This paper is in the following e-collection/theme issue:

mHealth in a Clinical Setting (624)

Published on in Vol 6, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10666, first published .
A Real-Time Autonomous Dashboard for the Emergency Department: 5-Year Case Study

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

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

Authors of this article:

Junsang Yoo1 Author Orcid Image ;   Kwang Yul Jung2 Author Orcid Image ;   Taerim Kim2 Author Orcid Image ;   Taerim Lee3 Author Orcid Image ;   Sung Yeon Hwang2 Author Orcid Image ;   Hee Yoon2 Author Orcid Image ;   Tae Gun Shin2 Author Orcid Image ;   Min Seob Sim2 Author Orcid Image ;   Ik Joon Jo2 Author Orcid Image ;   Hansol Paeng4 Author Orcid Image ;   Jong Soo Choi1, 5 Author Orcid Image ;   Won Chul Cha2, 5, 6 Author Orcid Image
Article Authors Cited by (26) Tweetations (5) Metrics

    Original Paper

    1SAIHST, Department of Digital Health, Sungkyunkwan University, Seoul, Republic of Korea

    2Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

    3Department of Emergency Medicine, Chamjoeun Hospital, Gwangju, Republic of Korea

    4Human Understanding Design Center (HUDC), Seoul Medical Center, Seoul, Republic of Korea

    5Health Information Center, Samsung Medical Center, Seoul, Republic of Korea

    6Department of Digital Health, Samsung Advanced Institute of Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea

    Corresponding Author:

    Won Chul Cha, MD

    Department of Emergency Medicine

    Samsung Medical Center

    Sungkyunkwan University School of Medicine

    81, Irwon-ro

    Gangnam-gu

    Seoul, 06351

    Republic of Korea

    Phone: 82 2 3410 2053

    Fax:82 2 3410 0012

    Email: wc.cha@samsung.com


    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 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.

    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.

    JMIR Mhealth Uhealth 2018;6(11):e10666

    doi:10.2196/10666

    Keywords

    dashboard; development; emergency department; evaluation; health information technology; situation awareness; usability 


    An emergency department (ED) is a complex system designed to treat patients with various conditions simultaneously. Even though ED providers try to triage patients according to their clinical needs while managing scarce resources, these activities are often overwhelmed by the complexity and large volume of data. Emergency physicians are required to treat multiple patients while maintaining situational awareness of the ED surroundings [1]. This task is very challenging because it requires acquisition, processing, integration, and archiving of large data at multiple levels [2]. Thus, physicians frequently feel like they are losing control over the ED, which aggravates burnout and affects performance [3,4].

    Moreover, many EDs are already overcrowded, thus increasing the complexity [5-7]. While ED overcrowding remains a major health care issue, it significantly and adversely affects quality of care by influencing major quality factors, such as timeliness, effectiveness, efficiency, safety, and patient-centeredness, resulting in increased mortality and morbidity [5,8-10]. Multiple studies have suggested the use of system engineering and science to improve ED performance, streamline the process, and improve the throughput [11-13]. However, a strategic approach to identify process delays and supply-demand mismatch using traditional hospital information systems (HISs) is not feasible. It is important to monitor and manage the ED as a whole.

    The dashboard is “a visual display of the most important information needed to achieve one or more objectives” [14]. Because the situation in the ED affects the quality of care and patient outcomes, clinicians use different diagnostic and treatment strategies depending on the situation [15]. Therefore, recognizing the correct situation is becoming increasingly important to emergency medical clinicians [16].

    While a quality dashboard helps decision making at the organization level, a clinical dashboard helps decision making regarding patient care [17]. A dashboard that fits the changing situations in the ED in the real time must have the characteristics of both quality and clinical dashboards [17]. Recent studies on the ED dashboard system have reported its potential to improve patient safety, situation awareness, and workflow [15,18], but such studies have not addressed long-term experiences and association between the introduction of the dashboard and mental workload of the users. In particular, ensuring real-time availability is challenging and important because nonreal–time dashboards cannot support decision making [15].

