Brazier, J and Rowen, D and Yang, Y and Tsuchiya, A (2009): Using rank and discrete choice data to estimate health state utility values on the QALY scale.
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Objective: Recent years have seen increasing interest in the use of ordinal methods to elicit health state utility values as an alternative to conventional methods such as standard gamble and time trade-off. However, in order to use these health state values in cost effectiveness analysis using cost per quality adjusted life year (QALY) analysis, these values must be anchored on the full health-dead scale. This study addresses this challenge and examines how rank and discrete choice experiment data can be used to elicit health state utility values anchored on the full health-dead scale and compares the results to time trade-off (TTO) results.
Methods: Two valuation studies were conducted using identical methods for two health state classification systems: asthma and overactive bladder. Each valuation study involved interviews of 300 members of the general population using ranking and TTO plus a postal survey using discrete choice experiment sent to all consenting interviewees and a "cold" sample of the general population who were not interviewed.
Results: Overall DCE produced different results from ranking and time trade-off, whereas ranking produced similar results to TTO in one study, but not the other.
Conclusions: Ordinal methods offer a promising alternative to conventional cardinal methods of standard gamble and TTO. However, the results do not appear to be robust across different health state classification systems and potentially different medical conditions. There remains a large and important research agenda to address.
|Item Type:||MPRA Paper|
|Original Title:||Using rank and discrete choice data to estimate health state utility values on the QALY scale|
|Keywords:||ranking; discrete choice experiment; preference-based measures; QALYs|
|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
|Depositing User:||Sarah McEvoy|
|Date Deposited:||29. Mar 2011 10:57|
|Last Modified:||16. Feb 2013 05:02|
Gold MR, Siegel JE, Russell LB, Weinstein MC (1996). Cost-effectiveness in health and medicine. Oxford: Oxford University Press.
NICE (National Institute for Health and Clinical Excellence) (2008). Guide to the methods of technology appraisal. NICE: London.
Drummond MF, Sculpher M, O’Brien B, et al (2005). Methods for the economic evaluation of health care programmes. Oxford: Oxford Medical Publications.
Dolan P. Modelling valuation for Euroqol health states (1997). Med Care 35:351-63.
Brazier J, Roberts J, Deverill M (2002). The estimation of a preference based single index measure for health from the SF-36. J Health Econ 21:271-92.
Feeny D, Furlong W, Torrance G, et al (2002). Multiattribute and single attribute utility functions for the Health Utilities Index Mark 3 system. Med Care 40:113-28.
Bleichrodt H (2002). A new explanation for the difference between time trade-off utilities and standard gamble utilities. Health Econ 11:447-56.
Kind P (1982). A comparison of two models for scaling health indicators. Int J Epidemiol 11:271–5.
Salomon JA (2003). Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data. Popul Health Metr 1:12.
McCabe C, Brazier J, Gilks P, et al (2006). Using rank data to estimate health state utility models. J Health Econ 25:418-31.
Burr JM, Kilonzo M, Vale L, et al (2007). Developing a preference-based glaucoma utility index using a discrete choice experiment. Optom Vis Sci 84:797-808.
Ratcliffe J, Brazier J, Tsuchiya A, et al (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 Econ, forthcoming.
Ryan M, Netten A, Skatun D, et al (2006). Using discrete choice experiments to estimate a preference-based measure of outcome – an application to social care for older people. J Health Econ 25:927-44.
Thurstone LL (1927). A law of comparative judgement. Psychol Rev 34:273-86.
Fanshel S, Bush JW (1970). A health status index and its application to health services outcomes. Operations Research 18:1021-66.
Kind P (2005). Applying paired comparisons models to EQ-5D valuations – deriving TTO utilities from ordinal preferences data. In: Kind P, Brooks R, Rabin R (eds), EQ-5D concepts and methods: a developmental history. Netherlands: Springer.
Luce RD (1959). Individual choice behavior: a theoretical analysis. New York: John Wiley & Sons, Inc..
McFadden D (1974). Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed), Frontiers in econometrics. New York; Academic Press.
Hakim Z, Pathak DS (1999). Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling. Health Econ 8:103-16.
Johnson R, Banzhaf M, Desvousges W (2000). Willingness to pay for improved respiratory and cardiovascular health: a multiple-format, stated preference approach. Health Econ 9:295–317.
Osman LM, McKenzie L, Cairns J, et al (2001). Patient weighting of importance of asthma symptoms. Thorax 56:138-42.
Young T, Yang Y, Brazier J, et al (2007). The use of Rasch analysis as a tool in the construction of a preference based measure: the case of AQLQ. Health Economics and Decision Science Discussion Paper 07/01. ScHARR, University of Sheffield. http://www.sheffield.ac.uk/scharr/sections/heds/discussion.html
Juniper EF, Guyatt GH, Ferrie PJ, et al (1993). Measuring quality of life in asthma. American Review of Respiratory Disease 147:832-8.
Young T, Yang Y, Brazier J, et al (2009). The first stage of developing preference-based measures: constructing a health-state classification using Rasch analysis. Qual Life Res 18:253-65.
Coyne K, Revicki D, Hunt T, et al (2002). Psychometric validation of an overactive bladder symptom and health related quality of life questionnaire: The OAB-q. Qual Life Res 11:563-74.
MVH Group (1995). The measurement and valuation of health: Final report on the modelling of valuation tariffs. Centre for Health Economics, University of York.
Huber J, Zwerina K (1996). The importance of utility balance in efficient choice designs. Journal of Marketing Research 33:307-17.
Yang Y, Tsuchiya A, Brazier J, et al (2007). Estimating a preference-based single index from the Asthma Quality of Life Questionnaire (AQLQ). Health Economics and Decision Science Discussion Paper 07/02. ScHARR, University of Sheffield. http://www.sheffield.ac.uk/scharr/sections/heds/discussion.html
Yang Y, Brazier JE, Tsuchiya A, et al (2009). Estimating a preference-based index from the Over-Active Bladder questionnaire. Value in Health 12:159-66.
Brazier J, Ratcliffe J, Salomon J, et al (2007). The measurement and valuation of health benefits for economic evaluation. Oxford: Oxford University Press.
Kind P, Harman G, Macran S (1999). UK population norms for EQ-5D. Centre for Health Economics Discussion Series, University of York.
Louviere JJ (2006). What you don't know might hurt you: some unresolved issues in the design and analysis of discrete choice experiments. Environmental and Resource Economics 34:173–88.
Train K (2003). Discrete choice methods with simulation. Cambridge: Cambridge University Press.