Elshehaly, M, Randell, R, Brehmer, M et al. (4 more authors) (2021) QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement. IEEE Transactions on Visualization and Computer Graphics, 27 (2). pp. 689-699. ISSN 1077-2626
Abstract
Adapting dashboard design to different contexts of use is an open question in visualisation research. Dashboard designers often seek to strike a balance between dashboard adaptability and ease-of-use, and in hospitals challenges arise from the vast diversity of key metrics, data models and users involved at different organizational levels. In this design study, we present QualDash, a dashboard generation engine that allows for the dynamic configuration and deployment of visualisation dashboards for healthcare quality improvement (QI). We present a rigorous task analysis based on interviews with healthcare professionals, a co-design workshop and a series of one-on-one meetings with front line analysts. From these activities we define a metric card metaphor as a unit of visual analysis in healthcare QI, using this concept as a building block for generating highly adaptable dashboards, and leading to the design of a Metric Specification Structure (MSS). Each MSS is a JSON structure which enables dashboard authors to concisely configure unit-specific variants of a metric card, while offloading common patterns that are shared across cards to be preset by the engine. We reflect on deploying and iterating the design of OualDash in cardiology wards and pediatric intensive care units of five NHS hospitals. Finally, we report evaluation results that demonstrate the adaptability, ease-of-use and usefulness of QualDash in a real-world scenario.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Information visualisation, task analysis, co-design, dashboards, design study, healthcare |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) > Nursing Adult (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Clinical & Population Science Dept (Leeds) |
Funding Information: | Funder Grant number NIHR National Inst Health Research 16/04/06 |
Depositing User: | Symplectic Publications |
Date Deposited: | 08 Sep 2020 11:39 |
Last Modified: | 04 Mar 2021 20:42 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/TVCG.2020.3030424 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165165 |