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设计用于传达健康数据的视觉层级结构。

Designing visual hierarchies for the communication of health data.

机构信息

National Center for Supercomputing Applications, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States.

Biomedical and Translational Sciences, Carle Illinois College of Medicine, University of Illinois Urbana-Champaign, Urbana, IL 61801, United States.

出版信息

J Am Med Inform Assoc. 2024 Nov 1;31(11):2722-2729. doi: 10.1093/jamia/ocae175.

Abstract

OBJECTIVES

Visual hierarchy underlies all visual design decisions related to information presentation. This manuscript describes the experience of a multidisciplinary health data visualization and software design team in using visual hierarchy to redesign a hereditary colorectal cancer lab report.

MATERIALS AND METHODS

A series of interviews with representative users were conducted to identify target user groups and determine information hierarchy for each user type. Visual elements (eg, size, color, contrast, etc.) were then assigned to mirror the information hierarchy and workflow for each user type.

RESULTS

User research identified 2 distinct user groups as consumers of the redesigned lab report. An interactive design employing a 2-level page hierarchy was developed, which stratified the content to support the needs of each user type.

CONCLUSIONS

The challenges related to displaying the complex nature of digital and personal health data can be addressed by applying foundational design methods such as visual hierarchy.

DISCUSSION

Visual hierarchy, a foundational design principle, can be used by visualization teams to clearly and efficiently present complex datasets associated with healthcare.

摘要

目的

视觉层级结构是所有与信息呈现相关的视觉设计决策的基础。本文档描述了一个多学科健康数据可视化和软件设计团队在使用视觉层级结构重新设计遗传性结直肠癌实验室报告方面的经验。

材料与方法

对具有代表性的用户进行了一系列访谈,以确定目标用户群体并确定每个用户类型的信息层次结构。然后,为每个用户类型分配视觉元素(例如大小、颜色、对比度等),以反映信息层次结构和工作流程。

结果

用户研究确定了 2 个截然不同的用户群体,作为重新设计的实验室报告的消费者。开发了一种采用 2 级页面层次结构的交互式设计,对内容进行分层,以满足每种用户类型的需求。

结论

通过应用基础设计方法(如视觉层级结构),可以解决显示数字和个人健康数据复杂性质的相关挑战。

讨论

视觉层级结构是一个基础设计原则,可视化团队可以使用它来清晰有效地呈现与医疗保健相关的复杂数据集。

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