Med Decis Making - The lead time tradeoff: the case of health states better than dead.

Tópicos

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{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
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{ framework(1458) process(801) describ(734) }
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Resumo

CKGROUND: Lead time tradeoff (L-TTO) is a variant of the time tradeoff (TTO). L-TTO introduces a lead period in full health before illness onset, avoiding the need to use 2 different procedures for states better and worse than dead. To estimate utilities, additive separability is assumed. We tested to what extent violations of this assumption can bias utilities estimated with L-TTO.METHODS: A sample of 500 members of the Spanish general population evaluated 24 health states, using face-to-face interviews. A total of 188 subjects were interviewed with L-TTO and the rest with TTO. Both samples evaluated the same set of 24 health states, divided into 4 groups with 6 health states per set. Each subject evaluated 1 of the sets. A random effects regression model was fitted to our data. Only health states better than dead were included in the regression since it is in this subset where additive separability can be tested clearly.RESULTS: Utilities were higher in L-TTO in relation to TTO (on average L-TTO adds about 0.2 points to the utility of health states), suggesting that additive separability is violated. The difference between methods increased with the severity of the health state. Thus, L-TTO adds about 0.14 points to the average utility of the less severe states, 0.23 to the intermediate states, and 0.28 points to the more severe estates.CONCLUSIONS: L-TTO produced higher utilities than TTO. Health problems are perceived as less severe if a lead period in full health is added upfront, implying that there are interactions between disjointed time periods. The advantages of this method have to be compared with the cost of modeling the interaction between periods.

Resumo Limpo

ckground lead time tradeoff ltto variant time tradeoff tto ltto introduc lead period full health ill onset avoid need use differ procedur state better wors dead estim util addit separ assum test extent violat assumpt can bias util estim lttomethod sampl member spanish general popul evalu health state use facetofac interview total subject interview ltto rest tto sampl evalu set health state divid group health state per set subject evalu set random effect regress model fit data health state better dead includ regress sinc subset addit separ can test clearlyresult util higher ltto relat tto averag ltto add point util health state suggest addit separ violat differ method increas sever health state thus ltto add point averag util less sever state intermedi state point sever estatesconclus ltto produc higher util tto health problem perceiv less sever lead period full health ad upfront impli interact disjoint time period advantag method compar cost model interact period

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