    This study aimed to describe the development of a real-time organizational dashboard for the ED and to evaluate its usability.


    This study was approved by the Institutional Review Board of the study site (Institutional Review Board File #SMC 2018-01-040-001).

    Study Setting

    The study was carried out in a metropolis: Seoul. It was undertaken at an ED with an annual visit volume of 79,000 patients in a tertiary teaching hospital. The hospital has about 2000 inpatient beds. This ED is one of the most overcrowded EDs in the country [19].

    The HIS was in use in this ED since 1994, supported by electronic medical records and a picture archiving and communication system. Although the history of this HIS is long and its technical quality was one of the most advanced in the country, no ED-specific dashboard system was ever used in this hospital.

    Development

    The Happinovation and the Happy Emergency Room Team

    In 2012, an institution-wide project, the “Happinovation” (Happy innovation), was initiated to enhance patient and provider happiness through process and hardware innovations. The “Happy Emergency Room Team” was formed as a satellite team for the overall project. The team focused on visualizing the ED process for providers and patients.

    Specifically, 2 subprojects were implemented. One was a visualization project for providers—an electronic dashboard to develop visualization of ED performance status on wall-mounted monitors and PCs. The other was a visualization project for patients and their families—a wall-mounted electronic dashboard, kiosks, and tablets.

    The multidisciplinary Happy Emergency Room Team included 6 physicians, 4 nurses, 1 administrator, 2 quality improvement team members, 2 consultants, and 2 designers. While hospital staff provided inputs, consultants and designers tried to see things from patients’ perspective, thus balancing the conclusion. Several rounds of discussions and debates took place before the first dashboard principle and design feature was created.

    Dashboard Principle

    The team had agreed on the following 3 dashboard principles that define the characteristics of the dashboard.

    Anytime, Anywhere, at a Glance

    The dashboard was designed to be like a traditional whiteboard for the ED, which means that it should be mounted on a wall and be visible to providers from about 2-5 m away. It should be in a static mode, without flipping the screen, such that providers would not waste any time to find the desired information [20]. Since multiple providers should be able to access the information, interactivity was not feasible. We did not include a writing and communication function from the dashboard because it was designed to only offer providers the overall ED status at a glance [15,21].

    Minimal Interruption to Workflow

    The dashboard should be integrated with the clinical workflow. An unfavorable clinical workflow often changes after implementing health information technology [21-23]. However, the Happy Emergency Room Team worried that the dashboard could be a source of botheration. Therefore, we designed it such that it would not require any additional inputs. This means that all data should come from the legacy system.

    ‎
    Figure 1. Geographical layout of the emergency department.
    View this figure

    All information on the dashboard is automatically generated from previous columns of HIS. For example, the moment at which a physician’s order or barcode of a clinical sample is input by a nurse, it is linked to the dashboard system such that the whole operating process could be automatically marked and shown without additional inputting processes. This is also different from traditional dry-erase whiteboards [24].

    Protect Patient Privacy

    It is important that patients’ privacy be secured [25]. Because the screen is physically accessible to patients and families, most information should be deidentified and symbolized to prevent unnecessary misunderstandings and debates.

    Design Features

    The team adopted the following 3 design features for the dashboard:

    Geographical Layout

    The dashboard should indicate the ED floor plan. A geographical layout would give intuitive information to ED providers on what is going on where in the ED. It is also very common that ED providers recognize and communicate about patients with their bed locations and not with their numbers or names, which made it more intuitive and effective to use a geographical layout rather than a patient list (Figure 1).

    Patient-Level Alert

    All beds and chairs were symbolized to stand for a patient to provide patient-specific information to ED clinicians. Additional patient-level information was included to provide a real-time alert to providers through encoded colors and symbols, especially regarding process delays. The main objective of this concept was to provide ED staff with patient-level alerts such that a provider could immediately notice delays in catering to patients.

