IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

Valuing child health utility 9D health states with a young adolescent sample

Listed author(s):
  • Julie Ratcliffe

    ()

  • Leah Couzner
  • Terry Flynn
  • Michael Sawyer
  • Katherine Stevens
  • John Brazier
  • Leonie Burgess
Registered author(s):

    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. Copyright Adis Data Information BV 2011

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://hdl.handle.net/10.2165/11536960-000000000-00000
    Download Restriction: Access to full text is restricted to subscribers.

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Springer in its journal Applied Health Economics and Health Policy.

    Volume (Year): 9 (2011)
    Issue (Month): 1 (January)
    Pages: 15-27

    as
    in new window

    Handle: RePEc:spr:aphecp:v:9:y:2011:i:1:p:15-27
    DOI: 10.2165/11536960-000000000-00000
    Contact details of provider: Web page: http://www.springer.com

    Order Information: Web: http://www.springer.com/economics/journal/40258

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as
    in new window


    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. Julie Ratcliffe & John Brazier & Aki Tsuchiya & Tara Symonds & Martin Brown, 2009. "Using DCE and ranking data to estimate cardinal values for health states for deriving a preference-based single index from the sexual quality of life questionnaire," Health Economics, John Wiley & Sons, Ltd., vol. 18(11), pages 1261-1276.
    3. McCabe, Christopher & Brazier, John & Gilks, Peter & Tsuchiya, Aki & Roberts, Jennifer & O'Hagan, Anthony & Stevens, Katherine, 2006. "Using rank data to estimate health state utility models," Journal of Health Economics, Elsevier, vol. 25(3), pages 418-431, May.
    4. 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.
    5. Ryan, Mandy & Netten, Ann & Skatun, Diane & Smith, Paul, 2006. "Using discrete choice experiments to estimate a preference-based measure of outcome--An application to social care for older people," Journal of Health Economics, Elsevier, vol. 25(5), pages 927-944, September.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:spr:aphecp:v:9:y:2011:i:1:p:15-27. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla)

    or (Rebekah McClure)

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.