Waiting Time In Emergency/Healthcare In Ontario
Introduction & Rational
After immigrating to Canada and going through several doctor visits, I have realized that the waiting time tends to be quite long. I would find myself waiting for hours before being seen or called. Therefore, for this project, I chose to discuss the theme of waiting time in emergency/healthcare in Ontario. Looking at the data, from 2014-2025, various reports and publications indicate that waiting time in emergency departments prior to getting an initial assessment is considerably high, negatively impacting patients’ physical, emotional, and mental well being. On average, patients seem to be waiting for approximately 2 to 3 hours before receiving particular treatment or guidance.
Behind the numbers, statistics, charts as well as graphs presented are patients whose lives are affected, shaped by distressing experiences. Thus, my goal in this project is to demonstrate multiple data storytelling techniques, illustrate this issue, and ensure to highlight the human aspect.
Data, Methods & Techniques
To complete this project, I explored several reports and publications that analyzed and discussed the issue of emergency waiting times in Ontario. “Value-For-Money Audit: Emergency Department”, “The Common Quality Agenda 2017: Measuring Up 2017”, “Emergency Department Return Visit Quality Program: Annual Report 2024” reports as well as “Canadians Are Waiting Too Long In The Emergency Room” publication illustrated the waiting time between 2014 and 2025, which I then compiled into a table, shown in Table 1.
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The visual methods used include a sticky-based ideation, to lay out my ideas and the different aspects involved, as well as a line graph to illustrate the trend in the waiting times over the years. A storyboard was then developed to further highlight the human aspect.
Visualization Storytelling Methods
Iteration 1: Sticky-Based Ideation
For my first iteration, I chose to use Miro to visually present and map the story of waiting time in Ontario’s emergency/healthcare system, demonstrating the different aspects, including; theme, character (human element), data, and visual design ideas.
Figure 1: Iteration 1 Sticky-Based Ideation
Iteration 2: Data Collection
In the second iteration, the process began with data collection. This includes researching the average time patients spend waiting to be seen/called, as well as creating a line chart to illustrate the ER waiting time across the years (2014-2025), which I have created using the data provided in reports and publications I explored. Moreover, I was able to research additional information regarding the reasoning behind the long waiting time, this includes; increased demand for patient care, shortage of healthcare staff, limited resources and seasonal and outbreak pressure. As well as how it impacts patients including longer waits result in capacity issues, and reduce patient satisfaction and condition worsening & higher calculations.
While developing this iteration, I realized that although it demonstrates the data, it did not convey my goal of highlighting the human aspect that I wanted to communicate.
Figure 2: Average Waiting Time (Hours) Graph
Iteration 3: Storyboard
For my third iteration, keeping the human element in mind, I have decided to use a storyboard technique to better illustrate the human experience behind the waiting time. I drew various panels, presenting the timeline of the story, indicating the setting at which a patient may be at. I have decided to proceed with this idea, using myself as an example, hence the wavy hair and glasses. The human-centred design is evident in this iteration, addressing not only the preliminary concern but also how it affects the lives involved.
Figure 3: Iteration 3 Storyboard
Panel 1: I started to experience severe knee pain and thus decided to visit the emergency department for a check-up.
Panel 2: It has been 2 hours since I arrived (time shown on the clock), and I have not been called.
I am feeling distressed, and my pain has worsened.
Panel 3: I started observing the room, and when I realized there were still several people waiting, that is where I wondered if they had been waiting longer than I had.
Panel 4: After 3 hours of waiting, I was finally called to see a specialist for an initial assessment.
Panel 5: A meeting is taking place to review the trend over the years, as well as discuss the reasons behind the long wait times and their affect on patients' well being.
Audience
This project targets healthcare professionals, executives and other decision makers, those who are able to make changes/improvements to the system. It also includes patients, who are directly affected by the long waiting times and go through unpleasant experiences.
Conclusion
In conclusion, it is evident that longer wait times not only affect the efficiency of the healthcare system but also the well-being of patients. What I hope for the audience to take away is to view this issue from a human perspective and not just as statistics.