IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v36y2016i2p160-175.html
   My bibliography  Save this article

Mapping between 6 Multiattribute Utility Instruments

Author

Listed:
  • Gang Chen
  • Munir A. Khan
  • Angelo Iezzi
  • Julie Ratcliffe
  • Jeff Richardson

Abstract

Background: Cost-utility analyses commonly employ a multiattribute utility (MAU) instrument to estimate the health state utilities, which are needed to calculate quality-adjusted life years. Different MAU instruments predict significantly different utilities, which makes comparison of results from different evaluation studies problematical. Aim: This article presents mapping functions (“crosswalks†) from 6 MAU instruments (EQ-5D-5L, SF-6D, Health Utilities Index 3 [HUI 3], 15D, Quality of Well-Being [QWB], and Assessment of Quality of Life 8D [AQoL-8D]) to each of the other 5 instruments in the study: a total of 30 mapping functions. Methods: Data were obtained from a multi-instrument comparison survey of the public and patients in 7 disease areas conducted in 6 countries (Australia, Canada, Germany, Norway, United Kingdom, and United States). The 8022 respondents were administered each of the 6 study instruments. Mapping equations between each instrument pair were estimated using 4 econometric techniques: ordinary least squares, generalized linear model, censored least absolute deviations, and, for the first time, a robust MM-estimator. Results: Goodness-of-fit indicators for each of the results are within the range of published studies. Transformations reduced discrepancies between predicted utilities. Incremental utilities, which determine the value of quality-related health benefits, are almost perfectly aligned at the sample means. Conclusion: Transformations presented here align the measurement scales of MAU instruments. Their use will increase confidence in the comparability of evaluation studies, which have employed different MAU instruments.