    Real-Time Summary Data

    The dashboard would show summary statistics regarding ED performance in the real time. While in-depth information for each patient is available in the pre-existing HIS, a real-time summary depends mostly on subjective feeling of individual providers, which varies significantly due to the lack of information on summary information over ED state. With summary data, providers would be able to reschedule clinical processes for their patients’ efficient journey. For example, a nurse could direct a patient to the X-ray if there is a long queue for a co-ordered computed tomography.

    Prototyping

    Initially, multiple measures were suggested for the dashboard. Measures were chosen and categorized based on a “conceptual model of ED crowding.” The model consisted of 3 factors, among which the throughput factors, which reflect the internal process of ED care, were mostly demonstrated with the dashboard [13]. Among input factors, which are components that contribute to the demand for ED services, patient severity and measure of visits were included. Cautions on infection information were also included since they were well correlated with severity and patient allocation within the ED and hospital. Throughput factors were divided into 2 sections: structures and functions. Output factors, such as boarding and discharge data, were also included. Boarding pertains to the inability to admit a patient to a ward due to the lack of inpatient beds even through the patient is determined to be admitted.

    We used a Windows server as the ED visualization platform to support various devices in the ED, including the dashboard and kiosks for patients and mobile devices. Our entire platform was developed and deployed on 2 Windows 2008 servers, each with a 1200-GB hard drive and 20-GB memory, and 2 4-core Intel Xeon 2.4 GHz processors. The servers queried the measurements mentioned above from the electronic medical records and picture archiving and communication system servers. A Windows communication foundation was used as a visualization tool (Figure 2).

    Evolution of the Emergency Department Dashboard

    We developed and updated the dashboard over 5 years. During the observation, the ED had gone through a Middle East Respiratory Syndrome outbreak, followed by a major structural and functional renovation [26]. The ED dashboard adopted such changes and evolved through the process.

    Evaluation

    Selection of Participants

    Inclusion criteria were those currently working as ED physicians and triage or charge nurses and those using the dashboard. Participants were recruited from January 1 to February 10, 2018.

    Intervention

    Participants responded to 20 questions on a 5-point Likert scale after completing a consent form. The first 10 items of the questionnaire were derived from the system usability scale (SUS) to investigate the usability of the dashboard [27]. The last 10 items were derived from the situation awareness index (SAI), which we composed based on the Situation Awareness Rating Technique (SART) [28]. The SAI aimed to assess whether ED physicians and nurses were using the dashboard to help them recognize the situation. The SAI includes the constructs of the SART as a whole, and small modifications were made to adjust it to fit the dashboard.

    ‎
    Figure 2. Transfer of electronic medical record (EMR) and picture archiving and communication system (PACS) data to the emergency department (ED) visual architecture platform. LAN: Local Area Network.
    View this figure

    After completing the questionnaire, the participants received about US $8 as compensation for participating in the survey.

    Outcome Analysis

    The SUS scores were interpreted using an adjective rating scale [29].

    The SAI score was calculated using the following formula:

    SAI = {Q11 + Q12 + Q13 + Q14 + Q15 + Q16 + (6 - Q17) + Q18 + Q19 + Q20} / 10, where Q: question number.

    The SAI scores were also examined using descriptive analyses.


    Design and Structure

    Introduction to the First Version of the Emergency Department Dashboard

    The semicircle-shaped indicator in the upper central area represents the complexity of the ED and presents the expected mean length of stay of a current patient in the ED. The semicircle borrows the scheme of the traffic light so that the user intuitively grasps the current situation of the ED.

    A semitransparent colored square represents each section of the ED and matches the geographical layout presented in Figure 1. The squares are not visible on the actual dashboard. Small icons, such as that shown in the red circle, indicate patients, and they intuitively inform the user about the patient’s journey through the color corresponding to the patient’s process on the left.

    The left side of the dashboard presents a summary of the patient process. This information allows the physician to set up a patient diagnosis strategy and the nurse to determine the order of various tests. The central area of the dashboard reflects the geographical layout of the ED. Here, individual patients’ specific information is displayed, such as real-time clinical processes. The right side of the dashboard presents the number of patients by zone, thereby enabling efficient distribution of medical labor (Figure 3).

