Ara, R and Brazier, JE (2010): Using health state utility values from the general population to approximate baselines in decision analytic models when condition specific data are not available.
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Decision analytic models in healthcare require baseline health related quality of life (HRQoL) data to accurately assess the benefits of interventions. The use of inappropriate baselines such as assuming the value of perfect health (EQ-5D = 1) for not having a condition may overestimate the benefits of some treatment and thus distort policy decisions informed by cost per QALY thresholds.
The primary objective was to determine if data from the general population are appropriate for baseline health state utility values (HSUVs) when condition-specific data are not available.
Methods: Data from four consecutive Health Surveys for England were pooled. Self-reported health status and EQ-5D data were extracted and used to generate mean HSUVs for cohorts with or without prevalent health conditions. These were compared with mean HSUVs from all respondents irrespective of health status.
Results: Over 45% of respondents (n=41,174) reported at least one health condition and almost 20% reported at least two. Our results suggest that data from the general population could be used to approximate baseline HSUVs in some analyses but not all. In particular, HSUVs from the general population would not be an appropriate baseline for cohorts who have just one health condition. In these instances, if condition-specific data are not available, data from respondents who report they do not have a prevalent health condition may be more appropriate. Exploratory analyses suggest the decrement on HRQoL may not be constant across ages for all conditions and these relationships may be condition-specific. Additional research is required to validate our findings.
|Item Type:||MPRA Paper|
|Original Title:||Using health state utility values from the general population to approximate baselines in decision analytic models when condition specific data are not available|
|Keywords:||health state utility values; baseline; quality of life; EQ-5D; age-adjusted|
|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 19:05|
|Last Modified:||16. Mar 2015 08:00|
Brazier J (2007). Briefing paper for methods review workshop on key issues in utility measurement. NICE. Available from: www.nice.org.uk/TAMethodsReview.
Fryback DG, Lawrence WF (1997). Dollars may not buy as many QALYs as we think: A problem with defining quality of life adjustments. Med Decis Making 17:276.
Murray CWS, Brazier JE (2002). Utility following a fracture in a group of elderly women. Qual Life Res 11:642.
Manuel DG, Schultz SE, Kopec JA (2002). Measuring the health burden of chronic disease and injury using health adjusted life expectancy and the Health Utilities Index. J Epidemiol Community Health 56:843-50.
Ara R, Brazier J (2010). Populating an economic model with health state utility values: moving toward better practice. HEDS Discussion Paper No 09/11. Available at http://www.sheffield.ac.uk/scharr/sections/heds/dps-2009.html
Joint Health Surveys Unit of Social and Community Planning Research and University College London, Health Survey for England 200x [computer file] (3rd ed.). Colchester, Essex: UK Data Archive, [distributor], 2008.
Dolan P, Gudex C, Kind P, Williams A (1996). The time trade-off method: results from a general population study. Health Econ 5:141-54.
Walters SJ, Brazier JE (2005). Comparison of the minimally important difference for two health state utility measures: EQ-5D SF-6D. Qual Life Res 14:1423-32.
Julious SA (2004). Using confidence intervals around individual means to assess statistical significance between two means. Pharmaceut Statist 3:217-22.
Fu AZ, Kattan MW (2008). Utilities should not be multiplied: evidence from the preference-based scores in the United States. Medical Care 46(9):984-90.
Fryback DG, Dunham NC, Palta M, Hanmer J, Buechner J, Cherepanov D, Herrington S (2007). US norms for six generic health-related quality of life indexes from the national health measurement study. Med Care 45(12):1162-70.
Hanmer J, Lawrence WF, Anderson JP, Kaplan RM, Fryback DG (2006). Report of nationally representative values for the noninstitutionalized US adult population for 7 health-related quality-of-life scores. Med Decis Making 26:391-400.