitgave 1/2019

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Abstract

Purpose

To derive children and adolescents’ preferences for health states defined by the Chinese version of Child Health Utility 9D (CHU9D-CHN) instrument in China that can be used to estimate quality-adjusted life years (QALYs) for economic evaluation.

Methods

A profile case best–worst scaling (BWS) and a time trade-off (TTO) method were combined to derive a Chinese-specific tariff for the CHU9D-CHN. The BWS survey recruited students from primary and high schools using a multi-stage random sampling method and was administered in a classroom setting, whilst the TTO survey adopted an interviewer-administrated conventional TTO task and was administered to a convenience sample of undergraduate students. A latent class modelling framework was adopted for analysing the BWS data.

Results

Two independent surveys were conducted in Nanjing, China, including a valid sample of 902 students (mean age 13 years) from the BWS survey and a valid sample of 38 students (mean age 18 years) from the TTO survey. The poolability of the best and the worst responses was rejected and the optimal result based on the best responses only. The optimal model suggests the existence of two latent classes. The BWS estimates were further re-anchored onto the QALY scale using the TTO generated health state values via a mapping approach.

Conclusion

This study provides further insights into the use of the BWS method to generate health state values with young people and highlights the potential different decision rules that young people may employ for determining best vs. worst choices in this context.
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Voetnoten
1
It should be noted that additional three students failed to complete the BWS choice experiment, and additional two students cannot complete the TTO tasks.
 
2
Considering the well-documented issue relating to the sensitivity of the log-likelihood ratio test, we have also tried to relax the constraint of some dimension level parameters (e.g. the 5th level of ‘activities’ dimension) in estimating the pooled BWS data, i.e. to allow estimated coefficients differ between the best and the worst. However, the conclusion to not pool the best and the worst data remains the same based on the Swait–Louviere test.
 
3
We have also estimated the scale-adjusted LC model and the log-scale factor estimated for the worst choices was − 0.3 (p < 0.001), indicating the worst choices exhibit less consistency (i.e. exp(− 0.3) = 0.74) across choice sets than the best choices.
 
4
Initially 2–4 classes were considered. The BIC values decreased along with the increased number of classes being specified (i.e. more class is favourable based on the information criteria); however, increasingly more inconsistencies among estimated dimension levels were observed in the 3- or 4-class case. Further considering the % reductions on the likelihood ratio chi-squared statistic L2 of a 7% reduction from 1-class to 2-classes, versus a 2%/1% from 2- to 3- or 3- to 4-class specifications. The 2-class case was selected as the optimal result, similar to the Australian adolescent study result reported by Ratcliffe et al. [23].
 
5
The inconsistencies have been widely reported in the valuation studies regardless of which valuation techniques been adopted [23, 42].
 
6
The adjustment was conducted within each class and with one inconsistence dimension level at a time. The adjustment slightly changed the proportions of the 2 class membership, from 57.32% versus 42.68–57.98% versus 42.02%. The BIC values were 29993.68 in the main model and 29834.74 in the final model.
 
7
In Australian study, respondents in Class 1 (63%) placed the most important weights on mental health dimensions and the least important weights on activities, and daily routine. In Class 2 (37%), respondents placed equal weights on all dimensions.
 
8
Comparison of these established scoring algorithms, with the development of the new Chinese adolescent-specific scoring algorithm documented in this paper indicates some key methodological differences including (i) elicitation methods been used (SG vs. BWS & TTO), (ii) sample size, (iii) whose values were elicited from (adults vs. adolescents), (iv) source of respondents (random street/student sample vs. online panel), (v) the mode of survey delivery (face-to-face interview vs. online survey vs. hard copy questionnaire), (vi) the utility function to be estimated (whether potential interaction terms were considered and tested), and (vii) econometric techniques used to estimate the utility function (OLS vs. latent class modelling).
 
9
Two re-anchoring approaches were adopted in this study. Re-anchoring onto the PITS approach arguably uses less information from the second source of preference (i.e. only elicited utility score from the worst health state was used), as compared to the mapping approach (in which a series of elicited utility scores were all used); however, that does not necessary imply the preferential choice of the re-anchoring approach. Better goodness-of-fit (or less prediction errors) from the mapping approach in this study indicates that empirically it is a preferred approach. Whether this conclusion holds in future studies is unclear, but it is evident that re-scaling based on the PITS state only may not be an optimal approach.
 
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Metagegevens
Titel
Scoring the Child Health Utility 9D instrument: estimation of a Chinese child and adolescent-specific tariff
Auteurs
Gang Chen
Fei Xu
Elisabeth Huynh
Zhiyong Wang
Katherine Stevens
Julie Ratcliffe
Publicatiedatum
29-10-2018
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 1/2019
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-018-2032-z

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