Valuation of the Child Health Utility Index 9D (CHU9D)

Stevens, K (2010): Valuation of the Child Health Utility Index 9D (CHU9D).

Abstract

Objectives The aim of this study was to test the feasibility of estimating preference weights for all health states defined by the Child Health Utility 9D (CHU9D), a new generic measure of health related quality of life for children. This will allow the calculation of quality adjusted life years (QALYs) for use in paediatric economic evaluation.

Methods Valuation interviews were undertaken with 300 members of the UK adult general population using standard gamble and ranking valuation methods. Regression modelling was undertaken to estimate models that could predict a value for every health state defined by the CHU9D. A range of models were tested and evaluated based on their predictive performance.

Results Models estimated on the standard gamble data performed better than the rank model. All models had a few inconsistencies or insignificant levels and so further modelling was done to estimate a parsimonious consistent regression model, by combining inconsistent levels and removing non significant levels. The final preferred model was an OLS model where all coefficients were significant, there were no inconsistencies and the model had the best predictive performance.

Conclusion This research has demonstrated it is feasible to value the CHU9D descriptive system and preference weights for each health state can be generated to allow the calculation of QALYs. The CHU9D can now be used in the economic evaluation of paediatric health care interventions. Further research is needed to investigate the impact of children’s preferences for the health states and what methods could be used to obtain these preferences.

• Item Type: MPRA Paper
• Language: English
• Keywords: economic evaluation; quality of life; paediatric; preference based measures; health state valuation
• Subjects: I - Health, Education, and Welfare > I3 - Welfare, Well-Being, and Poverty > I31 - General Welfare, Well-Being; I - Health, Education, and Welfare > I1 - Health > I19 - Other

References

Stevens KJ (2009). Developing a descriptive system for a new preference-based measure of health related quality of life for children. Quality of Life Research 18(8):1105-13.

Stevens KJ (2010). Working with children to develop dimensions for a preference-based, generic, pediatric health-related quality-of-life measure. Qualitative Health Research 20:340-51.

Stevens KJ (2010). 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. Health Economics and Decision Science Discussion Paper 10/02. Available from http://eprints.whiterose.ac.uk/view/iau/Sheffield=2EHCM=2EWP.html

Gold MR, Siegel JE, Russell LB, et al (1996). Cost effectiveness in health and medicine. Oxford: Oxford University Press.

Brazier JE, Deverill M, Harper R, et al (1999). A review of the use of health status measures in economic evaluation. Health Technology Assessment 3(9).

National Institute for Clinical Excellence (2004). Guide to the methods of technology appraisal. London: NICE.

Brazier JE, Roberts J, Deverill M (2002). The estimation of a preference based measure of health from the SF-36. Journal of Health Economics 21(2):271-92.

Torrance G, Feeny D, Furling W, Barr R, Zhang Y, Wang Q (1996). Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Medical Care 34:702-22.

Stevens KJ, Brazier JE, McKenna SP, Doward LC, Cork MJ (2005). The development of a preference-based measure of health in children with atopic dermatitis. British Journal of Dermatology 153:372-7.

Brazier JE, Ratcliffe J, Salomon J, Tsuchiya A (2007). Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press.

The MVH Group: Dolan P, Gudex C, Kind P, Williams A (2004). The measurement and valuation of health. First report on the main survey. Centre for Health Economics, University of York.

McCabe C, Stevens K, Roberts J, Brazier JE (2005). Health state values for the Health Utilities Index Mark 2 descriptive system: results from a UK valuation survey. Health Economics 14(3):231-44.

Dolan P (1997). Modelling valuations for EuroQol health states. Medical Care 35(11):1095-108.

Patrick DL, Starks HE, Cain KC, et al (1994). Measuring preferences for health states worse than death. Medical Decision Making 14:9-18.

Names and numbers manual. http://www.afd.co.uk/manuals/namesandnumbers/contents.htm. Accessed 03/07/2008

Kharroubi SA, Brazier JE, Roberts J, O’Hagan A (2007). Modelling SF-6D health state preference data using a nonparametric Bayesian method. Journal of Health Economics 26:597-612.

Kharroubi S, McCabe C (2008). Modelling HUI 2 health state preference data using a nonparametric Bayesian method. Medical Decision Making 28:875-87.

Gujarati DN (1995). Basic Econometrics. Chapter 3. McGraw-Hill, Inc. Third Edition.

McCabe C, Brazier JE, Gilks P, Tsuchiya A, Roberts J, O’Hagan A, Stevens K (2006). Using rank data to estimate health state utility models. Journal of Health Economics 25:418-31.

O’Brien BJ, Drummond MF (1994). Statistical versus quantitative significance in the socioeconomic evaluation of medicines. Pharmacoeconomics 5:389.

Ljung G, Box G (1979). On a measure of lack of fit in time series models. Biometrika 66:265-70.

Brazier JE, Roberts JR (2004). The estimation of a preference-based measure of health from the SF-12. Medical Care 42(9).

Lloyd A (2003). Threats to the estimation of benefit: are preference estimation methods accurate? Health Economics 12:393-402.

Walters SJ, Brazier JE (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D and SF-6D. Quality of Life Research 14:1523-32.

Ratcliffe J, Brazier JE, Tsuchiya A, Symonds T, Brown M (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 18(11):1261-76.

Brazier J, Rowen D, Yang Y, Tsuchiya A (2009). Using rank and discrete choice data to estimate health state utility values on the QALY scale. Health Economics and Decision Science Discussion Paper 09/10. The University of Sheffield. Available from http://eprints.whiterose.ac.uk/view/iau/Sheffield=2EHCM=2EWP.html