Suggested Citation

  • Gang Chen & Munir A. Khan & Angelo Iezzi & Julie Ratcliffe & Jeff Richardson, 2016. "Mapping between 6 Multiattribute Utility Instruments," Medical Decision Making, , vol. 36(2), pages 160-175, February.
    • Handle: RePEc:sae:medema:v:36:y:2016:i:2:p:160-175
    DOI: 10.1177/0272989X15578127
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X15578127
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X15578127?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Janelle Seymour & Paul McNamee & Anthony Scott & Michela Tinelli, 2010. "Shedding new light onto the ceiling and floor? A quantile regression approach to compare EQ‐5D and SF‐6D responses," Health Economics, John Wiley & Sons, Ltd., vol. 19(6), pages 683-696, June.
    2. Donna Rowen & John Brazier & Aki Tsuchiya & Mónica Hernández Alava, 2012. "Valuing states from multiple measures on the same visual analogue sale: a feasibility study," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 715-729, June.
    3. Powell, James L., 1984. "Least absolute deviations estimation for the censored regression model," Journal of Econometrics, Elsevier, vol. 25(3), pages 303-325, July.
    4. Duncan Mortimer & Leonie Segal, 2008. "Comparing the Incomparable? A Systematic Review of Competing Techniques for Converting Descriptive Measures of Health Status into QALY-Weights," Medical Decision Making, , vol. 28(1), pages 66-89, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lei Si & Liudan Tu & Ya Xie & Gang Chen & Mickaël Hiligsmann & Mingcan Yang & Yanli Zhang & Xi Zhang & Yutong Jiang & Qiujing Wei & Jieruo Gu & Andrew J. Palmer, 2022. "Evaluating Health Related Quality of Life in Older People at Risk of Osteoporotic Fracture: A Head-to-Head Comparison of the EQ-5D-5L and AQoL-6D," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 160(2), pages 809-824, April.
    2. Shitong Xie & Jing Wu & Gang Chen, 2024. "Comparative performance and mapping algorithms between EQ-5D-5L and SF-6Dv2 among the Chinese general population," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 25(1), pages 7-19, February.
    3. Lan Gao & Wei Luo & Utsana Tonmukayakul & Marj Moodie & Gang Chen, 2021. "Mapping MacNew Heart Disease Quality of Life Questionnaire onto country-specific EQ-5D-5L utility scores: a comparison of traditional regression models with a machine learning technique," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(2), pages 341-350, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicholas Mitsakakis & Karen E. Bremner & George Tomlinson & Murray Krahn, 2020. "Exploring the Benefits of Transformations in Health Utility Mapping," Medical Decision Making, , vol. 40(2), pages 183-197, February.
    2. McCarthy, Ian M., 2016. "Eliminating composite bias in treatment effects estimates: Applications to quality of life assessment," Journal of Health Economics, Elsevier, vol. 50(C), pages 47-58.
    3. Héctor Manuel Zárate S., 2005. "Cambios en la estructura salarial: una historia desde la regresión cuanfílica," Monetaria, CEMLA, vol. 0(4), pages 339-364, octubre-d.
    4. Andrés Langebaek R. & Diego Vásquez E., 2007. "Determinantes de la actividad innovadora en la industria manufacturera colombiana," Borradores de Economia 433, Banco de la Republica de Colombia.
    5. Peracchi, Franco, 2002. "On estimating conditional quantiles and distribution functions," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 433-447, February.
    6. Gerrans, Paul & Yap, Ghialy, 2014. "Retirement savings investment choices: Sophisticated or naive?," Pacific-Basin Finance Journal, Elsevier, vol. 30(C), pages 233-250.
    7. Brunner, Eric & Sonstelie, Jon, 2003. "School finance reform and voluntary fiscal federalism," Journal of Public Economics, Elsevier, vol. 87(9-10), pages 2157-2185, September.
    8. Seamus Kent & Alastair Gray & Iryna Schlackow & Crispin Jenkinson & Emma McIntosh, 2015. "Mapping from the Parkinson’s Disease Questionnaire PDQ-39 to the Generic EuroQol EQ-5D-3L," Medical Decision Making, , vol. 35(7), pages 902-911, October.
    9. Eliana Christou & Michael G. Akritas, 2019. "Single index quantile regression for censored data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(4), pages 655-678, December.
    10. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
    11. De Backer, Mickael & El Ghouch, Anouar & Van Keilegom, Ingrid, 2017. "An Adapted Loss Function for Censored Quantile Regression," LIDAM Discussion Papers ISBA 2017003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    12. Qiuqiong Huang & David Dawe & Scott Rozelle & Jikun Huang & Jinxia Wang, 2005. "Irrigation, poverty and inequality in rural China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), pages 159-175, June.
    13. Barton Hughes Hamilton, 1997. "Racial discrimination and professional basketball salaries in the 1990s," Applied Economics, Taylor & Francis Journals, vol. 29(3), pages 287-296.
    14. Anil Kumar, 2012. "Nonparametric estimation of the impact of taxes on female labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 415-439, April.
    15. Eric Nazindigouba Kere, 2016. "Do political economy factors matter in explaining the increase in the production of bioenergy?," WIDER Working Paper Series 025, World Institute for Development Economic Research (UNU-WIDER).
    16. Xue, Hong & Mainville, Denise Y. & You, Wen & Nayga, Rodolfo M., Jr., 2009. "Nutrition Knowledge, Sensory Characteristics and Consumers’ Willingness to Pay for Pasture-Fed Beef," 2009 Annual Meeting, July 26-28, 2009, Milwaukee, Wisconsin 49277, Agricultural and Applied Economics Association.
    17. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    18. Wu Wang & Zhongyi Zhu, 2017. "Conditional empirical likelihood for quantile regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(1), pages 1-16, January.
    19. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    20. Gracious M. Diiro & Abdoul G. Sam & David Kraybill, 2017. "Heterogeneous Effects of Maternal Labor Market Participation on the Nutritional Status of Children: Empirical Evidence from Rural India," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 10(3), pages 609-632, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:36:y:2016:i:2:p:160-175. See general information about how to correct material in RePEc.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.