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QALYs without bias? Nonparametric correction of time trade-off and standard gamble weights based on prospect theory.

ABSTRACT: Common health state valuation methodologies, such as standard gamble (SG) and time trade-off (TTO), typically produce different weights for identical health states. We attempt to alleviate these differences by correcting the confounding influences modeled in prospect theory: loss aversion and probability weighting. Furthermore, we correct for nonlinear utility of life duration. In contrast to earlier attempts at correcting TTO and SG weights, we measure and correct all these tenets simultaneously, using newly developed nonparametric methodology. These corrections were applied to three less-than-perfect health states, measured with TTO and SG. We found considerable loss aversion and probability weighting for both gains and losses in life years, and we observe concave utility for gains and convex utility for losses in life years. After correction, the initially significant differences in weights between TTO and SG disappeared for all health states. Our findings suggest new opportunities to account for bias in health state valuations but also the need for further validation of resulting weights.

SUBMITTER: Lipman SA

PROVIDER: S-EPMC6618285 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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QALYs without bias? Nonparametric correction of time trade-off and standard gamble weights based on prospect theory.

Lipman Stefan A SA Lipman Stefan A SA Brouwer Werner B F WBF Attema Arthur E AE

Health economics 20190701 7

Common health state valuation methodologies, such as standard gamble (SG) and time trade-off (TTO), typically produce different weights for identical health states. We attempt to alleviate these differences by correcting the confounding influences modeled in prospect theory: loss aversion and probability weighting. Furthermore, we correct for nonlinear utility of life duration. In contrast to earlier attempts at correcting TTO and SG weights, we measure and correct all these tenets simultaneousl ...[more]

PMID: 31237093

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Project description:ObjectivesThe purpose of this research is to understand the thought processes that underpin responses to stated preference approaches for eliciting quality of life, in particular the standard gamble.MethodsWe utilize standard gamble preference elicitation survey techniques to elicit quality-adjusted life year weights for two reduced health states: chronic severe depression and total blindness. After the survey, we conduct open-ended qualitative interviews with respondents to determine their thought processes while taking the surveys and to shed light on what their quality-adjusted life year weight is capturing. Survey responses were coded and analyzed for themes in NVivo, the results of which were then formalized in the terminology of decision sciences.ResultsThe qualitative results of the cognitive interviews present systematic evidence for a type of cognitive bias present in standard gamble quality-adjusted life year weight elicitation, which has not been previously highlighted and which we call treatment bias. We define this treatment bias as the consideration of salient treatment alternatives correlated with a reduced health state, when these alternatives are not explicitly posed in the question. Our formalization of this cognitive behavior demonstrates that treatment bias will always bias the elicited health state utility of treating the illness in question downward.ConclusionThe treatment bias highlighted in this study has implications for economic evaluation when comparing treatment for illnesses where alternative treatments are widely publicized versus those that are not. For example, comparing the effectiveness of treating depression versus arthritis may be biased against depression if advertisements for anti-depressants are more widely viewed by survey respondents than advertisements for arthritis treatments. We propose a statement to be imbedded in all questionnaires regarding stated preference elicitation of quality-adjusted life year weights in order to correct for this bias in future stated preference surveys.

Project description:The present Table of Standard Atomic Weights (TSAW) of the elements is perhaps one of the most familiar data sets in science. Unlike most parameters in physical science whose values and uncertainties are evaluated using the "Guide to the Expression of Uncertainty in Measurement" (GUM), the majority of standard atomic-weight values and their uncertainties are consensus values, not GUM-evaluated values. The Commission on Isotopic Abundances and Atomic Weights of the International Union of Pure and Applied Chemistry (IUPAC) regularly evaluates the literature for new isotopic-abundance measurements that can lead to revised standard atomic-weight values, Ar °(E) for element E. The Commission strives to provide utmost clarity in products it disseminates, namely the TSAW and the Table of Isotopic Compositions of the Elements (TICE). In 2016, the Commission recognized that a guideline recommending the expression of uncertainty listed in parentheses following the standard atomic-weight value, for example, Ar °(Se) = 78.971(8), did not agree with the GUM, which suggests that this parenthetic notation be reserved to express standard uncertainty, not the expanded uncertainty used in the TSAW and TICE. In 2017, to eliminate this noncompliance with the GUM, a new format was adopted in which the uncertainty value is specified by the "±" symbol, for example, Ar °(Se) = 78.971 ± 0.008. To clarify the definition of uncertainty, a new footnote has been added to the TSAW. This footnote emphasizes that an atomic-weight uncertainty is a consensus (decisional) uncertainty. Not only has the Commission shielded users of the TSAW and TICE from unreliable measurements that appear in the literature as a result of unduly small uncertainties, but the aim of IUPAC has been fulfilled by which any scientist, taking any natural sample from commerce or research, can expect the sample atomic weight to lie within Ar °(E) ± its uncertainty almost all of the time.

Dataset Information

QALYs without bias? Nonparametric correction of time trade-off and standard gamble weights based on prospect theory.

Publications

QALYs without bias? Nonparametric correction of time trade-off and standard gamble weights based on prospect theory.

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