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Pharmacoeconomics ; 41(10): 1165-1174, 2023 10.
Article in English | MEDLINE | ID: mdl-37439998

ABSTRACT

Value sets for the EQ-5D-Y-3L published to date appear to have distinctive characteristics compared with value sets for corresponding adult instruments: in many cases, the value for the worst health state is higher and there are fewer values < 0. The aim of this paper is to consider how and why values for child and adult health differ; and what the implications of that are for the use of EQ-5D-Y-3L values in economic evaluations to inform healthcare resource allocation decisions. We posit four potential explanations for the differences in values: (a) The wording of severity labels may mean the worst problems on the EQ-5D-Y-3L are descriptively less severe than those on the EQ-5D-5L; (b) Adults may genuinely consider that children are less badly affected than adults by descriptively similar health issues. That is, for any given health problem, adult respondents in valuation studies consider children's overall health-related quality of life (HRQoL) on average to be higher than that for adults; (c) Values are being sought by eliciting adults' stated preferences for HRQoL in another person, rather than in themselves (regardless of whether the 'other person' concerned is a child); and (d) The need to elicit preferences for child HRQoL that are anchored at dead = 0 invokes special considerations regarding children's survival. Existing evidence does not rule out the possibility that (c) and (d) exert an upward bias in values. We consider the implications of that for the interpretation and use of values for pediatric HRQoL. Alternative methods for valuing children's HRQoL in a manner that is not 'age specific' are possible and may help to avoid issues of non-comparability. Use of these methods would place the onus on health technology assessment bodies to reflect any special considerations regarding child quality-adjusted life-year gains.


Subject(s)
Health Status , Quality of Life , Adult , Humans , Child , Cost-Benefit Analysis , Surveys and Questionnaires , Age Factors
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