Rescaling Quality of Life Values for QALYs
Author Information
Author(s): Terry N. Flynn, Jordan J. Louviere, Anthony AJ Marley, Joanna Coast, Tim J. Peters
Primary Institution: University of Bristol
Hypothesis
Can ordinal tasks like discrete choice experiments accurately estimate QALY health state values?
Conclusion
Using statistical models to anchor quality of life values to death is inappropriate when respondents do not conform to conventional random utility theory.
Supporting Evidence
- Only 26% of respondents conformed to conventional random utility theory.
- At least 14% of respondents violated the assumptions of the theory.
- Varying the proportions of conforming respondents led to significant changes in estimated QALY values.
Takeaway
This study shows that some people think all life is worth living, which makes it hard to measure how bad a state is compared to death.
Methodology
Data from the ICECAP valuation exercise were analyzed using an ordinal model and bootstrapping to estimate QALY-like values.
Potential Biases
The model may not accurately reflect the preferences of individuals who consider all life worth living.
Limitations
The true proportion of people unwilling to consider any ICECAP state to be worse than death was unknown.
Participant Demographics
Participants were aged 65 and over, sampled from the Health Survey for England.
Digital Object Identifier (DOI)
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