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This dashboard does fulfill Few’s one-sentence definition of a dashboard, but there is certainly room for improvement. It displays information needed to improve patient outcomes by indicating harmful trends. These can be addressed with further investigation and solutions can be implemented. All of the data for key indicators is consolidated on a single screen. While it reads like a report, stop-light color-coding does lead the reader to a conclusion about which indicators are problematic and require further attention.
As Few notes in his “Eenie, Meenie, Minie, Moe” article, color is not an effective means for visually encoding quantitative values. Splitting the time scale into months is a meaningful improvement from quarters, but it is difficult to interpret much regarding trends over time. This dashboard does not readily show the degree of deviation from acceptable bounds. It fails to readily show how individual data points are related to one another, unless a threshold is crossed. It does not facilitate comparison between different indicators. Importantly, all dashboard functionality collapses when this is printed out on the available black and white printers for stakeholders to reference.
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If I use Few’s definition, ‘A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance’ (Dashboard Confusion, Stephen Few), I would say the Mpilo Hospital “adapted maternity dashboard’ tool is not a dashboard.
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Although the ‘WHO Maternity Dashboard’ does include some color coding to help the reader draw conclusions, this appears to be more of a report rather than aligning with Few’s definition of a dashboard. This ‘dashboard’ does not clearly allow the user to monitor information at a glance and may be better presented in graphs focusing on each performance measure to clearly identify trends. The dashboard also includes blank columns where either historically information or upcoming months of data is not included. This should be left out of the monthly until the data is available to present to the reader.
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The WHO Maternity Dashboard is undoubtedly a vast improvement from what was done prior to this intervention. The execution, however, could be improved greatly. According to the Alexander textbook, dashboards should be more visual, with “at a glance” views. This could have been achieved possibly by using line graphs of each area measured by month. This way, practitioners can easily see how their data is trending and quickly know if they are hitting target metrics in each area. Individual areas in need of improvement can also be listed out as a reminder for practitioners to follow a certain protocol that may lead to more favorable outcomes for their patients and their children.
I work in healthcare and we use similar graphs to measure our own outcomes. Each department has its own measures that they follow monthly, each on a separate dashboard with a line graph. Colored arrows adjacent to the graph indicate whether target is being met, similar to the color coding shown within the WHO dashboard. It makes it very simple to look at and to understand how each area of the hospital is performing in key areas.
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Based on Stephen Few’s definition of a dashboard, the Mpilo Central Hospital’s maternity dashboard display could be considered a primitive version of a dashboard. While it is certainly a vast improvement compared to the paper-based system previously in place, there are areas of opportunity. The performance measures have been narrowed down to a single “at-a-glance” page with stoplight indicators. However, it is difficult to detect and interpret trends with the inclusion of so many numbers. It would be helpful if only the year totals were displayed with their indicators in relation to the targets. The monthly data could then be included as drill-down graphical information on a separate page. This would allow the hospital to see how close or far away they are from targets on a monthly basis.
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I agree with others who have suggested that the WHO maternity dashboard at the Mpilo Central Hospital meets Stephen Few’s definition of a dashboard but could be substantially improved to support decision-making in the hospital. The WHO dashboard does display important information on a single screen to achieve the objective of improving maternal and perinatal clinical outcomes. The information displayed could be considered a “high-level summary” in that it shows change over time for a number of indicators without providing additional details about how and why any changes might have occurred. The table does concisely display the data, but this display format is not optimal for quick decision-making, as others have pointed out. Compared to, for example, widgets or metric boxes that display key indicators individually, the table used in this dashboard takes longer to visually process, because it requires that the user visually move between the left side of the screen (where the performance measures are listed) and the right side of the screen, which displays the most recent month of data. Additionally, the authors noted that the dashboard was printed, but that no color printer was available at the hospital; the use of gray-scale would potentially make it even more challenging for the user to make quick assessments at a glance. The tool therefore might not meet Few’s “customized” criterion in that the visual elements were designed without consideration of limitations of the local environment, such as the lack of color printing.
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While the WHO Maternity Dashboard does fit Few’s criteria of data being “consolidated and arranged on a single screen,” and utilizes various colors to visually indicate status of an outcome towards the target, there are multiple factors that make me lean towards not qualifying this example as a dashboard. First, Alexander noted that a dashboard should focus on data related to the goal. As stated in the WHO article, the “goal” of this dashboard was to present effectiveness of the PROMPT training, with a secondary focus on identifying adverse outcomes in perinatal trends. The maternity “dashboard” displayed does not specify training outcomes versus overall trends that may or may not be related to the training. The “dashboard” displayed tends to fit Alexander’s definition of a report, as it is a table that contains raw data. This table is more of an intermediary step to a dashboard, which has the potential to be translated into graphical visuals that will allow for conclusions to be drawn “at a glance.”
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Although the WHO local maternity dashboard at the Mpilo Central Hospital does meet some components of Stephen Few’s definition of a dashboard, it appears to be more closely aligned with the definition a report than a dashboard. The WHO “dashboard” does display important information, in the form of a high-level summary, on a single screen and uses a red–amber–green, traffic-light coding system to alert users to changes in the frequency of selected parameters. However, this information is not visually displayed so that the user can easily monitor these metrics at a glance, which Few notes as an essential component of a dashboard. Furthermore, this color-coding system is lost when printed, since the Mpilo Central Hospital has no color-printing, eliminating the feature of the “dashboard” that visually alerted the user to changes in key performance indicators. Overall, the use of a table to display numerous metrics makes this information difficult to review, process, and draw meaningful conclusions quickly. This tool could certainly be optimized by displaying this information graphically or with the use of metric boxes, for example.
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The WHO Maternity Dashboard does meet the definition of a dashboard as it includes Key Performance Indicators (KPIs) for clinicians who spearheaded the dashboard, it can be easily gauged with the use of the ambulatory color-coded system and it is/was maintained and updated on a monthly/at least monthly basis. In my experience, most dashboards in their initial stage does not have the desired outcomes for all stake-holders, but the beauty of dashboards is that they can be improved upon in time. This also comes with the possibility of overcomplicating or making them more complex with too much data to meet the needs of all stakeholders and thus takes time to hone indicators down to a happy medium.
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To echo other course participants, the WHO maternity dashboard at the Mpilo Central Hospital meets Stephen Few’s definition of a dashboard. By demonstrating trends using a traffic-light coding system it provides a level of data accessibility highlighting areas of “opportunity” and “success”. Although the WHO maternal dashboard meets Few’s definition of a dashboard, it also meets Alexander’s definition of a report; a table containing raw data. Improvements including data visualizations, summary statistics, and a key/legend with definitions of the color-coding thresholds would tremendously contribute to the readability of this dashboard. A dashboard should ultimately provide an opportunity for the reader to quickly identify trends and, as accessible, refer to larger datasets for in-depth analyses.
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