Project Two:Doctor Search & Selection
Problem
Choosing where to get medical care is one of the most important healthcare decisions consumers make. But in the age of information abundance, this decision is not simple. No matter the tools someone uses to navigate their search for care, they are faced with a tough task — how do I find the right doctor for me? I was tasked with exploring what factors matter most when people (in this case members of a specific insurance company) are searching for and selecting a doctor?
Process
Generative Research: In-depth interviews and a large, quantitative survey to understand what factors matter at what point in the decision-making process
Design: Synthesis, data analysis including inferential statistics (SPSS), idea gen workshop, and design working sessions to redesign the care search experience
Evaluative Research: Concept testing with members to identify utility, comprehension, or usability issues with redesigned care search experience
Results
Concept and prototype were validated by users
Resulted in substantial enhancements to the care search experience for members (including ability to review doctors) and changes to information architecture
Surfaced issue with provider data inaccuracy that became a 2025 company priority
Reflection:
To help stakeholders apply learnings, leverage theoretical models that already exist and use them to frame post-study working sessions. This project applied Google’s “Messy Middle” model to explain the doctor search and selection process.
Surveys are the most misused and misunderstood tool in UX research. Writing a good survey is part art, part science.
Note: This study is featured on the Oscar Tech blog too - read more about it here!