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Nothing About Us Without Us? A Comparison of Adolescent and Adult Health‐State Values for the Child Health Utility‐9D Using Profile Case Best–Worst Scaling

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  • Julie Ratcliffe
  • Elisabeth Huynh
  • Katherine Stevens
  • John Brazier
  • Michael Sawyer
  • Terry Flynn

Abstract

The main objective of this study was to compare and contrast adolescent and adult values for the Child Health Utility‐9D (CHU9D), a new generic preference‐based measure of health‐related quality of life designed for application in the economic evaluation of treatment and preventive programmes for children and adolescents. Previous studies have indicated that there may be systematic differences in adolescent and adult values for identical health states. An online survey including a series of best–worst scaling discrete choice experiment questions for health states defined by the CHU9D was administered to two general population samples comprising adults and adolescents, respectively. The results highlight potentially important age‐related differences in the values attached to CHU9D dimensions. Adults, in general, placed less weight upon impairments in mental health (worried, sad, annoyed) and more weight upon moderate to severe levels of pain relative to adolescents. The source of values (adults or adolescents) has important implications for economic evaluation and may impact significantly upon healthcare policy. Copyright © 2015 John Wiley & Sons, Ltd.

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  • Julie Ratcliffe & Elisabeth Huynh & Katherine Stevens & John Brazier & Michael Sawyer & Terry Flynn, 2016. "Nothing About Us Without Us? A Comparison of Adolescent and Adult Health‐State Values for the Child Health Utility‐9D Using Profile Case Best–Worst Scaling," Health Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 486-496, April.
  • Handle: RePEc:wly:hlthec:v:25:y:2016:i:4:p:486-496
    DOI: 10.1002/hec.3165
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    References listed on IDEAS

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    1. Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, edition 2, number 9780198725923.
    2. Stavros Petrou, 2003. "Methodological issues raised by preference‐based approaches to measuring the health status of children," Health Economics, John Wiley & Sons, Ltd., vol. 12(8), pages 697-702, August.
    3. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    4. Terry N. Flynn & Elisabeth Huynh & Tim J. Peters & Hareth Al‐Janabi & Sam Clemens & Alison Moody & Joanna Coast, 2015. "Scoring the Icecap‐a Capability Instrument. Estimation of a UK General Population Tariff," Health Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 258-269, March.
    5. Katherine Stevens, 2012. "Valuation of the Child Health Utility 9D Index," PharmacoEconomics, Springer, vol. 30(8), pages 729-747, August.
    6. Katherine Stevens, 2011. "Assessing the performance of a new generic measure of health-related quality of life for children and refining it for use in health state valuation," Applied Health Economics and Health Policy, Springer, vol. 9(3), pages 157-169, May.
    7. Coast, Joanna & Flynn, Terry N. & Natarajan, Lucy & Sproston, Kerry & Lewis, Jane & Louviere, Jordan J. & Peters, Tim J., 2008. "Valuing the ICECAP capability index for older people," Social Science & Medicine, Elsevier, vol. 67(5), pages 874-882, September.
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    1. Ernest H. Law & Annika L. Pickard & Anika Kaczynski & A. Simon Pickard, 2017. "Choice Blindness and Health-State Choices among Adolescents and Adults," Medical Decision Making, , vol. 37(6), pages 680-687, August.
    2. Richard De Abreu Lourenço & Nancy Devlin & Kirsten Howard & Jason J. Ong & Julie Ratcliffe & Jo Watson & Esther Willing & Elisabeth Huynh, 2021. "Giving a Voice to Marginalised Groups for Health Care Decision Making," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 14(1), pages 5-10, January.
    3. Sampson, C. & Garau, M., 2019. "How Should We Measure Quality of Life Impact in Rare Disease? Recent Learnings in Spinal Muscular Atrophy," Briefings 002146, Office of Health Economics.
    4. Kim Dalziel & Max Catchpool & Borja García-Lorenzo & Inigo Gorostiza & Richard Norman & Oliver Rivero-Arias, 2020. "Feasibility, Validity and Differences in Adolescent and Adult EQ-5D-Y Health State Valuation in Australia and Spain: An Application of Best–Worst Scaling," PharmacoEconomics, Springer, vol. 38(5), pages 499-513, May.
    5. Aizaki, Hideo & Fogarty, James, 2019. "An R package and tutorial for case 2 best–worst scaling," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    6. Clara Mukuria & Donna Rowen & Sue Harnan & Andrew Rawdin & Ruth Wong & Roberta Ara & John Brazier, 2019. "An Updated Systematic Review of Studies Mapping (or Cross-Walking) Measures of Health-Related Quality of Life to Generic Preference-Based Measures to Generate Utility Values," Applied Health Economics and Health Policy, Springer, vol. 17(3), pages 295-313, June.
    7. Carla Guerriero & Neus Abrines Jaume & Karla Diaz-Ordaz & Katherine Loraine Brown & Jo Wray & Joan Ashworth & Matt Abbiss & John Cairns, 2020. "Using Animation to Self-Report Health: A Randomized Experiment with Children," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 13(2), pages 175-188, April.
    8. Donna Rowen & Oliver Rivero-Arias & Nancy Devlin & Julie Ratcliffe, 2020. "Review of Valuation Methods of Preference-Based Measures of Health for Economic Evaluation in Child and Adolescent Populations: Where are We Now and Where are We Going?," PharmacoEconomics, Springer, vol. 38(4), pages 325-340, April.

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