Table 2.
Arguments Identified by the Literature Review or the Books and PhD Theses Review
| Argument | Source |
|---|---|
| Dead and good health are anchored at 0 and 1 by definition or for convenience. | Found in multiple studies (Refs.6,10,12) and is common in the literature |
| “To estimate utility values for each health state defined by a classification system, the results of the TTO study are modelled using multivariate regression. The disutility coefficient for each severity level of each dimension is calculated using level 1 (no problem) as the baseline. Therefore, full health is anchored at 1, and the utility value for each overall health state is calculated by subtracting the disutility value for each dimension from 1.”13 (It is convenient to assign perfect health the value 1, because it makes the calculation of utility values based on TTO results easier. When using multivariate regression, disutility is simply subtracted from full health for each dimension of health.—BR)a | Mulhern et al. (2014) |
| “We set H(FH)=1 and U(death)=0, which is allowed by the uniqueness properties of U.”14 (Here, U denotes the QALY model and H(FH) denotes the value of full health on the health–utility scale.—BR) | Bleichrodt et al. (2002) |
| “If the preference weights do not produce utility values on the full health-dead scale they cannot be used in economic evaluation using cost per QALY analysis.”15 | Brazier et al. (2012) |
| The anchoring of DCE data on the 0–1 dead–full health scale is problematic. Four different methods are tested, and all provide varying amounts of health states considered WTD.9 | Norman et al. (2016) |
| Using dead as a health state in DCE is problematic, because this might lead to a violation of the random utility model that is used to assign values to health states.16 | Flynn et al. (2008) |
| For single-attribute health measures, a 0 (dead) to 1 (best health imaginable) scale is preferable, because it corresponds to the utilities and probabilities of basic reference lotteries (like SG). This is extended to multiattribute health measures such as the QALY.17 | Weinstein and Fineberg (1980) (book) |
| “In the measurement of such attributes as attitudes, esthetics, preferences, and value, the natural origin occurs within the series and can be described as a neutral point such that all stimuli or individuals in one direction are favourable, pleasant, liked, or wanted as the case may be, whereas all those on the other side are unfavourable, unpleasant, disliked or not wanted.”18 (Dead could function as such a neutral zero point that divides all health states between desirable and undesirable.—BR) | Torgerson (1958) (book) |
| Using 0 (dead) and 1 (perfect health) as anchors makes QALYs comparable to survival analyses. “Partly by convention but principally as a consequence of the data requirements of the analytic methods used, for example in the quality adjustment of survival, the unit interval of health is defined in terms of the distance between full health and death, valued as 1 and 0, respectively.”19 | Macran and Kind (2001)b |
| The zero-condition papers by Miyamoto et al.1 and Bleichrodt et al.20 make no explicit assumption that dead should have a value of 0, merely stating that individuals are indifferent between health states if the duration of such a health episode is 0. | Miyamoto et al. (1998) and Bleichrodt et al. (1997)b |
a
Author comments for clarification are reported in italics.
b
Arguments that were not identified by the literature review but were identified by the authors as other relevant papers.