    Evolution of the Emergency Department Dashboard

    Major difference between versions 1 and 2 of the dashboard is that the latter reflects a geographical change. In 2015, the ED of the study site underwent a Middle East Respiratory Syndrome outbreak, and a respiratory isolation area was established and operated. This structural change to the ED was reflected on the dashboard (Figure 4).

    In version 3, a revision was made to improve usability. We updated the dashboard to change the overall color coding. By doing so, we were able to reflect the users’ suggestions, such as “difficulty to identify bed status” (Figure 4).

    A major change in version 4 is the improvement of patient-specific information.

    The circle next to the patient indicates the mapping of the Korean Triage and Acuity Scale score from 1 to 5, presented from red to green. Additionally, the rectangle next to the patient reflects “infection caution,” such as “air caution” and “blood caution” (Figure 4).

    ‎
    Figure 3. The first version of the emergency department dashboard.
    View this figure
    ‎
    Figure 4. Evolution of the emergency department dashboard, showing the second, third, and final versions.
    View this figure

    Evaluation

    Participant Characteristics

    A total of 52 participants were recruited; 25 were physicians and 27 were nurses. In the physician group, 17 were males and 8 were females; in the nurse group, only 2 were males and 25 were females. The participants’ years of experience also varied; 8 had worked for less than 3 years, 10 had worked for 3-5 years, 19 had worked for 5-10 years, and 15 had worked for over 10 years (Table 1).

    System Usability Scale

    The SUS score of the ED dashboard system was 67.6 points (Table 2). The SUS score showed a slight difference between the 2 groups; the physician and nurse groups had scores of 67.5 and 67.69 points, respectively. We could interpret our result as follows: acceptability of the dashboard was “marginally high,” and the adjective rating was “OK-to-Good” [29]. These findings indicate that the participants used it very frequently. They also felt that this system was easy to learn and use.

    Situation Awareness Index

    The overall SAI score was 3.87 points, and the score of the physician group (3.95) was higher than that of the nurse group (3.80). The top 5 rated items were “concentration support” (4.15), “complexity representation” (4.02 points), “variability representation” (3.96 points), “information quality provided” (3.94 points), and “familiarity of dashboard” (3.94 points). However, the score for “division of attention” was 2.25 points (Table 3).

    Table 1. Characteristics of participants.
    CharacteristicPhysician (n=25)Nurse (n=27)Total (N=52)
    Age group, n (%)

    		20s2 (8)6 (22)8 (15)

    		30s19 (76)19 (70)38 (73)

    		40s1 (4)2 (7)3 (6)

    		50s3 (12)0 (0)3 (6)
    Sex, n (%)

    		Male17 (68)2 (7)19 (37)

    		Female8 (32)25 (93)33 (64)
    Years of experience, n (%)

    		0-38 (32)0 (0)8 (15)

    		3-56 (24)4 (15)10 (19)

    		5-104 (16)15 (56)19 (37)

