Wicked Problem — Public Hospitals in Brazil
As the first official project of UX/UI @Ironhack São Paulo Bootcamp, my group (Vicente Rossi and Jhessyka Freitas) was challenged with a proper wicked problem: public hospitals in Brazil. That’s it, no more big explanations there, we needed to define the problem and to propose a UX/UI solution for public hospitals in Brazil.
Even with our little experience in the field, we knew we had a big challenge in our hands, and we would need a lot of research to come up with the problem and the solution for that. So we decided to use Design Thinking as our method to unravel that wicked problem and come up with the best solution for it. That’s when our journey truly begins, follow me below for our insightful discoveries and final delivery.
1. Empathize | Research, survey, and data analysis
As public health is such a big problem, gathering a lot of data was not hard. Actually, the hard part is to select which data is relevant and which data is not. So we started by understanding the public health scenario in Brazil, how complex and which services it provided for the citizens.
Here are some relevant data about Brazilian public health:
One part of the data that really caught our attention was that most of the problems could be solved on Basic Health Care Units, but what does that mean? The Brazilian health care system is divided into 3 levels, which depends on how complex and urgent the case is. The levels are: basic/preventive, intermediate, and severe. For each level, there is a correspondent health unit type which the patient must go to in each case to get the correct treatment and orientation. So that brought the question: Do people know which health unit to go to in each case? We also learned that hospitals are often crowded and are not able to provide the best care for the patient, who needs to wait a long time to get the assistance he/she is looking for. That’s when we decided we needed to learn from the patients, and we launched a survey with 15 questions that were open for 3 days and got 103 respondents. Added to that we also decided to make 5 in-depth interviews to better understand the reasons behind the data we gathered with the survey.
Some useful insights from the respondents:
After gathering and analyzing that data we were able to build a user journey to help us understand the main pain points of the patient’s journey and at which moment our solution would be more valuable.
2. Define | How might we
After the data analysis and user journey, it was the time to define our problem by identifying one main point of pain which is when the patient is researching for symptoms on the internet. So we decided to make a How Might we, that help us both define the problem but opens for the third part of the project. Here follows our problem statement:
How might we better orient people on the proper use of public health facilities?
3. Ideate | Crazy 8’s, persona, and wireframe
Following up on our project it was time to think about solutions for our problem. In order to comply with the deadline and bring up unusual ideas to light, we decided to make a Crazy 8’s that generated 24 ideas.
Most of the ideas generated had something to do with a smart map or an online pre-screening, so we decided that might be our way to go. But in order to develop an even more focused solution, we decided to create our persona: Joyce Dolores.
With that persona in mind, it was much easier to think about how our solution would look like. As our data showed, 7 in 10 Brazilians rely on public health, so we knew our solution needed to be as accessible as possible. We also learned that people tend to look for symptoms and treatments on the internet when they are having a mild symptom, so that was our action gap, the moment which our solution would have the greater impact. Our briefing left us free to think about a new solution (such as an app or website) or to improve an already existing one, so we decided to go on that way.
With all that in mind, we decided to implement our solution on Google, by improving Google Maps and also adding a pre-screening option for users looking for a more precise orientation on which health facility refers to.
Since our team was already using Miro to design the user journey, we decided to make our wireframes there as well. It worked quite well and helped us to think about the user journey more clearly as Miro is such a simple tool in terms of design options.
4. Prototype | Figma
After the wireframe, we moved to Figma to design our high-fidelity prototype. We did that because Google already has a well-defined visual identity which would help us to have the solution designed the closest possible to what google already looks like without having to work on a completely new visual identity for a new product.
By clicking on the map displayed, the user is taken to google maps on the Health Map function where he can visualize all health facilities available in a geographic area based on his/her location. Each health unity type is identified by a color code, green for the basic health units (UBS), yellow for the mild health units (UPA), and red for the high complexity units (hospitals). By clicking on the unit a card pops at the bottom of the page displaying basic information about the facility, the services provided there, and the contact information.
Added to that solution the user can also go to the pre-screening feature by clicking on the “Find my health unit” button. Clicking there, the user is taken to a test that aims to learn how severe is the user's case in order to inform him about the appropriate health unit for his/her case.
5. Final Thoughts
As for the first project in UX/UI, I was pretty happy with the result. It was surprisingly interesting how we were able to apply the research into functionalities and how much the data-informed our design at the end. Being able to put into practice some knowledge we’ve been learning in class was challenging and exciting at the same time, and we truly believe that this solution is something that has a good potential to become a real functionality in Google Brazil search.
At this time we were not able to run a user test in order to improve the solution.
