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Origami plot: a novel multivariate data visualization tool that improves radar chart

delete2023-04-01
delete12
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OA
AI
R
Rui Duan *
J
Jiayi Tong
A
Alex J. Sutton
D
David A. Asch
H
Haitao Chu
C
Christopher H. Schmid
Y
Yong Chen *
DOI:10.1016/j.jclinepi.2023.02.020delete
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Abstract

Abstract

En 中文
Objectives: We propose the origami plot, which maintains the original functionality of a radar chart and avoids potential misuse of its connected regions, with newly added features to better assist multicriteria decision-making.Study Design and Setting: Built upon a radar chart, the origami plot adds additional auxiliary axes and points such that the area of the connected region of all dots is invariant to the ordering of axes. As such, it enables ranking different individuals by the overall performance for multicriteria decision-making while maintaining the intuitive visual appeal of the radar chart. We develop extensions of the origami plot, including the weighted origami plot, which allows reweighting of each attribute to define the overall performance, and the pairwise origami plot, which highlights comparisons between two individuals.Results: We illustrate the different versions of origami plots using the hospital compare database developed by the Centers for Medi-care & Medicaid Services (CMS). The plot shows individual hospital's performance on mortality, readmission, complication, and infection, as well as patient experience and timely and effective care, as well as their overall performance across these metrics. The weighted origami plot allows weighing the attributes differently when some are more important than others. We illustrate the potential use of the pairwise origami plot in electronic health records (EHR) system to monitor five clinical measures (body mass index [BMI]), fasting glucose level, blood pressure, triglycerides, and low-density lipoprotein ([LDL] cholesterol) of a patient across multiple hospital visits.Conclusion: The origami plot is a useful visualization tool to assist multicriteria decision making. It improves radar charts by avoiding po-tential misuse of the connected regions. It has several new features and allows flexible customization. (c) 2023 Elsevier Inc. All rights reserved.
Keywords:
Multivariate data
Radar chart
Ranking
Visualization tool
Polar chart
Star chart
Spider chart
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Journal

Journal of Clinical Epidemiology cover
Journal of Clinical Epidemiology
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