HEALTHCARE
B2B AND B2C PRODUCT
AI APPLICATION
Improving Clinician Productivity with
AI Powered
Patient Notes
Designing a 0-to-1 AI-assisted documentation mobile platform to streamline clinical workflows, improving productivity and increase adoption
PLATFORM
Web and mobile app
DURATION
12 Weeks
MY ROLE
Product designer
WHAT WE ACHIEVED
Notes generated in 3 months
Downloads in pilot
MAU in pilot across customers
THE PROBLEM
Physicians are drowning
in documentation.
Patients are paying the price.
in documentation.
Patients are paying the price.
Clinical documentation takes up to 2 hours of a physician's day time stolen directly from patient care. Clinicians manually transcribe notes after every visit, switching between the EHR, their phones, and paper pads.
The result: delayed notes, missed details, and burnout.
The result: delayed notes, missed details, and burnout.
No In-Visit
Documentation
Physicians couldn't document during consultations without breaking eye contact and losing patient trust. Conversations are recorded or physically transcribed
Unstructured, Inconsistent Notes
Since Notes are manually created, they tend to be inconsistent and unstructured. Clinicians were creating notes based on rough recordings and memory
High Cognitive Load on Care Managers
Clinicians were spending 40% extra time beyond regular shift on documentation tasks causing increased errors and fatigue.
Two users, one
broken workflow
broken workflow
Discovery interviews with 16 Clinicians and revealed fundamentally different pain points but one shared frustration: documentation was eating their clinical time.
Jim - Clinician
8 patients/day • 90+ min post visit documentations
"I became a Clinician to treat patients, not to type. By the time I finish notes at 9 PM, I've already forgotten half of what was said."
Wants structured SOAP output
Needs hands-free, ambient capture during visits
Can't afford errors in clinical documentation
Doesn't trust technology that adds steps, not removes them
Cerry - Care manager
Manages documentation for 3–4 physicians daily
"I'm always playing catch-up. The physician finishes the visit, and then I have 20 minutes to reconstruct everything from a voice memo and my memory."
Needs a reliable source of truth from every visit
Wants to review and edit AI-generated notes quickly
Needs QR-based session start — no manual entry
Requires offline-capable tool for poor connectivity areas
From voice to
verified note phases
verified note phases
Applied Lean UX across 2 sprint cycles starting with Discovery and assumptions, building the minimum to test them, and iterating only on what evidence demanded.
Discovery & Assumption
After interviewing clinical experts, we deduced the following assumptions:
Mobile application to introduce flexibility
Create ready to review notes that should be editable.
Assumption Mapping
Problem Statement
Build the MVP (Think → Make)
Built the thinnest version that could test our core assumption:
That ambient capture + auto-structured output would reduce documentation
Time without disrupting the visit. No full design system.
Defined the IA based on user journey map to make sure the flow integrates smoothly in
cinician's documentation workflow
5-Screen MVP
Lo-Fi Prototype
Validate & Kill Assumptions (Check)
Round 1 testing with Clinical experts and other stakeholders revealed that we need a more
secure log in that does not entirely depend on organisation SSo. Options to edit notes
Usability Testing
Assumption Validation
Final Iteration and Handoff
With MVP's tested we designed high-fi designs . Annotated edge cases : poor audio environments,
interrupted sessions, offline mode, EHR sync failures.
UAT ran with 4 customer clinicians across 2 sites before production release.
Dev Handoff
UAT
AMBIENT SCRIBING
One tap to start. One structured note when you're done.
The scribing app removes all friction from clinical documentation, giving physicians ambient capture during visits and care managers a clean, editable SOAP note the moment the session ends.
Scribing Interface
Since Notes are manually created, they tend to be inconsistent and unstructured. Clinicians were creating notes based on rough recordings and memory
Auto Patient Recall
The app automatically identifies the patient when opened within the EHR system.
Language selection
Clinicians can select from multiple languages to ensure the application is localized.
AI GENERATED NOTES
Auto-generated notes with AI suggestions
SOAP Note Interface
Automated note generation
The note is automatically generated when the session ends.
Editable Notes
Users can tap on the note to edit it, similar to any standard note-taking application.
AI Suggestions
The AI system suggests medications and therapies that clinicians can add to the note.
IMPACT
What changed after pilot
Measured across the pilot cohort of all institutes over the first 4 weeks .during pilot
Saved per clinician per day
Reduction in post-visit documentation time
Note accuracy achieved
LEARNINGS
Reflections & Next steps
Voice-first doesn't mean voice-only
Clinicians trusted the tool more when they had a visible indicator that recording was active. A silent, invisible AI felt untrustworthy in clinical settings. Adding a subtle waveform animation during capture — and a clear "listening" state — increased session completion rates by 30% in testing.
The real user isn't always in the room
We designed for physicians, but the product's daily power user was the care managers who went along with patients for side activities and helped clinicians manager produced SOAP notes
What's next: EHR deep integration + ambient multi visit mode
The next version should support passive listening across multiple consults in a shift with the physician only reviewing, not triggering. A direct EHR write API would eliminate the care manager review step entirely for low complexity visits.
Creating agentic workflow for care managers
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Creating agentic workflow for care managers
