Med Decis Making - A framework for estimating health state utility values within a discrete choice experiment: modeling risky choices.

Tópicos

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Resumo

CKGROUND: There has been recent interest in using the discrete choice experiment (DCE) method to derive health state utilities for use in quality-adjusted life year (QALY) calculations, but challenges remain.OBJECTIVES: We set out to develop a risk-based DCE approach to derive utility values for health states that allowed 1) utility values to be anchored directly to normal health and death and 2) worse than dead health states to be assessed in the same manner as better than dead states. Furthermore, we set out to estimate alternative models of risky choice within a DCE model.METHOD: A survey was designed that incorporated a risk-based DCE and a "modified" standard gamble (SG). Health state utility values were elicited for 3 EQ-5D health states assuming "standard" expected utility (EU) preferences. The DCE model was then generalized to allow for rank-dependent expected utility (RDU) preferences, thereby allowing for probability weighting. A convenience sample of 60 students was recruited and data collected in small groups.RESULTS: Under the assumption of "standard" EU preferences, the utility values derived within the DCE corresponded fairly closely to the mean results from the modified SG. Under the assumption of RDU preferences, the utility values estimated are somewhat lower than under the assumption of standard EU, suggesting that the latter may be biased upward.CONCLUSION: Applying the correct model of risky choice is important whether a modified SG or a risk-based DCE is deployed. It is, however, possible to estimate a probability weighting function within a DCE and estimate "unbiased" utility values directly, which is not possible within a modified SG. We conclude by setting out the relative strengths and weaknesses of the 2 approaches in this context.

Resumo Limpo

ckground recent interest use discret choic experi dce method deriv health state util use qualityadjust life year qali calcul challeng remainobject set develop riskbas dce approach deriv util valu health state allow util valu anchor direct normal health death wors dead health state assess manner better dead state furthermor set estim altern model riski choic within dce modelmethod survey design incorpor riskbas dce modifi standard gambl sg health state util valu elicit eqd health state assum standard expect util eu prefer dce model general allow rankdepend expect util rdu prefer therebi allow probabl weight conveni sampl student recruit data collect small groupsresult assumpt standard eu prefer util valu deriv within dce correspond fair close mean result modifi sg assumpt rdu prefer util valu estim somewhat lower assumpt standard eu suggest latter may bias upwardconclus appli correct model riski choic import whether modifi sg riskbas dce deploy howev possibl estim probabl weight function within dce estim unbias util valu direct possibl within modifi sg conclud set relat strength weak approach context

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