Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Apr 2, 2018
Open Peer Review Period: Apr 3, 2018 - Aug 10, 2018
Date Accepted: Aug 10, 2018
(closed for review but you can still tweet)
A Real-Time Autonomous Dashboard for the Emergency Department: 5-Year Case Study
ABSTRACT
Background:
The task of monitoring and managing the entire emergency department (ED) is becoming more important due to increasing pressure on the ED. Recently, dashboards have received the spotlight as health information technology to support these tasks.
Objective:
This study aimed to describe the development of a real-time autonomous dashboard for the ED and to evaluate perspectives of clinical staff on its usability.
Methods:
We developed a dashboard based on three principles—“anytime, anywhere, at a glance;†“minimal interruption to workflow;†and “protect patient privacyâ€â€”and 3 design features—“geographical layout,†“patient-level alert,†and “real-time summary data.†Items to evaluate the dashboard were selected based on the throughput factor of the conceptual model of ED crowding. Moreover, ED physicians and nurses were surveyed using the system usability scale (SUS) and situation awareness index as well as a questionnaire we created on the basis of the construct of the Situation Awareness Rating Technique.
Results:
The first version of the ED dashboard was successfully launched in 2013, and it has undergone 3 major revisions since then because of geographical changes in ED and modifications to improve usability. A total of 52 ED staff members participated in the survey. The average SUS score of the dashboard was 67.6 points, which indicates “OK-to-Good†usability. The participants also reported that the dashboard provided efficient “concentration support†(4.15 points), “complexity representation†(4.02 points), “variability representation†(3.96 points), “information quality†(3.94 points), and “familiarity†(3.94 points). However, the “division of attention†was rated at 2.25 points.
Conclusions:
We developed a real-time autonomous ED dashboard and successfully used it for 5 years with good evaluation from users.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.