1. Empowering patients
The starting point for our project was the challenge of “Empowering Patients” on the Hackathon. The challenge emphasized the empowerment of patients in a healthcare system where there is a lack of focus on the patient experience.

Therefore, we were asked to create an AI-driven solution that would:
- Simplify the complexity of medical terminology and turn it into everyday language.
- Help patients assess the trustworthiness of medical information they find on the internet.
- Support accessibility and multi-language support, especially for languages other than English.
During the initial discovery process, we reviewed existing material and interviewed one of the mentors present in the hackathon, a medical researcher working with rare disease patients. In our chat with him, it became clear that patients who were most likely to struggle with the understanding of their disease were rare disease patients. Thus, we decided to narrow the scope of the project by placing our focus on patients suffering from rare diseases, refining our problem statement to the following:
How might we empower rare disease patients?
2. My research process

I kicked off the research process with secondary research, looking at scientific articles, as well as research reports from organizations such as IDEO on rare disease patients, patient experience and empowerment.

We needed to better understand the daily struggles of rare disease patients. As this project took place in the middle of the Covid-19 pandemic with no access to hospitals or patients, it was impossible to conduct a field or ethnography study to observe rare disease patients. Therefore, I decided to take a digital approach to ethnography: I extracted posts from three rare disease Facebook groups, where patients and their parents found a community to discuss their struggles.

Simultaneously, I conducted a competitive analysis of existing tools tailored for rare disease patients to be able to identify where the users pain points were not being addressed and where we could bring something new and competitive to the market.

To create categories and codes for the analysis, I analysed a limited sample of posts from three Facebook groups. Based on the categories and codes derived from the initial reading, I assigned each post with at least one code and category.

Next, I presented the findings of my research to my stakeholders, and we held a workshop to brainstorm the best solution to the struggles rare disease patients were facing. After a divergent thinking practice, we decided on an app that combines symptom tracking, real-time meetings, and fact-checked resources.

Finally, I created paper prototypes for the UX design of the app. The UI designer of our group took my input to create a prototype of our CaReD app on Figma. After a quick-and-dirty heuristic analysis to improve the usability of the product, we had an initial version of the product.