Implications of an economic model of health states worse than dead

Sharma, Rajiv; Stano, Miron

doi:10.1016/j.jhealeco.2010.05.005

Cited by 5 publications

(3 citation statements)

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“…MET causes health states to be considered BTD for short durations but WTD when lasting longer, for example, the 10 years used in the typical TTO task Stalmeier et al, 2005). Stalmeier et al (2005) and Sharma and Stano (2010) illustrated that this reasoning implies that TTO valuations derived in conventional TTO tasks do not reflect the fact the some health states may have a small positive utility for a short duration but subsequently a negative utility. This may lead to a 'gap effect' in TTO exercises (a larger difference between the best WTD health state and the worst BTD health state than between all other adjacent health states).…”

Section: Discussionmentioning

confidence: 99%

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Deriving Time Discounting Correction Factors for Tto Tariffs

Attema

Brouwer

2013

Health Economics

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ABSTRACT. The Time Tradeoff (TTO) method is a popular method for valuing health state utilities and is frequently used in economic evaluations. However, this method produces utilities that are distorted by several biases. One important bias entails the failure to incorporate time discounting. This paper aims to measure time discounting for health outcomes in a sample representative for the general population. In particular, we estimate TTO scores alongside time discounting in order to derive a set of correction factors that can be employed to correct raw TTO scores for the downward bias caused by time discounting. We find substantial positive correction factors, which are increasing with the severity of the health state. Furthermore, higher discounting is found when using more severe health states in the discounting elicitation task. More research is needed to further develop discount rate elicitation procedures and test their validity, especially in general public samples. Moreover, future research should investigate the correction of TTO score for other biases as well, such as loss aversion, and to develop a criterion to test the external validity of TTO scores.

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Section: Discussionmentioning

confidence: 99%

“…In sum, although the VAS task may be especially ill suited to elicit preferences for WTD states, the TTO task may produce biased results for MET health states. Sharma and Stano () in that context called for richer preference elicitation methods that incorporate more dimensions than the health state alone.…”

Section: Discussionmentioning

confidence: 99%

Deriving Time Discounting Correction Factors for Tto Tariffs

Attema

Brouwer

2013

Health Economics

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“…Evidence shows that preferences for 'dead' are dominated by factors other than the value of health (Sharma & Stano, 2010); that when completing valuation tasks people are not always aware of what 'dead' implies or the meaning of WTD states (Al Sayah et al, 2016); that the framing of 'dead' influences valuations (Jakubczyk et al, 2023); and that negative values are not associated with the states' severity (Roudijk et al, 2022). 1 Including 'dead' in valuation studies produces many excluded observations.…”

Section: Problems With Using 'Dead'mentioning

confidence: 99%

Is anchoring at ‘dead’ a theoretical requirement for health state valuation?

Sampson,

Parkin,

Devlin

2024

Health Economics

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Values that accompany generic health measures are typically anchored at 1 = full health and 0 = dead. Some health states may then be considered ‘worse than dead’ (WTD) and assigned negative values, which causes fundamental measurement problems. In this paper, we challenge the assumption that anchoring values at ‘dead = 0’ is necessary for quality‐adjusted life year (QALY) estimation. We summarise the role of ‘dead’ in health state valuation and consider three critical questions: (i) whether the measurement properties of health state values require ‘dead’; (ii) whether ‘dead’ needs to be valued relative to health states; and (iii) whether values for states WTD are meaningful or useful. We conclude that anchoring 0 at dead is not a requirement of health status measurement or cost‐effectiveness analysis. This results from reframing QALYs as the relevant unit of measurement and reframing values as being derived from QALYs rather than the reverse.

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