Preference Elicitation and Aggregation to Aid with Patient Triage during the COVID-19 Pandemic
Preference Elicitation and Aggregation to Aid with Patient Triage during the COVID-19 Pandemic
复制标题
偏好诱导和聚合有助于在 COVID-19 大流行期间进行患者分类
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
P. Vayanos
中科院分区：
文献类型：
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作者：
Caroline M Johnston;Simon Blessenohl;P. Vayanos
在 COVID-19 大流行期间，分类委员会必须做出道德上困难的决定，而利益相关者利益的多样性使这些决定变得复杂。我们提出了一种自动化方法来支持群体决策，通过向群体推荐一项政策，在潜在冲突的个人偏好之间达成妥协。为了确定最能汇总个人偏好的政策，我们的系统首先通过询问适量的战略选择查询来引发个人利益相关者的价值判断，每个查询都采取针对特定利益相关者的成对比较的形式。我们针对该问题提出了一种新颖的多阶段鲁棒优化公式，该公式选择最能告知下游推荐问题的查询。我们将其表述为混合整数线性程序，评估了我们的方法在为 COVID-19 患者分配重症监护床位的推荐政策问题上的性能。我们表明，与随机提问相比，明智地提出问题可以推荐一种后悔率明显较低的政策，这表明该系统可以通过提出与利益相关者价值判断相一致的政策来帮助委员会做出更好的决策。
During the COVID-19 pandemic, triage commit-tees must make ethically difficult decisions which are complicated by the diversity of stakeholder interests. We propose an automated approach to support group decisions by recommending a policy to the group that strikes a compromise between potentially conflicting individual preferences. To identify a policy that best aggregates individual preferences, our system first elicits individual stakeholder value judgements by asking a moderate number of strategically selected queries, each taking the form of a pairwise comparison posed to a specific stakeholder. We propose a novel multi-stage robust optimization formulation of this problem that selects queries that best inform the downstream recommendation problem. For-mulating this as a mixed-integer linear program, we evaluate the performance of our approach on the problem of recommending policies for allocating critical care beds to patients with COVID-19. We show that asking questions intelligently allows recommending a policy with significantly lower regret than asking questions randomly, suggesting that the system can help committees reach a better decision by suggesting a policy that aligns with stakeholder value judgments.
DOI：
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发表时间：
2016
期刊：
Uncertainty in artificial intelligence
影响因子：
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作者：
Zhao, Zhibing;Li, Haoming;Wang, Junming;Kephart, Jeffrey O.;Mattei, Nicholas;Su, Hui;Xia, Lirong
通讯作者：
Xia, Lirong