[01] Context
THE_CONTEXT
Following virtual appointments, veterinarians are legally required to complete DAP (Data, Assessment, Plan) records and provide treatment plans to pet parents.
[02] Problem
THE_CORE_PROBLEM
Vets spend up to 20 minutes manually documenting each appointment, often batching this tedious work at the end of the day.
THE_RIPPLE_EFFECT
Cognitive load from manual DAP compounds across the workflow. Adjust today’s consult count to see how 20 min per visit stacks after hours.
1 block = 1 consult · Blue = charts done after hours
160
min of manual DAP today
2.7h
if batched after 5pm
8
consult slots lost to charting
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Impact 01
Burnout & churn risk
Burnout and platform churn grow when charting is pushed to the end of the day, and vets carry cognitive load that does not stay inside the EMR.
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Impact 02
Delayed prescriptions
When medical records trail the visit, scripts and follow-ups wait, and prescriptions and care plans ship later than they should.
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Impact 03
Client experience
Pet parents feel the gap between a crisp consult and a thin or delayed record; trust in the platform erodes when documentation lags.
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Impact 04
Revenue & ops lag
Every hour of batch charting is an hour not spent on revenue-generating consults, attach, and clean handoffs to eCommerce workflows.
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THE_GOAL
Build a confident, frictionless AI tool that accelerates medical record creation without compromising medical credibility.
[03] Process & Decisions
DISCOVERY
Conducted interviews with 10 veterinarians to gauge baseline trust in AI, uncover current documentation habits, and understand their relationship with the platform.
KEY_INSIGHT_&_PIVOT
Competitor analysis revealed that dumping a massive AI-generated transcript into a single text field creates more cognitive friction. Vets spend more time untangling the text than if they wrote it themselves.
STRATEGIC_DECISION
Pivoted to a modular, section-by-section draft generation. This allows vets to review, compare, and insert only the specific content they need.
PROCESS_FLOW
[04] Solutions
FLEXIBLE_FORMATTING
Recognizing that documentation styles vary wildly, we introduced format toggles: point-form vs. paragraph, abbreviated vs. full wording, and everyday language vs. medical terminology.
MOCK_UP
Format toggles — point-form vs paragraph, abbreviated vs full, medical vs everyday language.
CONTROL_&_REGENERATION
Gave vets the power to regenerate drafts up to two times, ensuring the AI acts as an assistant, not an autonomous dictator.
MOCK_UP
Regenerate flow — section-level refresh with a clear limit on attempts.
TRUST_&_ERROR_PREVENTION
Uncovered a major friction point where vets lost drafts due to accidentally closing tabs. Implemented robust auto-save functionality and a clear "draft" status, dramatically increasing user tolerance and confidence.
MOCK_UP
Auto-save and draft status — visible save state so vets never lose work mid-chart.
BEFORE_vs_AFTER
Drag the slider to compare manual vs. AI-assisted documentation
[05] Impact & Outcomes
By prioritizing user control and seamlessly integrating AI into the natural workflow, we established a scalable foundation for future data inputs and eCommerce integrations. Post-launch, sentiment and accuracy scores read as confidence in the product, while the documented time drop on records reads as completion efficiency. Both are outcomes of the same interaction design bet.
Medical record completion time
20 min
Single quantified report: 20 → 5 min
Average sentiment
0%
Across all 6 veterinarians interviewed
Average accuracy
0%
Across the post-launch interviews with vets
VETERINARIAN_TESTIMONIALS