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卫生技术评估中两种专家意见征集方法的比较。

A comparison of two methods for expert elicitation in health technology assessments.

作者信息

Grigore Bogdan, Peters Jaime, Hyde Christopher, Stein Ken

机构信息

Evidence Synthesis & Modelling for Health Improvement (ESMI), Institute for Health Research, University of Exeter Medical School, University of Exeter, Room 3.09.3, St Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK.

出版信息

BMC Med Res Methodol. 2016 Jul 26;16:85. doi: 10.1186/s12874-016-0186-3.

Abstract

BACKGROUND

When data needed to inform parameters in decision models are lacking, formal elicitation of expert judgement can be used to characterise parameter uncertainty. Although numerous methods for eliciting expert opinion as probability distributions exist, there is little research to suggest whether one method is more useful than any other method. This study had three objectives: (i) to obtain subjective probability distributions characterising parameter uncertainty in the context of a health technology assessment; (ii) to compare two elicitation methods by eliciting the same parameters in different ways; (iii) to collect subjective preferences of the experts for the different elicitation methods used.

METHODS

Twenty-seven clinical experts were invited to participate in an elicitation exercise to inform a published model-based cost-effectiveness analysis of alternative treatments for prostate cancer. Participants were individually asked to express their judgements as probability distributions using two different methods - the histogram and hybrid elicitation methods - presented in a random order. Individual distributions were mathematically aggregated across experts with and without weighting. The resulting combined distributions were used in the probabilistic analysis of the decision model and mean incremental cost-effectiveness ratios and the expected values of perfect information (EVPI) were calculated for each method, and compared with the original cost-effectiveness analysis. Scores on the ease of use of the two methods and the extent to which the probability distributions obtained from each method accurately reflected the expert's opinion were also recorded.

RESULTS

Six experts completed the task. Mean ICERs from the probabilistic analysis ranged between £162,600-£175,500 per quality-adjusted life year (QALY) depending on the elicitation and weighting methods used. Compared to having no information, use of expert opinion decreased decision uncertainty: the EVPI value at the £30,000 per QALY threshold decreased by 74-86 % from the original cost-effectiveness analysis. Experts indicated that the histogram method was easier to use, but attributed a perception of more accuracy to the hybrid method.

CONCLUSIONS

Inclusion of expert elicitation can decrease decision uncertainty. Here, choice of method did not affect the overall cost-effectiveness conclusions, but researchers intending to use expert elicitation need to be aware of the impact different methods could have.

摘要

背景

当决策模型中参数所需的数据缺失时,可以采用正式的专家判断引出法来描述参数的不确定性。尽管存在许多将专家意见引出为概率分布的方法,但很少有研究表明一种方法是否比其他方法更有用。本研究有三个目标:(i)在卫生技术评估的背景下获得表征参数不确定性的主观概率分布;(ii)通过以不同方式引出相同参数来比较两种引出方法;(iii)收集专家对所使用的不同引出方法的主观偏好。

方法

邀请了27位临床专家参与一项引出练习,以支持已发表的基于模型的前列腺癌替代治疗成本效益分析。要求参与者使用两种不同的方法——直方图法和混合引出法——以随机顺序将他们的判断表示为概率分布。在有加权和无加权的情况下,对专家的个体分布进行数学汇总。将得到的组合分布用于决策模型的概率分析,并计算每种方法的平均增量成本效益比和完美信息期望值(EVPI),并与原始成本效益分析进行比较。还记录了两种方法在易用性方面的得分以及从每种方法获得的概率分布准确反映专家意见的程度。

结果

六位专家完成了任务。根据所使用的引出和加权方法,概率分析得出的平均增量成本效益比为每质量调整生命年(QALY)162,600-175,500英镑。与没有信息相比,使用专家意见降低了决策不确定性:在每QALY 30,000英镑的阈值下,EVPI值比原始成本效益分析降低了74-86%。专家表示直方图法更易于使用,但认为混合法更准确。

结论

纳入专家引出法可以降低决策不确定性。在此,方法的选择并未影响总体成本效益结论,但打算使用专家引出法的研究人员需要意识到不同方法可能产生的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d178/4960697/fd221e535361/12874_2016_186_Fig1_HTML.jpg

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