Why do multi-attribute utility instruments produce different utilities: the relative importance of the descriptive systems, scale and ‘micro-utility-effects

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• 作者：Jeff Richardson ; Angelo Iezzi ; Munir A. Khan
• 关键词：MAU instruments ; Cost ; utility analysis ; Utility
• 刊名：Quality of Life Research
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：24
• 期：8
• 页码：2045-2053
• 全文大小：446 KB
• 参考文献：1.Richardson, J., McKie, J., & Bariola, E. (2014). Multi attribute utility instruments and their use. In A. J. Culyer (Ed.), Encyclopedia of health economics (pp. 341-57). San Diego: Elsevier Science.View Article
  2.WHO. (2001). International classification of functioning, disability and health. Geneva: World Health Organization http://?apps.?who.?int/?classifications/?icfbrowser/-/span> Accessed 27 July 2013.
  3.Fryback, D. G., Palta, M., Cherepanov, D., Bolt, D., & Kim, J. (2010). Comparison of 5 health related quality of life indexes using item response theory analysis. Medical Decision Making, 30(1), 5-5.PubMed Central PubMed View Article
  4.Hawthorne, G., Richardson, J., & Day, N. A. (2001). A comparison of the assessment of quality of life (AQoL) with four other generic utility instruments. Annals of Medicine, 33, 358-70.PubMed View Article
  5.Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2014). Comparing and explaining differences in the content, sensitivity and magnitude of incremental utilities predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB and AQoL-8D multi attribute utility instruments- Medical Decision Making,. doi:10.-177/-272989X14543107-/span> .PubMed
  6.Whitehurst, D. G. T., Norman, R., Brazier, J. E., & Viney, R. (2014). Comparison of contemporaneous EQ-5D and SF-6D responses using scoring algorithms derived from similar valuation exercises. Value in Health, 17(5), 570-77.PubMed View Article
  7.Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2012). Cross-national comparison of twelve quality of life instruments: MIC paper 1: Background, questions, instruments, research paper 76. Melbourne: Centre for Health Economics, Monash University http://?www.?buseco.?monash.?edu.?au/?centres/?che/?pubs/?researchpaper76.?pdf . Accessed 29 July 2013.
  8.Richardson, J., Khan, M. A., Iezzi, A., & Maxwell, A. (2012). Cross-national comparison of twelve quality of life instruments, research papers 78, 80-em class="EmphasisTypeItalic">83, 85. MIC report: 2: Australia; 3: UK; 4: USA; 5: Canada; 6: Norway; 7: Germany. Melbourne: Centre for Health Economics, Monash University, http://?www.?buseco.?monash.?edu.?au/?centres/?che/?che-publications.?html Accessed 25 Jan 2013.
  9.Richardson, J., Cummins, R. A., Olsen, J. A., Kaplan, R., Coast, J., & Schlander, M. (2015). The Multi instrument comparison (MIC) database, http://?www.?aqol.?com.?au/?index.?php/?aqol-current . Accessed 16 Jan 2015.
  10.Brazier, J., Roberts, J., & Deverill, M. (2002). The estimation of a preference-based measure of health from the SF-36. Journal of Health Economics, 21, 271-92.PubMed View Article
  11.Feeny, D., Furlong, W., Torrance, G., Goldsmith, C., Zhu, Z., DePauw, S., et al. (2002). Multi attribute and single attribute utility functions for the Health Utilities Index Mark 3 System. Medical Care, 40(2), 113-28.PubMed View Article
  12.Sintonen, H., & Pekurinen, M. (1993). A fifteen-dimensional measure of health related quality of life (15D) and its applications. In S. Walker & R. Rosser (Eds.), Quality of life assessment. Dordrecht: Kluwer Academic Publishers.
  13.Richardson, J., Sinha, K., Iezzi, A., & Khan, M. A. (2014). Modelling utility weights for the assessment of quality of life (AQoL) 8D. Quality of Life Research, 23(8), 2395-404.PubMed View Article
  14.Rabin, R., Oemar, M., Oppe, M., Janssen, B., & Herdman, M. (2011). EQ-5D-5L User guide: Basic information on how to use the EQ-5D-5L instrument. Rotterdam: EuroQoL Group, http://?www.?euroqol.?org/?fileadmin/?user_?upload/?Documenten/?PDF/?Folders_?Flyers/?UserGuide_?EQ-5D-5L.?pdf . Accessed 13 Mar 2014.
  15.van Hout, B., Janssen, M. F., Feng, Y., Kohlmann, T., Busschbach, J., Golicki, D., et al. (2012). Interim scoring for the EQ-5D-5L: Mapping the EQ-5D-5L to EQ-5D-3L value sets. Value in Health, 15, 708-15.PubMed View Article
  16.Richardson J., Chen G., Khan M. A., Lezzi A. (2014). Can multi attribute utility instruments adequately account for subjective well-being? Medical Decsion Making. Accepted 13 Dec 2014.
  
• 作者单位：Jeff Richardson (1)
  Angelo Iezzi (1)
  Munir A. Khan (1)
  
  1. Centre for Health Economics, Monash Business School, Monash University, Wellington Road, Clayton, VIC, 3800, Australia
  
• 刊物类别：Medicine
• 刊物主题：Medicine & Public Health
  Quality of Life Research
  Sociology
  Public Health
  
• 出版者：Springer Netherlands
• ISSN：1573-2649

文摘

Purpose Health state utilities measured by the major multi-attribute utility instruments differ. Understanding the reasons for this is important for the choice of instrument and for research designed to reconcile these differences. This paper investigates these reasons by explaining pairwise differences between utilities derived from six multi-attribute utility instruments in terms of (1) their implicit measurement scales; (2) the structure of their descriptive systems; and (3) ‘micro-utility effects- scale-adjusted differences attributable to their utility formula. Methods The EQ-5D-5L, SF-6D, HUI 3, 15D and AQoL-8D were administered to 8,019 individuals. Utilities and unweighted values were calculated using each instrument. Scale effects were determined by the linear relationship between utilities, the effect of the descriptive system by comparison of scale-adjusted values and ‘micro-utility effects-by the unexplained difference between utilities and values. Results Overall, 66?% of the differences between utilities was attributable to the descriptive systems, 30.3?% to scale effects and 3.7?% to micro-utility effects. Discussion Results imply that the revision of utility algorithms will not reconcile differences between instruments. The dominating importance of the descriptive system highlights the need for researchers to select the instrument most capable of describing the health states relevant for a study. Conclusions Reconciliation of inconsistent utilities produced by different instruments must focus primarily upon the content of the descriptive system. Utility weights primarily determine the measurement scale. Other differences, attributable to utility formula, are comparatively unimportant.