Boarding has reached crisis levels across the United States, recently culminating in a letter from ACEP and other national organizations to the President outlining the drastic harms to patients, staff, and clinicians.¹ However, despite widespread agreement that boarding is a threat to our specialty and patients, there is lack of consensus on how to visualize, and even define, the boarding crisis. In our emergency department, we recognized that our current metrics do not allow for the many diverse stakeholders—including frontline clinicians, staff, and administrators—to engage with up-to-date boarding data and generate solutions.^2,3 Our team aimed to create a blueprint for visualizing boarding that is accessible and scalable at any institution across the United States.

The Gap

Health systems typically rely on validated scoring systems such as the National Emergency department Overcrowding Score (NEDOCS).⁴ While these can help quantify boarding severity in real-time, they have limitations when it comes to generating system-level interventions. First, they do not allow for visualization of trends over time, which is critical to identifying drivers of boarding and directing potential interventions. Boarding is associated with several upstream factors, including hospital occupancy and inpatient capacity, and identifying these factors within an institution are critical to implementing the multidisciplinary solutions this problem requires.^5,6 Second, NEDOCS rely on several complex inputs that require institutional and real-time operational knowledge, which may limit usability to a small subset of emergency department leadership. Given the broad impact of boarding, democratizing access to information is a powerful tool to create inclusion and source potentially innovative ideas from a diverse group of stakeholders.

Our Approach

We used a design thinking approach to develop an accessible and interpretable visual boarding dashboard for both daily operational and quality improvement use by a broad audience. Design thinking centers the experience of the end-user to create usable products, including iterative prototyping and rapid incorporation of feedback.⁷ We conducted a comprehensive literature review, 13 stakeholder interviews, and consultation with experts in data management and visualization, aiming to design a single dashboard for utilization by three distinct groups of end-users: frontline clinicians, emergency department management, and hospital-level administrators.

The Final Product

FIGURE 1: Mock-up of internal dashboard displaying boarding heatmap by day and hour. (Click to enlarge.)

The ZSFG boarding dashboard is a web-based platform that visualizes boarding as a temporal heatmap. The dashboard displays the number of boarded patients by hour in a single snapshot that defaults to the past 32 days (Figure 1) and can also be collapsed to show average boarding by several time periods including by day, week, month, quarter and year (Figure 2). Boarding is defined as any patient still in the emergency department more than 120 minutes from admission request.⁸ The dashboard can be stratified by age, emergency severity index (ESI), and emergency department length of stay, and other key variables. Data are updated in near real-time from our electronic medical record (Epic Systems) and visualized using Tableau (Tableau Software Version: 2019, Mountain View, CA).

FIGURE 2: Mock-up of internal dashboard collapsed to average boarding by day and hour. (Click to enlarge.)

From October 1, 2022 to March 16, 2023, the dashboard had 963 views, with 13 high-volume users accounting for 374 views. The heatmap allows any end-user, including clinicians and staff, to quickly assess key features of boarding at our institution, including predictability, temporality, and cyclicality. In our department, boarding reliably peaks during the middle of the day and during midweek (Tues-Thurs). We also find that our levels of emergency department boarding are correlated strongly with inpatient census. Making these trends more accessible for all users helped lead to several multidisciplinary interventions, including: staffing the ED with medical-surgical nurses during predicted boarding peaks, facilitating inpatient hallway boarding, and supplementing inpatient capacity and discharge planning. The success of these interventions has relied on collaboration with our inpatient colleagues, and making these trends broadly accessible to stakeholders outside the emergency department was critical to generating institutional support.

Sharing Our Approach

Boarding is a national problem, but trends and drivers may be institution specific. Though our emergency department, an urban Level I trauma center and safety net hospital, may be different than others facing similar throughput issues, our approach is dynamic and applicable in a variety of settings. Even with variability across institutions, efficiently visualizing institution specific trends can help direct root cause analyses.⁹ Our boarding heatmap allows any emergency department stakeholder to quickly identify trends in and the severity of boarding to inform interventions. The heatmap enables frontline clinicians to better predict boarding and shift practice patterns appropriately, while also engaging a broader audience to understand the problem and generate ideas for institution-wide responses. While there is lack of consensus in the literature on how to best define and visualize boarding, we propose the heatmap as an effective, accessible method for informing local intervention that is both standardized and flexible to institutional trends and variability. Solving the boarding crisis will require multidisciplinary collaboration between departments and across stakeholder groups—democratizing boarding data is an important first step.

Ms. Schwartz (@HOPESCHWARTZY) is a 4th year medical student at UCSF and health policy fellow at the Kaiser Family Foundation, where she conducts research on cost, quality, and value of emergency department care.

Dr. Peabody (@TOFFPEABODY) is an associate clinical professor of emergency medicine and director of the UCSF Acute Care Innovation Center.

Dr. Straube is an emergency physician at the Zuckerberg San Francisco General Hospital for the University of California, San Francisco and serves as the assistant medical director the emergency department.

References

1. Davis J. Update on the ED boarding crisis: ACEP and 34 other organizations send letter to president Biden calling for a summit. ACEP website. Published November 10, 2022. Accessed November 29, 2023.
2. Bauchwitz B, Lynn S, Weyhrauch P, et al. Thematic issues in analysis and visualization of emergency department patient flow. Proc Int Symp Hum Factors Ergon Health Care. 2018;7(1):132-139.
3. The Joint Commission. R3 report issue 4: Patient flow through the emergency department. The Joint Commission website. https://www.jointcommission.org//media/tjc/documents/standards/r3-reports/r3_report_issue_4.pdf. Published December 19, 2012. Accessed November 29, 2023.
4. Weiss SJ, Derlet R, Arndahl J, et al. Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS). Acad Emerg Med. 2004;11(1):38-50.
5. Janke AT, Melnick ER, Venkatesh AK. Hospital occupancy and emergency department boarding during the COVID-19 pandemic. JAMA Netw Open. 2022;5(9):e2233964.
6. Kelen GD, Wolfe R, D’Onofrio G, et al. Emergency department crowding: the canary in the health care system. NEJM Catalyst website. https://catalyst.nejm.org/doi/full/10.1056/CAT.21.0217. Published online September 28, 2021. Accessed November 29, 2023.
7. Schwartz HEM, Stark NR, Sowa CS, et al. Building back better: applying lessons from the COVID-19 pandemic to expand critical information access. J Emerg Med. 2021;61(5):607-614.
8. Agency for Healthcare Research and Quality. Emergency department performance measures and benchmarking summit: The consensus statement. https://qualityindicators.ahrq.gov/Downloads/Resources/Publications/2006/EDPerformanceMeasures-ConsensusStatement.pdf. Published 2005. Accessed November 29, 2023.
9. Park S, Bekemeier B, Flaxman A, et al. Impact of data visualization on decision-making and its implications for public health practice: a systematic literature review. Inform Health Soc Care. 2022;47(2):175-193.