CRII: SCH: Visualization for Better Medical Decision-Making

CRII：SCH：可视化以实现更好的医疗决策

基本信息

批准号：
1755734
负责人：
Alvitta Ottley
金额：
$ 17.43万
依托单位：
Washington University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-06-15 至 2022-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1755734&HistoricalAwards=false
关键词：
CRII SCH Visualization Better Medical

项目摘要

This project develops visualization methods for communicating complex health risk data to patients. The project determines how the use of visual aids can impact decision-making and whether visual aids can cause, reinforce or mitigate biases. Additionally, the project identifies strategies people use when making medical decisions. Results of this work will have broad and varying impacts. The knowledge gained from this project will provide a better understanding of how people reason and make decisions with health statistics, and how we can improve or create novel designs for communicating such complex data beyond the medical field. The output of the project will be a database of tested visualization designs for supporting informed medical decision-making. Despite being fundamental components of evidence-based decision-making, medical statistics are notoriously unintuitive and arduous for people to understand. As a result, providing patient support for health decision-making has become a significant challenge for the medical community. This research addresses this problem by calling attention to synergies between medical risk communication and visualization theory. The project will create a theoretical framework for how visual representations impact decisions. The results will demonstrate how different designs can create, reinforce, or mitigate biases related to risk perception, and will identify individual characteristics that may mediate cognitive biases. Furthermore, the project will develop computational approaches for how people use visualization throughout the decision-making process and will determine which visual elements people tend to use or ignore. Using medical risk communication as a test bed, this research will investigate core topics in the Visualization community and simultaneously make contributions to the medical community. A core product of this project will be a web-based multi-dimensional recommendation system for health risk visualization. All publications, data, and source code will be publicly available.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目开发了可视化方法，以将复杂的健康风险数据传达给患者。该项目决定了视觉辅助工具的使用如何影响决策，以及视觉辅助工具是否会导致，增强或减轻偏见。此外，该项目确定了人们在做出医疗决策时使用的策略。这项工作的结果将产生广泛而不同的影响。从该项目中获得的知识将更好地了解人们如何推理和通过健康统计数据做出决策，以及我们如何改进或创建新颖的设计，以在医疗领域以外的情况下传达此类复杂数据。该项目的输出将是经过测试的可视化设计数据库，用于支持知情的医疗决策。尽管是基于证据的决策的基本组成部分，但众所周知，医疗统计数据对人们来说是不直觉和艰巨的。结果，为患者提供对健康决策的支持已成为医学界的重大挑战。这项研究通过呼吁关注医学风险通信与可视化理论之间的协同作用来解决这一问题。该项目将为视觉表示如何影响决策创建一个理论框架。结果将证明不同的设计如何创造，加强或减轻与风险感知相关的偏见，并确定可能介导认知偏见的个体特征。此外，该项目将开发用于人们如何在整个决策过程中使用可视化的计算方法，并确定人们倾向于使用或忽略哪些视觉元素。这项研究将使用医疗风险通信作为测试床，将研究可视化界的核心主题，并同时为医学界做出贡献。该项目的核心产品将是一种基于Web的多维建议系统，用于健康风险可视化。所有出版物，数据和源代码都将公开可用。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。