Optispan-Apollo
HIPAA-compliant clinical collaboration platform reducing documentation and coordination friction.
Overview
Optispan is a HIPAA-compliant clinical collaboration platform that helps physicians and clinic staff coordinate care while dramatically reducing documentation burden.
I led 0–1 product design across provider and patient experiences, defining AI-assisted documentation, file ingestion, task and notification systems, and patient profiles; collaborated closely with clinicians and engineering team to establish human-in-the-loop AI workflows and scalable interaction foundations.
Responsibility
Solo Product Designer
Provider and Patient experiences, Desktop + Mobile experience
Focus
Human-in-the-loop AI Workflows, File Ingestion, Tasks/Notifications System
Timeline
2025.6 - 2026.1, 7 months
Collaboration
Project Manager, Product Manager, 5 Engineers, 3 Internal Clinic Users, 3 Customer Users
Impact
90->30 min
Note time reduced
-65% ↓
Manual entry reduced
92%
Customer user satisfaction
Problem - Predesign situation
Fragmented data and tool sprawl break clinical workflows
Current System Problem
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Fragmented data increases clinical risk
Patient information lived across PDFs, Labs, IoT, and manual entry.
Tool sprawl breaks care coordination
linical work flow cross 5+tools (EHR, ZOOM, phone call, email, Heathie)
AI without boundaries erodes trust
Introducing AI into clinical tasks raised concerns around accuracy.
Solution highlight
Designed an end-to-end AI-assisted workflow that integrates documentation, data ingestion, and task coordination while preserving human control and auditability.
SOLUTION highlight/1
A user-owned data foundation from files to clinical context
I identify the friction in backend-supported file handling workflows and proposed a user-facing file system, treating documents as first-class objects with visible AI-generated tags, and review states.
Feature: File Upload
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I structured data from uploaded files powered an 80+ biomarker dashboard and served as a shared foundation for both clinic decision making and AI-assisted documentation.
Feature: Clinic Data-Labs
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SOLUTION highlight/2
Explicit human-in-the-loop boundaries for clinical AI
With structured data as the foundation, I positioned a Clinic AI copilot as a collaborative layer in documentation rather than a decision-maker. By defining explicit human-in-the-loop boundaries and review states, clinicians retained control and accountability while benefiting from meaningful efficiency gains.
AI-generated Clinic Note flow with human-in-loop
Demo
SOLUTION highlight/3
Task and notification system designed to support patient journeys
As the platform was used in real clinic workflows, I observed that care quality often broke down when administrative tasks between clinic staff and patients were delayed and cause confusion.
By mapping patient journeys and key handoff points, I designed a task assignment and notification system that clarified ownership and timing, achieving an 80% task completion rate and enabling more reliable, high-quality care.
Designing an operational signaling system for care coordination
I designed notification rules across task types and states, to reduced noise while ensuring critical tasks were completed before visits.
Diagram: Operational Signaling System
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Designing consistent signals across Web, Mobile, and Email
Consistent Notification Semantics Across Surfaces
Demo
Retrospective
Lessons / Next step
My next step includes:
Scale validation across contexts and surfaces to real patient journeys and mobile touchpoints. Evolve clinician-first patterns into consumer-friendly experiences, reducing cognitive load.
Formalize interaction patterns into a scalable design foundation, to support faster iteration and consistency cross 2 user portals.
lesson 1 - AI interaction design
Trust in AI systems is shaped more by how uncertainty and control are expressed in the interface than by model accuracy alone.
lesson 2 - Data & system design
Design data as a shared interaction layer, made it possible to support visualization, AI reasoning, and task workflows without duplicating complexity.