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基于数据驱动理解物质使用障碍流行情况的可视化分析

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic.

作者信息

Qaurooni Danial, Herr Bruce W, Zappone Sarah Renee, Wojciechowska Klaudia, Börner Katy, Schleyer Titus

机构信息

Indiana University Bloomington, Bloomington, IN, USA.

Indiana University School of Medicine, Indianapolis, IN, USA.

出版信息

Inquiry. 2024 Jan-Dec;61:469580241227020. doi: 10.1177/00469580241227020.

Abstract

The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard's usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard's use cases and limitations.

摘要

物质使用障碍流行已成为一场严重的公共卫生危机,带来了复杂的挑战。可视化分析提供了一种独特的方法来应对这种复杂性并促进有效的干预措施。本文详细介绍了一个创新的可视化分析仪表板的开发,旨在增进我们对物质使用障碍流行情况的了解。通过采用记录链接技术,我们整合了各种数据源,以提供该流行病的全面视图。坚持响应式、开放式和以用户为中心的设计原则确保了仪表板的实用性和易用性。我们的数据和设计方法鼓励包括研究人员、政治家和医疗从业者在内的各种利益相关者之间的合作。通过示例输出,我们展示了仪表板如何能够加深我们对该流行病的理解、支持干预策略并评估已实施措施的有效性。本文最后讨论了仪表板的用例和局限性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/96e3/10823843/5cbbb0db82e3/10.1177_00469580241227020-fig1.jpg

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