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评估死亡对离散选择实验效用的直接影响。

Assessing the Direct Impact of Death on Discrete Choice Experiment Utilities.

作者信息

Ameri Hossein, Poder Thomas G

机构信息

Département de gestion, évaluation et politique de santé, School of Public Health, University of Montreal, Montreal, QC, Canada.

CR-IUSMM, CIUSSS de l'Est de l'Île de Montréal, 7101 Parc Avenue, Montreal, QC, H3N 1X9, Canada.

出版信息

Appl Health Econ Health Policy. 2025 Mar;23(2):319-327. doi: 10.1007/s40258-024-00929-6. Epub 2024 Dec 6.

Abstract

BACKGROUND

The dead state can affect the value sets derived from discrete choice experiments (DCEs). Our aim was to empirically assess the direct impact of the immediate death state on health utilities using discrete choice experiment with time (DCE).

METHODS

A sample of the general population in Quebec, Canada, completed two approaches: DCE followed by a best-worst scaling with time (BWS) (hereafter referred to as DCE), versus DCE followed by the dominated option and the immediate death state (hereafter referred to as DCE), both designed with the SF-6Dv2. In DCE, all participants first completed 10 DCE choices (i.e., option A vs B), followed by 3 BWS. In DCE, the same participants first completed the same 10 DCE choices, followed by a repeated choice between the dominated option (i.e., A or B) and the immediate death state. A conditional logit model was used to estimate value sets. The performance of models was assessed using goodness of fit using Bayesian information criterion, parameters' logical consistency, and levels' significance. The direct impact of the death state on DCE latent utilities was evaluated by examining the magnitude of coefficients, assessing the agreement among the value sets estimated by DCE with DCE and with DCE using Bland-Altman plots, the proportion of worst-than-dead (WTD) health states, and analyzing the range of estimated values.

RESULTS

From 398 participants, a total of 348 participants were included for final analysis. The number of parameters with illogical consistency and non-significant coefficients was lower in DCE. The observed consistency in the relative importance of dimensions across all approaches suggests a stable and reliable ranking. The utility range for DCE (- 0.921 to 1) was narrower than for DCE (- 1.578 to 1) and DCE (- 1.150 to 1). The DCE estimated a lower percentage of WTD health states (20.01 %) compared to DCE (47.19 %) and DCE (33.73 %). The agreement between DCE and DCE was slightly stronger than between DCE and DCE, and the mean utility values were higher in DCE than in DCE.

CONCLUSIONS

The inclusion of the immediate death state directly within DCE increased utility values. This increase was higher when the immediate death was included in a sequence within a DCE (i.e., DCE) than when it was included in a continuum of DCE (i.e., DCE). The use of DCE was potentially better suited to incorporate the dead state into a DCE.

摘要

背景

死亡状态会影响离散选择实验(DCE)得出的价值集。我们的目的是通过带时间的离散选择实验(DCE),实证评估即时死亡状态对健康效用的直接影响。

方法

加拿大魁北克省的一般人群样本完成了两种方法:先进行DCE,然后进行带时间的最佳-最差标度法(BWS)(以下简称DCE),以及先进行DCE,然后进行占优选项和即时死亡状态(以下简称DCE),两者均采用SF-6Dv2设计。在DCE中,所有参与者首先完成10个DCE选择(即选项A对B),然后进行3次BWS。在DCE中,相同的参与者首先完成相同的10个DCE选择,然后在占优选项(即A或B)和即时死亡状态之间进行重复选择。使用条件logit模型估计价值集。使用贝叶斯信息准则通过拟合优度、参数的逻辑一致性和水平的显著性来评估模型的性能。通过检查系数的大小、使用布兰德-奥特曼图评估DCE与DCE和DCE估计的价值集之间的一致性、比死亡更差(WTD)健康状态的比例以及分析估计值的范围,来评估死亡状态对DCE潜在效用的直接影响。

结果

在398名参与者中,共有348名参与者纳入最终分析。DCE中逻辑一致性不合理和系数不显著的参数数量较少。在所有方法中观察到的维度相对重要性的一致性表明了一种稳定且可靠的排序。DCE的效用范围(-0.921至1)比DCE(-1.578至1)和DCE(-1.150至1)更窄。与DCE(47.19%)和DCE(33.73%)相比,DCE估计的WTD健康状态百分比更低(20.01%)。DCE与DCE之间的一致性略强于DCE与DCE之间的一致性,且DCE中的平均效用值高于DCE。

结论

在DCE中直接纳入即时死亡状态会增加效用值。当即时死亡包含在DCE的序列中(即DCE)时,这种增加比包含在DCE的连续统中(即DCE)时更高。使用DCE可能更适合将死亡状态纳入DCE。

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