The Problem
The challenge was not simply presenting data, but aligning digital structure with clinical reasoning. Clinicians synthesize multiple signals, including patient history, diagnostic indicators, and treatment response. Existing tools were static and linear, misaligned with real-world clinical reasoning.
Patient
Healthcare
Provider
Inflammation
Markers
Disorders
Medical History
The Solution
I defined a modular interaction framework that mirrored real-world diagnostic thinking. The interactive patient builder enables clinicians to:
- Start from familiar patient archetypes
- Customize key health inputs
- Instantly see how those inputs affect patient classification and treatment direction
Patient I
Symptom I
Symptom II
Symptom III
Symptom V
Symptom IV
Patient II
Patient III
Patient V
Key UX Moves
The experience was built around four key structural design principles:
- Start with mental modelsThe experience begins with recognizable patient archetypes, reducing cognitive load and accelerating meaningful clinical engagement.
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Patient Type I
Patient Type I
Patient Type III
Patient Type V
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- Progressive disclosure of dataClinical inputs are revealed progressively, allowing exploration without overwhelming cognitive load.
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Symptom Type I Level
Symptom Type II Level
Symptom Type III Level
Symptom Type V Level
59%
360
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3x
- Make the invisible visibleA dynamic 3D model updates in real time, translating abstract data into tangible patient context.
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- Clear outcomes without false certaintyThe system presents likelihood models rather than diagnoses, supporting informed discussion while preserving clinical autonomy.
ISI
PI
Safety
Change Inputs
240
60
mL
%
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Outcome
The patient builder established a scalable interaction framework that translated complex clinical inputs into clear treatment pathways, driving adoption across web platforms, congress materials, and field conversations.
Enabled more
personalized clinical conversations
Shifted conversations from “if” a patient may benefit to “why” they may benefit.
Established a scalable interaction framework used across similar patient tools
Work completed as part of a cross-functional team at a global healthcare agency. Details modified for confidentiality.
