JMIR mHealth and uHealth (Nov 2018)

A Real-Time Autonomous Dashboard for the Emergency Department: 5-Year Case Study

  • Yoo, Junsang,
  • Jung, Kwang Yul,
  • Kim, Taerim,
  • Lee, Taerim,
  • Hwang, Sung Yeon,
  • Yoon, Hee,
  • Shin, Tae Gun,
  • Sim, Min Seob,
  • Jo, Ik Joon,
  • Paeng, Hansol,
  • Choi, Jong Soo,
  • Cha, Won Chul

DOI
https://doi.org/10.2196/10666
Journal volume & issue
Vol. 6, no. 11
p. e10666

Abstract

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BackgroundThe 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. ObjectiveThis 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. MethodsWe developed a dashboard based on three principles—“anytime, anywhere, at a glance;” “minimal interruption to workflow;” and “protect patient privacy”—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. ResultsThe 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. ConclusionsWe developed a real-time autonomous ED dashboard and successfully used it for 5 years with good evaluation from users.