    		>107 (28)8 (30)15 (29)
    Table 2. System usability scale scores.
    ItemPhysician, mean (SD)Nurse, mean (SD)Total, mean (SD)
    Q1. I think that I would like to use this dashboard frequently.4.52 (0.7)4.15 (0.5)4.33 (0.6)
    Q2. I found the dashboard unnecessarily complex.2.44 (0.9)2.52 (1.0)2.48 (0.9)
    Q3. I thought the dashboard was easy to use.3.76 (0.7)3.85 (0.6)3.81 (0.7)
    Q4. I think that I would need the support of a technician to be able to use this dashboard.3.08 (1.1)2.89 (1.1)2.98 (1.1)
    Q5. I found that the various functions in this dashboard were well integrated.3.56 (0.8)3.78 (0.7)3.67 (0.7)
    Q6. I thought there was too much inconsistency in this dashboard.2.24 (0.9)2.07 (0.7)2.15 (0.8)
    Q7. I would imagine that most people would learn to use this dashboard very quickly.3.72 (0.9)3.93 (0.6)3.83 (0.8)
    Q8. I found the dashboard very cumbersome to use.2.12 (0.7)2.11 (0.6)2.12 (0.7)
    Q9. I felt very confident using the dashboard.3.84 (0.9)3.67 (0.8)3.75 (0.9)
    Q10. I needed to learn a lot of things before I could get going with this dashboard.2.52 (1.1)2.70 (1.1)2.62 (1.1)
    System usability scale score67.50 (12.0)67.69 (11.0)67.60 (11.4)
    Table 3. Situation awareness and dashboard results.
    ConstructItemPhysician, mean (SD)Nurse, mean (SD)Total, mean (SD)
    Instability representationQ11. The dashboard adequately represents the instability of the EDa.3.96 (1.0)3.78 (0.7)3.87 (0.8)
    Complexity representationQ12. The dashboard adequately represents the complexity of the ED.4.12 (0.9)3.93 (0.6)4.02 (0.8)
    Variability representationQ13. The dashboard contains key elements that are changing in the ED.4.08 (0.6)3.85 (0.8)3.96 (0.7)
    Arousal supportQ14. The dashboard helps me be alert and clearer.3.92 (0.9)3.74 (0.7)3.83 (0.8)
    Concentration supportQ15. The dashboard helps me focus on the situation in the ED.4.20 (0.6)4.11 (0.6)4.15 (0.6)
    Spare mental capacity supportQ16. I can acquire additional mental capacity in a pressing ED situation.3.60 (1.2)3.48 (0.9)3.54 (1.0)
    Division of attentionQ17. The dashboard distracts attention from important tasks of the ED.2.12 (0.7)2.37 (0.9)2.25 (0.8)
    Information quantity providedQ18. The quantity of information provided by the dashboard is appropriate for performing ED tasks.3.84 (0.9)3.67 (0.8)3.75 (0.8)
    Information quality providedQ19. The quality of information provided by the dashboard is appropriate for performing ED tasks.3.92 (1.0)3.96 (0.6)3.94 (0.8)
    Familiarity of dashboardQ20. I can perform ED tasks more proficiently using the dashboard.4.00 (0.9)3.89 (0.8)3.94 (0.9)
    Situation awareness index—3.95 (0.6)3.80 (0.5)3.87 (0.6)

    aED: emergency department.


    Principal Findings

    The ED dashboard was successfully developed and implemented. The system is independent of manual input and is fully connected to the legacy HIS. The graphical and statistical concepts were determined during the developmental period, and they were upgraded gradually. Though clinical dashboards for EDs have been developed in other studies [15,30-32], this study is the first to examine its long-term use and conduct serial upgrades.

    We used SUS, a formal, highly validated usability test, and obtained a score of 67.6 points from physicians and nurses. This score could be interpreted as indicating “marginally high acceptability” with “OK-to-Good usability.” Additionally, the ED staff responded that the dashboard presented the situation in the ED effectively and that they could better focus on the changing situation in the ED by using it. The quality of the information provided by the dashboard was rated high; however, the quantity of information was rated relatively low. There is a need for a systematic investigation to establish the information that ED staff seek and a subsequent improvement plan to reflect the same in the system.

    Clinical Aspects

    It has been one of the major responsibilities of ED staff to keep patients’ processes on track and ensure timely results [33]. To do so, ED providers had to call numerous departments and browse through multiple windows repeatedly during their duty time. As the tasks and volume of ED work-ups grew, this timekeeping function had become significantly heavy. The ED dashboard described in this study focused on providing a visual representation of this “hidden” information pertaining to the ED process, such that ED providers could plan and carry out their tasks proactively.

    The visualized information not only pertained to individual patients’ processes but also reported the department’s performance status. As the government and insurance companies focus on performance as a group of patients, it has become an essential job for the system administrator to be able to assess real-time statistics. ED providers’ responsibility as administrators demands tools like our dashboard during their work.

