Deriving Time Discounting Correction Factors for TTO Tariffs

Abstract

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.

Correcting for discounting and loss aversion in composite time trade‐off

“…In line with our observation of no/little discounting on average, if we correct for loss aversion only, or discounting only (see Appendix ), we find that the downward trend observed when applying a corrective approach to cTTO utilities is exclusively driven by loss aversion (as in Lipman et al., 2019c). This finding is in contrast to earlier work using the direct method that has suggested that correcting for discounting would influence TTO utilities (Attema & Brouwer, 2014). Future work should aim to replicate our results, as considered in isolation they could suggest that, if only average utilities are of importance, correcting for discounting may not be necessary.…”

“…First, it is the first applying a corrective approach with interviewer‐assisted data collection with members of the general public. Some authors have explored correction for discounting in cTTO in the general public using online self‐completed data collection (Attema & Brouwer, 2014), but this mode of administration will generally lead to lower quality data and increased no‐shows (Norman et al., 2010). Furthermore, our results may be of larger practical relevance, as cTTO utilities were obtained following the EQ‐VT protocol.…”

“…This model assumes utility of life duration is linear, that is, future life years are not discounted. In practice, this assumption is violated for many individuals, who positively discount the future, which means they derive less utility from health in the future (Attema & Brouwer, 2014; Attema et al., 2012; Van Der Pol & Roux, 2005). On the other hand, negative discounting has been observed as well, that is, individuals assigning more weight to health in the future (e.g., Lipman & Attema, 2020; Van Der Pol & Cairns, 2000).…”

A comparison of individual and collective decision making for standard gamble and time trade-off

“…Taken together, these studies suggest that risk preferences, which are relevant for SG, and time preferences, which are relevant for TTO, might be affected by collective decision making. For example, discounting of future life years leads to downwards bias in TTO [22][23][24], and if such discounting is lower in when individuals decide in a group [11] this could lead to higher TTO weights. Similarly, if groups are more willing to take risks [13], perhaps due to reduced overweighting of small probabilities of dying, this could yield lower SG weights.…”