Wittenberg Eve, Bray Jeremy W, Gebremariam Achamyeleh, Aden Brandon, Nosyk Bohdan, Schackman Bruce R
Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Department of Economics, University of North Carolina at Greensboro, Greensboro, NC, USA.
Value Health. 2017 Mar;20(3):458-465. doi: 10.1016/j.jval.2016.09.2404. Epub 2016 Nov 17.
Although co-occurring conditions are common with substance use disorders (SUDs), estimation methods for joint health state utilities have not yet been tested in this context.
To compare joint health state utility estimators in SUD to inform economic evaluation.
We conducted two Internet-based surveys of US adults to collect community perspective standard gamble utilities for SUD and common co-occurring conditions. We evaluated six conditions as they occur individually and four combinations of these as they occur in tandem. We applied joint utility estimators using the six individual conditions' utilities to compare their performance relative to the observed combination states' utilities. We assessed performance with bias (estimated utility minus observed utility) and root mean square error (RMSE).
Using 3892 utilities from 1502 respondents, the minimum estimator was statistically unbiased (i.e., the 95% confidence interval included 0) for all combination states that we measured. The maximum estimator was unbiased for two states and the linear index and adjusted decrement estimators were unbiased for one state. The maximum estimator had the smallest RMSE for two combination states (back pain and prescription opioid misuse [0.0004] and injection crack and injection opioid use [0.0007]); the linear index and minimum estimators had the smallest RMSE for one combination state each. The additive and multiplicative estimators had the largest RMSE for all states.
Our results demonstrate the usefulness of the minimum estimator in this context, and confirm the inadequacy of the additive and multiplicative estimators. Further research is needed to extend these results to other SUD states.
尽管共病情况在物质使用障碍（SUDs）中很常见，但联合健康状态效用的估计方法尚未在此背景下进行测试。
比较物质使用障碍中联合健康状态效用估计器，以为经济评估提供信息。
我们对美国成年人进行了两项基于互联网的调查，以收集关于物质使用障碍和常见共病情况的社区视角标准博弈效用。我们评估了六种单独出现的情况以及四种同时出现的这些情况的组合。我们使用六种单独情况的效用应用联合效用估计器，以比较它们相对于观察到的组合状态效用的性能。我们用偏差（估计效用减去观察到的效用）和均方根误差（RMSE）评估性能。
使用来自1502名受访者的3892个效用数据，对于我们测量的所有组合状态，最小估计器在统计学上无偏差（即95%置信区间包含0）。最大估计器对两种状态无偏差，线性指数和调整减量估计器对一种状态无偏差。对于两种组合状态（背痛和处方阿片类药物滥用[0.0004]以及注射快克和注射阿片类药物使用[0.0007]），最大估计器的RMSE最小；线性指数和最小估计器分别对一种组合状态的RMSE最小。加法和乘法估计器在所有状态下的RMSE最大。
我们的结果证明了最小估计器在此背景下的有用性，并证实了加法和乘法估计器的不足。需要进一步研究将这些结果扩展到其他物质使用障碍状态。
