DATABASE

OF US



Researched, ideated, and designed user centered features for Database of Us



Overview


I conducted user interviews in order to further understand the needs and pain points of people of marginalized identities within their medical diagnosis journey. I sourced users from multiple platforms, aided in the interview guide development, and synthesized the data into digestible visuals. I conducted rapid ideation and delivered data backed low fidelity feature suggestions.


Disciplines
UX Research, Research Synthesis, Data Analysis

Teammates
N/A

Timeline
07/21 - 08/21


Background


The Database of Us (Underrepresented Symptomatology) is a collaborative online portal documenting under-publicised illness presentations in Black, Indigenous and People of Colour (BIPOC) and marginalised genders. It is built on crowdsourced symptom information in the form of text and/or images from anonymous submitters around the world, and will serve both as a diagnostic aid for clinicians and as a self-advocacy tool for these groups.


 

Problem


BIPOC and people of marginalized genders have lower access to quality healthcare, poorer general health and worse disease outcomes than the wider population. This is in part the result of systemic clinical bias, which generates lower medical awareness of illness presentations in BIPOC, and lower public awareness of BIPOC-specific symptoms both within and outside of BIPOC communities. The aim of Database of Us is to work with BIPOC worldwide to create a uniquely inclusive health database. However in order to start, we needed to gain a deep understanding of the medical struggles of people of marginalized identities.


I had the opportunity to work with Imogen Malpas, the founder of Database of US, to conduct research to further understand how a database can aid our user base in their medical journey, specifically in their medical diagnosis journey.I was tasked specifically to source and conduct interviews with people of marginalized identities as my form of research.
To guide the overall project, I followed this problem statement:

“How might we design a comprehensive database that will generate awareness for different illnesses within the BIPOC community, be a resource and a form of support for BIPOC, and overall will be helpful to BIPOC in their medical journey?”
I followed this problem statement through my research:

“How might we understand the pain points of BIPOC during their medical diagnosis process and how might we learn about how we can aid and relieve these pain points?”

Solution Preview

Based on the interviews and data synthesis, I came up with some recommendations for the database.

Diagnosis Suggestor
The internet is filled with misinformation and biased information that factors into a self misdiagnosis. This features allows users to input a list of symptoms along with additional information and will output a unbiased and reliable diagnosis. It will likely use machine learning from internal and external data to conclude an accurate diagnosis.
Community Centers
Sometimes during hard times, a shoulder to lean on is the best form of support. Community centers are online pages that host a group of users, bounded by a particular topic or shared experience. Community centers will include features such as question threads, online and in person resources, access to diverse verified medical professionals, along with a post/resource sharing feature, creating niche communities bounded by medical challenges. It also can act as a forum of questions, creating open discussion and a trove of information.

The Process



Interviews
Before anything, we had to develop our interview guide so we had something standardized to follow. Our questions fell into these categories:





After developing this guide, I needed to source interviewees. Given the fact that our user base was people of marginalized identities and I was tasked to further understand medical diagnoses, I sought to look for people of marginalized identities with medical history. I sourced for interviewees on slack groups, discord channels, and Facebook groups. These groups fell into the following categories:


1. LGBTQ+ centered
2. BIPOC centered
3. UX Research centered
Pain points
Given the research, we compiled some pain points within the medical diagnosis procedure:
Personifying the data
To humanize and represent our data, I developed a few personas to tell a more compelling and empathetic story. I included relevant information about the persona as well as a journey map to effectively display the medical diagnosis process as a user.







Feature ideation
After conducting and synthesizing the research, I moved onto ideating some feature suggestions for the database. I conducted rapid ideation and was left with approximately 8 potential features. To narrow them down, I dove deeper into each feature. I followed the following steps for each one:


1. List features within the features
2. Create a pros and cons chart
3. Create an impact/effort chart (effort was not very highly weighed but was considered)
Database feature suggestions
After conducting and synthesizing the research, I moved onto ideating some feature suggestions for the database. Due to the incredibly short timeline, my suggestions consisted of comprehensive descriptions of the features instead of prototypes. 


isabel zheng
made w <3 from Berkeley, CA