A framework for evaluating dashboards in healthcare

Mengdie Zhuang, David Concannon, Ed Manley

View presentation:2022-10-21T14:48:00ZGMT-0600Change your timezone on the schedule page
2022-10-21T14:48:00Z
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A Framework: Seven Scenarios for Evaluating Dashboards

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The live footage of the talk, including the Q&A, can be viewed on the session page, Visual Analytics of Health Data.

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Keywords

Visualization, Dashboard, Evaluation, Healthcare.

Abstract

In the era of ‘information overload’, effective information provision is essential for enabling rapid response and critical decision making. In making sense of diverse information sources, dashboards have become an indispensable tool, providing fast, effective, adaptable, and personalized access to information for professionals and the general public alike. However, these objectives place heavy requirements on dashboards as information systems in usability and effective design. Understanding these issues is challenging given the absence of consistent and comprehensive approaches to dashboard evaluation. In this paper we systematically review literature on dashboard implementation in healthcare, where dashboards have been employed widely, and where there is widespread interest for improving the current state of the art, and subsequently analyse approaches taken towards evaluation. We draw upon consolidated dashboard literature and our own observations to introduce a general definition of dashboards which is more relevant to current trends, together with seven evaluation scenarios - task performance, behaviour change, interaction workflow, perceived engagement, potential utility, algorithm performance and system implementation. These scenarios distinguish different evaluation purposes which we illustrate through measurements, example studies, and common challenges in evaluation study design. We provide a breakdown of each evaluation scenario, and highlight some of the more subtle questions. We demonstrate the use of the proposed framework by a design study guided by this framework. We conclude by comparing this framework with existing literature, outlining a number of active discussion points and a set of dashboard evaluation best practices for the academic, clinical and software development communities alike.