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Chris Gale

dblp:265/4376 · also Chris P. Gale · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0003-4732-382XORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › visualization design
dashboard design
0.512021
QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement · IEEE Trans. Vis. Comput. Graph. 2021

Methods — techniques the papers use, named apart from their topics

task analysis · 0.5design study · 0.5co-design · 0.5
YearPublicationVenuePosition
2021 QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement
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.
Mai El-Shehaly, Rebecca Randell, Matthew Brehmer, Lynn McVey, Natasha Alvarado, Chris Gale, Roy A. Ruddle
IEEE Trans. Vis. Comput. Graph.6
2019 Requirements for a quality dashboard: Lessons from National Clinical Audits
Rebecca Randell, Natasha Alvarado, Lynn McVey, Roy A. Ruddle, Chris Gale, Mamas Mamas, Dawn Dowding
AMIA6