    Our ED dashboard affects the workflow of various medical personnel in the ED in a variety of ways, ranging from simple information delivery to clinical decision-making support. If the dashboard indicates that the ED is extremely overcrowded, the ED chief could contact the national acute care system to control the transfer of new patients. Additionally, physicians could grasp the timely information of each patient using this dashboard. The charge nurse could improve the efficacy of the ED by reassigning each nurse to more appropriate zones based on the information obtained from the dashboard. Triage nurses could also use the dashboard to allocate patients to appropriate treatment zones.

    Comparison With Previous Work

    Recent review articles have indicated that an ED dashboard could be useful for “saving time and reducing the risk of errors or delay” [18]. However, the association between the introduction of an electronic dashboard and the mental workload of ED staff is controversial. Further, there is little evidence to support that it improves clinical outcomes [18].

    A major difference between our system and other electronic boards is that our dashboard does not allow manual or direct input of patient-specific information. We have fully synchronized our dashboard with the legacy system such that physicians’ and nurses’ additional inputs are not required to use the dashboard. By achieving this goal, our system was found to provide effective arousal support, concentration support, and spare mental capacity (3.83 points, 4.15 points, and 3.54 points, respectively) even in the busy clinical setting.

    Limitations

    First, this is a single-center case study with its unique HIS. Its feasibility and usability should be validated in other institutions. Considering that the implementation of this system in other institutions has been discussed, subsequent investigation on ED dashboard utilization is expected in the near future.

    The measures used for the dashboard are not universally agreed upon. They have mainly been used in a highly crowded EDs of a teaching hospital. When used in smaller EDs, the measures of interest would be different. Additionally, the measures were not compared with the national standard, which requires further research.

    The SAI has not been validated. We searched for questionnaires to investigate the association between dashboards and situation awareness, but we could not find any that suited our purpose. Therefore, we developed a questionnaire based on the SART and applied it in this study. However, this questionnaire is not validated, and therefore, its interpretation value is limited.

    Finally, we could not investigate the association between the effectiveness of the ED dashboard and clinical outcomes. However, it is difficult to identify this association because the ED is one of the most complex systems affected by several uncontrollable factors. Therefore, multicenter comparative studies need to be conducted to examine this association.

    Conclusions

    We developed a real-time autonomous ED dashboard and successfully used it for 5 years. ED physicians and nurses rated the usability of the ED dashboard as “OK-to-Good.” We realize that continuous maintenance is important because the dashboard should reflect the situation of the ED.

    Acknowledgments

    The authors acknowledge the members of the Department of Quality Improvement and of the Health Information Center for their contribution to the design and development of the emergency department dashboard. This research was supported by Basic Science Research Program through the National Research Foundation of Korea and funded by the Ministry of Education (Grant #2017R1D1A1B03034690).

    Conflicts of Interest

    None declared.

