AI Care Navigator addresses a critical gap in healthcare:

73% of patients leave appointments confused, and 45% miss follow-ups. Our team of 3 designers tackled this over 8 weeks, conducting 24 user interviews and 156 survey responses.

The solution provides three core features:

• Plain-language visit summaries that eliminate medical jargon

• AI-generated questions tailored to patient history and concerns

• Personalized care plans with medication tracking and daily tasks

This collaborative project was built using Lovable, a modern web development platform. The full interactive case study showcases our research process, personas, information architecture, wireframes, and final high-fidelity designs.

Problem & Context

Design challenge:
How might we help chronic-care patients understand, prepare, and follow through on their care without needing medical training?

Users & Goals

Primary user
Chronic care patient (e.g., Type 2 diabetes, PCOS, depression), 22–55, digitally literate, often juggling multiple portals (hospital, lab, pharmacy).

User Goals

• See clear, simple explanations of their visit and labs

• Prepare smarter questions before the appointment

• Turn the care plan into small daily/weekly actions

• Feel in control, not lost

Product Goals

• Reduce cognitive overload after visits

• Drive better appointment conversations

• Build trust in AI by keeping users in control of the content

5. Reflection

This project reinforced for me that effective healthcare UX is as much about emotional safety as it is about clean UI. Through testing, I saw that the biggest shift for patients was not just “understanding” their data, but feeling less afraid of it. When users could control how information was explained and move at their own pace, they described appointments as calmer, more focused, and easier to prepare for. That insight now shapes how I design any AI-driven experience: the interface should lower anxiety before it shows off intelligence.

If I were to take AI Care Navigator further, I would focus on deeper integration into real clinical ecosystems. The next steps include connecting with existing patient portals, adding medication tracking and interaction warnings, and designing a dedicated caregiver view so families can support shared care without overwhelming the patient. I would also prioritize multilingual support and partnerships with healthcare systems for structured pilots, allowing us to validate outcomes like appointment preparedness, adherence to care plans, and patient confidence over time.