使证据可操作:交互式仪表板、贝叶斯和医疗保健创新

Anupa Bir, Nikki L. B. Freeman, Robert F. Chew, Kevin W. Smith, James H Derzon, T. Day
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引用次数: 1

摘要

许多大规模的联邦或多地点评估的结果通常被汇编成长篇报告,最终被决策者搁置在书架上。此外,决策者从这些报告中需要的信息往往隐藏在报告中,可能不被记住、理解,或者在需要时不容易被决策者获取。这对评估人员来说并不是一个新挑战,统计方法的进步虽然创造了更多的洞察机会,但可能会创造多种视角来看待证据,从而使挑战复杂化。来自传统频率论模型的描述性证据虽然熟悉,但经常被误解,而较新的贝叶斯方法提供了直观的证据,但不太熟悉。这些方法是互补的,但同时提出这两种方法会增加利益攸关方和决策者可能认为有用的证据数量。为了应对这些挑战,我们开发了一个交互式仪表板,它综合了定量和定性数据,并允许用户在需要时访问他们想要的证据,允许每个用户对为大规模联邦评估收集的数据进行定制和可定制的视图。这为政策制定者提供了一个机会,可以在任何时候选择与他们最相关的具体细节,并将自己的风险承受能力应用于各种结果的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Making Evidence Actionable: Interactive Dashboards, Bayes, and Health Care Innovation
The results of many large-scale federal or multi-site evaluations are typically compiled into long reports which end up sitting on policymaker’s shelves. Moreover, the information policymakers need from these reports is often buried in the report, may not be remembered, understood, or readily accessible to the policymaker when it is needed. This is not a new challenge for evaluators, and advances in statistical methodology, while they have created greater opportunities for insight, may compound the challenge by creating multiple lenses through which evidence can be viewed. The descriptive evidence from traditional frequentist models, while familiar, are frequently misunderstood, while newer Bayesian methods provide evidence which is intuitive, but less familiar. These methods are complementary but presenting both increases the amount of evidence stakeholders and policymakers may find useful. In response to these challenges, we developed an interactive dashboard that synthesizes quantitative and qualitative data and allows users to access the evidence they want, when they want it, allowing each user a customized, and customizable view into the data collected for one large-scale federal evaluation. This offers the opportunity for policymakers to select the specifics that are most relevant to them at any moment, and also apply their own risk tolerance to the probabilities of various outcomes.
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