    1. Endsley MR. Toward a Theory of Situation Awareness in Dynamic Systems. hum factors 1995 Mar 01;37(1):32-64. [CrossRef]
    2. Wickens CD. Situation Awareness and Workload in Aviation. Curr Dir Psychol Sci 2016 Jun 24;11(4):128-133 [FREE Full text] [CrossRef]
    3. De Stefano C, Philippon A, Krastinova E, Hausfater P, Riou B, Adnet F, et al. Effect of emergency physician burnout on patient waiting times. Intern Emerg Med 2018 Dec;13(3):421-428. [CrossRef] [Medline]
    4. Garrouste-Orgeas M, Perrin M, Soufir L, Vesin A, Blot F, Maxime V, et al. The Iatroref study: medical errors are associated with symptoms of depression in ICU staff but not burnout or safety culture. Intensive Care Med 2015 Feb;41(2):273-284 [FREE Full text] [CrossRef] [Medline]
    5. Pines JM, Iyer S, Disbot M, Hollander JE, Shofer FS, Datner EM. The effect of emergency department crowding on patient satisfaction for admitted patients. Acad Emerg Med 2008 Sep;15(9):825-831. [Medline]
    6. Pines JM, McCarthy ML. The crowding-effectiveness link: it doesn't matter how fast we deliver care if we don't deliver it right. Ann Emerg Med 2011 Mar;57(3):201-202. [CrossRef] [Medline]
    7. Warden G, Griffin RB, Erickson SM, Mchugh M, Wheatley B, Dharshi A, et al. Hospital-based emergency care: at the breaking point. Washington, DC: National Academies Press; Jun 2006.
    8. Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med 2009 Jan;16(1):1-10 [FREE Full text] [CrossRef] [Medline]
    9. Kang J, Kim J, Jo YH, Kim K, Lee JH, Kim T, et al. ED crowding and the outcomes of out-of-hospital cardiac arrest. Am J Emerg Med 2015 Nov;33(11):1659-1664. [CrossRef] [Medline]
    10. Cha WC, Cho JS, Shin SD, Lee EJ, Ro YS. The impact of prolonged boarding of successfully resuscitated out-of-hospital cardiac arrest patients on survival-to-discharge rates. Resuscitation 2015 May;90:25-29. [CrossRef] [Medline]
    11. Storrow AB, Zhou C, Gaddis G, Han JH, Miller K, Klubert D, et al. Decreasing lab turnaround time improves emergency department throughput and decreases emergency medical services diversion: a simulation model. Acad Emerg Med 2008 Nov;15(11):1130-1135 [FREE Full text] [CrossRef] [Medline]
    12. White BA, Baron JM, Dighe AS, Camargo CA, Brown DFM. Applying Lean methodologies reduces ED laboratory turnaround times. Am J Emerg Med 2015 Nov;33(11):1572-1576 [FREE Full text] [CrossRef] [Medline]
    13. Asplin BR, Magid DJ, Rhodes KV, Solberg LI, Lurie N, Camargo CA. A conceptual model of emergency department crowding. Ann Emerg Med 2003 Aug;42(2):173-180. [CrossRef] [Medline]
    14. Few S. Information Dashboard Design: The Effective Visual Communication of Data. Sebastopol, California: O'Reilly Media, Incorporated; 2006.
    15. Franklin A, Gantela S, Shifarraw S, Johnson TR, Robinson DJ, King BR, et al. Dashboard visualizations: Supporting real-time throughput decision-making. J Biomed Inform 2017 Dec;71:211-221. [CrossRef] [Medline]
    16. Jarvis PRE. Improving emergency department patient flow. Clin Exp Emerg Med 2016 Jun;3(2):63-68 [FREE Full text] [CrossRef] [Medline]
    17. Dowding D, Randell R, Gardner P, Fitzpatrick G, Dykes P, Favela J, et al. Dashboards for improving patient care: review of the literature. Int J Med Inform 2015 Feb;84(2):87-100. [CrossRef] [Medline]
    18. Randell R, Greenhalgh J, Wyatt J, Gardner P, Pearman A, Honey S, et al. Electronic whiteboards: review of the literature. Stud Health Technol Inform 2015;210:389-393. [Medline]
    19. Cha WC, Ahn KO, Shin SD, Park JH, Cho JS. Emergency Department Crowding Disparity: a Nationwide Cross-Sectional Study. J Korean Med Sci 2016 Aug;31(8):1331-1336 [FREE Full text] [CrossRef] [Medline]
    20. Bjørn P, Hertzum M. Artefactual Multiplicity: A Study of Emergency-Department Whiteboards. Comput Supported Coop Work 2010 Oct 27;20(1-2):93-121. [CrossRef]
