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2020 | OriginalPaper | Chapter

Designing a Visual Analytics System for Medication Error Screening and Detection

Authors : Tabassum Kakar, Xiao Qin, Cory M. Tapply, Oliver Spring, Derek Murphy, Daniel Yun, Elke A. Rundensteiner, Lane Harrison, Thang La, Sanjay K. Sahoo, Suranjan De

Published in: Computer Vision, Imaging and Computer Graphics Theory and Applications

Publisher: Springer International Publishing

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Abstract

Drug safety analysts at the U.S. Food & Drug Administration analyze medication error reports submitted to the Adverse Event Reporting System (FAERS) to detect and prevent detrimental errors from happening in the future. Currently this review process is time-consuming, involving manual extraction and sense-making of the key information from each report narrative. There is a need for a visual analytics approach that leverages both computational techniques and interactive visualizations to empower analysts to quickly gain insights from reports. To assist analysts responsible for identifying medication errors in these reports, we design an interactive Medication Error Visual analytics (MEV) system. In this paper, we describe the detailed study of the Pharmacovigilance at the FDA and the iterative design process that lead to the final design of MEV technology. MEV a multi-layer treemap based visualization system, guides analysts towards the most critical medication errors by displaying interactive reports distributions over multiple data attributes such as stages, causes and types of errors. A user study with ten drug safety analysts at the FDA confirms that screening and review tasks performed with MEV are perceived as being more efficient as well as easier than when using their existing tools. Expert subjective interviews highlight opportunities for improving MEV and the utilization of visual analytics techniques in general for analyzing critical FAERS reports at scale.

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Title: Designing a Visual Analytics System for Medication Error Screening and Detection
Authors: Tabassum Kakar
Xiao Qin
Cory M. Tapply
Oliver Spring
Derek Murphy
Daniel Yun
Elke A. Rundensteiner
Lane Harrison
Thang La
Sanjay K. Sahoo
Suranjan De
Publisher: Springer International Publishing
Book: Computer Vision, Imaging and Computer Graphics Theory and Applications
Print ISBN: 978-3-030-41589-1

Electronic ISBN: 978-3-030-41590-7

Copyright Year: 2020
DOI: https://doi.org/10.1007/978-3-030-41590-7_12

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