Literature DB >> 21033766

Valuing Child Health Utility 9D health states with a young adolescent sample: a feasibility study to compare best-worst scaling discrete-choice experiment, standard gamble and time trade-off methods.

Julie Ratcliffe1, Leah Couzner, Terry Flynn, Michael Sawyer, Katherine Stevens, John Brazier, Leonie Burgess.   

Abstract

QALYs are increasingly being utilized as a health outcome measure to calculate the benefits of new treatments and interventions within cost-utility analyses for economic evaluation. Cost-utility analyses of adolescent-specific treatment programmes are scant in comparison with those reported upon for adults and tend to incorporate the views of clinicians or adults as the main source of preferences. However, it is not clear that the views of adults are in accordance with those of adolescents on this issue. Hence, the treatments and interventions most highly valued by adults may not correspond with those most highly valued by adolescents. Ordinal methods for health state valuation may be more easily understood and interpreted by young adolescent samples than conventional approaches. The availability of young adolescent-specific health state values for the estimation of QALYs will provide new insights into the types of treatment programmes and health services that are most highly valued by young adolescents. The first objective of this study was to assess the feasibility of applying best-worst scaling (BWS) discrete-choice experiment (DCE) methods in a young adolescent sample to value health states defined by the Child Health Utility 9D (CHU9D) instrument, a new generic preference-based measure of health-related quality of life developed specifically for application in young people. The second objective was to compare BWS DCE questions (where respondents are asked to indicate the best and worst attribute for each of a number of health states, presented one at a time) with conventional time trade-off (TTO) and standard gamble (SG) questions in terms of ease of understanding and completeness. A feasibility study sample of consenting young adolescent school children (n = 16) aged 11-13 years participated in a face-to-face interview in which they were asked to indicate the best and worst attribute levels from a series of health states defined by the CHU9D, presented one at a time. Participants were also randomly allocated to receive additional conventional TTO or SG questions and prompted to indicate how difficult they found them to complete. The results indicate that participants were able to readily choose 'best' and 'worst' dimension levels in each of the CHU9D health states presented to them and provide justification for their choices. Furthermore, when presented with TTO or SG questions and prompted to make comparisons, participants found the BWS DCE task easier to understand and complete. The results of this feasibility study suggest that BWS DCE methods are potentially more readily understood and interpretable by vulnerable populations (e.g. young adolescents). These findings lend support to the potential application of BWS DCE methods to undertake large-scale health state valuation studies directly with young adolescent population samples.

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Mesh:

Year:  2011        PMID: 21033766     DOI: 10.2165/11536960-000000000-00000

Source DB:  PubMed          Journal:  Appl Health Econ Health Policy        ISSN: 1175-5652            Impact factor:   2.561


  51 in total

1.  An assessment of the construct validity of the CHU9D in the Australian adolescent general population.

Authors:  Julie Ratcliffe; Katherine Stevens; Terry Flynn; John Brazier; Michael Sawyer
Journal:  Qual Life Res       Date:  2011-08-12       Impact factor: 4.147

2.  Assessing capability in economic evaluation: a life course approach?

Authors:  Joanna Coast
Journal:  Eur J Health Econ       Date:  2019-08

3.  Giving a Voice to Marginalised Groups for Health Care Decision Making.

Authors:  Richard De Abreu Lourenço; Nancy Devlin; Kirsten Howard; Jason J Ong; Julie Ratcliffe; Jo Watson; Esther Willing; Elisabeth Huynh
Journal:  Patient       Date:  2020-10-01       Impact factor: 3.883

4.  A review of preference-based measures for the assessment of quality of life in children and adolescents with cerebral palsy.

Authors:  Christine Mpundu-Kaambwa; Gang Chen; Elisabeth Huynh; Remo Russo; Julie Ratcliffe
Journal:  Qual Life Res       Date:  2018-03-22       Impact factor: 4.147

5.  Challenges in health state valuation in paediatric economic evaluation: are QALYs contraindicated?

Authors:  Wendy J Ungar
Journal:  Pharmacoeconomics       Date:  2011-08       Impact factor: 4.981

6.  The Value Adults Place on Child Health and Functional Status.

Authors:  Benjamin M Craig; Derek S Brown; Bryce B Reeve
Journal:  Value Health       Date:  2015-04-15       Impact factor: 5.725

Review 7.  Outcome measurement in economic evaluations of public health interventions: a role for the capability approach?

Authors:  Paula K Lorgelly; Kenny D Lawson; Elisabeth A L Fenwick; Andrew H Briggs
Journal:  Int J Environ Res Public Health       Date:  2010-05-06       Impact factor: 3.390

8.  What's good and bad about contraceptive products?: a best-worst attribute experiment comparing the values of women consumers and GPs.

Authors:  Stephanie A Knox; Rosalie C Viney; Deborah J Street; Marion R Haas; Denzil G Fiebig; Edith Weisberg; Deborah Bateson
Journal:  Pharmacoeconomics       Date:  2012-12-01       Impact factor: 4.981

9.  Validity and responsiveness of the EQ-5D and the KIDSCREEN-10 in children with ADHD.

Authors:  Clazien Bouwmans; Annemarie van der Kolk; Mark Oppe; Saskia Schawo; Elly Stolk; Michel van Agthoven; Jan Buitelaar; LeonaHakkaart van Roijen
Journal:  Eur J Health Econ       Date:  2014-12

10.  Feasibility, Validity and Differences in Adolescent and Adult EQ-5D-Y Health State Valuation in Australia and Spain: An Application of Best-Worst Scaling.

Authors:  Kim Dalziel; Max Catchpool; Borja García-Lorenzo; Inigo Gorostiza; Richard Norman; Oliver Rivero-Arias
Journal:  Pharmacoeconomics       Date:  2020-05       Impact factor: 4.981

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