    21. Miller K, Mosby D, Capan M, Kowalski R, Ratwani R, Noaiseh Y, et al. Interface, information, interaction: a narrative review of design and functional requirements for clinical decision support. J Am Med Inform Assoc 2018 May 01;25(5):585-592. [CrossRef] [Medline]
    22. Ash JS, Berg M, Coiera E. Some unintended consequences of information technology in health care: the nature of patient care information system-related errors. J Am Med Inform Assoc 2004 Apr;11(2):104-112 [FREE Full text] [CrossRef] [Medline]
    23. Bloomrosen M, Starren J, Lorenzi NM, Ash JS, Patel VL, Shortliffe EH. Anticipating and addressing the unintended consequences of health IT and policy: a report from the AMIA 2009 Health Policy Meeting. J Am Med Inform Assoc 2011;18(1):82-90 [FREE Full text] [CrossRef] [Medline]
    24. Zhang AL, Chen RX, Kang MF, Fan HL, Wang WL. Study of the regulatory effect of acupuncture on rotation-induced gastric dysrhythmia in rabbits. World J Gastroenterol 1997 Mar 15;3(1):54-55 [FREE Full text] [CrossRef] [Medline]
    25. Tsou M, Jung C, Allen C, Yang J, Gawron J, Spitzberg B, et al. Social media analytics and research test-bed (SMART dashboard). In: Proceedings of the 2015 International Conference on Social Media & Society Article No. 2. 2015 Presented at: The 2015 International Conference on Social Media & Society; July 27 - 29, 2015; Toronto, Canada. [CrossRef]
    26. Park GE, Ko J, Peck KR, Lee JY, Lee JY, Cho SY, et al. Control of an Outbreak of Middle East Respiratory Syndrome in a Tertiary Hospital in Korea. Ann Intern Med 2016 Jul 19;165(2):87-93. [CrossRef] [Medline]
    27. Jordan P, Jordan J, McClelland I. SUS-A quick and dirty usability scale. In: Usability Evaluation in Industry. Boca Raton, Florida: Taylor & Francis, Inc; 1996:189-194.
    28. Selcon S, Taylor R. Evaluation of the Situational Awareness Rating Technique(SART) as a tool for aircrew systems design. In: AGARD, Situational Awareness in Aerospace Operations. 1989 Presented at: Advisory Group For Airospace Research & Development; october 02 1989; Copenhagen, Denmark   URL: http://www.dtic.mil/dtic/tr/fulltext/u2/a223939.pdf
    29. Bangor A, Kortum P, Miller J. Determining what individual SUS scores mean: Adding an adjective rating scale. Journal of usability studies 2009 May;4(3):114-123 [FREE Full text]
    30. Staib A, Sullivan C, Jones M, Griffin B, Bell A, Scott I. The ED-inpatient dashboard: Uniting emergency and inpatient clinicians to improve the efficiency and quality of care for patients requiring emergency admission to hospital. Emerg Med Australas 2017 Jun;29(3):363-366. [CrossRef] [Medline]
    31. Stone-Griffith S, Englebright JD, Cheung D, Korwek KM, Perlin JB. Data-driven process and operational improvement in the emergency department: the ED Dashboard and Reporting Application. J Healthc Manag 2012;57(3):167-80; discussion 180. [Medline]
    32. Batley NJ, Osman HO, Kazzi AA, Musallam KM. Implementation of an emergency department computer system: design features that users value. J Emerg Med 2011 Dec;41(6):693-700. [CrossRef] [Medline]
    33. Randell R, Keen J, Gates C, Ferguson E, Long A, Ginn C, et al. Managing Quality and Safety in Real Time? Evidence from an Interview Study. Stud Health Technol Inform 2016;228:23-27. [Medline]

    ‎
    ED: emergency department
    HIS: hospital information system
    LAN: Local Area Network
    SAI: situation awareness index
    SART: Situation Awareness Rating Technique
    SUS: system usability scale

    Edited by C Dias; submitted 02.04.18; peer-reviewed by R Randell, A Franklin, A Staib, J Jones; comments to author 14.05.18; revised version received 02.07.18; accepted 10.08.18; published 22.11.18

    Copyright

    ©Junsang Yoo, Kwang Yul Jung, Taerim Kim, Taerim Lee, Sung Yeon Hwang, Hee Yoon, Tae Gun Shin, Min Seob Sim, Ik Joon Jo, Hansol Paeng, Jong Soo Choi, Won Chul Cha. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 22.11.2018.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.