CHRISTINA GIBSON STUDIO
CHRISTINA GIBSON STUDIO
CURO CASE STUDY INTRODUCTION
CURO
Real-time clinical documentation for EMS and flight care
Curo is a conceptual UX content design case study exploring how real-time, voice-assisted documentation can reduce cognitive load for emergency medical professionals while improving accuracy, continuity of care, and hospital handoffs in regulated healthcare systems.
At a Glance
Context: Emergency and flight medical teams operate in high-pressure environments where documentation is legally required but often completed after care is delivered. Problem: Post-care charting increases cognitive burden, introduces omissions, and creates downstream risk for hospitals and QA teams. Focus: Designing patient-first documentation workflows that capture accurate information as care happens. Approach: Content strategy, information architecture, and ethical AI used to support—not replace—clinical judgment. Outcome: A conceptual system that treats documentation as clinical infrastructure rather than administrative overhead.
My Role
Role: Content Designer & Strategist Focus: Content strategy, UX writing, information architecture, systems thinking Status: Conceptual, research-informed case study I led the end-to-end content and system design, with particular focus on clarity under pressure, workflow alignment across ground and flight care, and responsible use of AI in clinical contexts.
Why "Curo"
From the Latin curo — to care for, to manage, to attend to, to provide for, to cure. The name reflects a shared intention across EMS crews, flight teams, hospital staff, and QA professionals: to care for patients through clarity, accuracy, and continuity—especially when time and attention are limited.
INFORMATION ARCHITECTURE & TAXONOMY
Overview
Designing documentation around clinical moments—not forms Curo’s information architecture and taxonomy were designed to support real-time care delivery in high-pressure environments. Rather than structuring documentation around traditional forms or fields, the system is organized around clinical moments—reflecting how EMS and flight teams actually work under time constraints. The goal was to reduce cognitive load, preserve accuracy, and ensure continuity of care across ground teams, flight crews, hospitals, and QA workflows.
Architectural Approach
The system is built on three core principles: Event-driven structure: Documentation aligns to what’s happening in the moment, not to static chart sections Progressive confirmation: Information moves from draft to reviewed to final, preserving clinician control Context-aware visibility: What’s shown adapts based on care phase, urgency, and role This approach allows documentation to occur in parallel with care—without interrupting it.
Top-Level Information Architecture
The top-level structure mirrors the natural progression of an emergency care encounter: - Active Call - Assessment - Transport - Handoff - Chart Review - QA & Audit Each section represents a distinct phase of care, with content and actions scoped to what is appropriate at that moment.
Care-Stage-Based Taxonomy
Instead of organizing information by clinical form type, content is grouped by care stage: Care stage - Dispatch - Arrival - Assessment - Transport - Transfer - Review - Final This structure supports: - Faster orientation - Reduced decision fatigue - Clear transitions between care phases
Content Type Taxonomy
To balance structured data with clinical nuance, content is classified by type: - Structured data (vitals, timestamps, identifiers) - Narrative notes (free-text clinical observations) - System-generated events (arrival confirmed, transport started) - Clinician-confirmed entries (reviewed and signed information) This distinction allows AI assistance and validation without flattening clinical judgment.
Confidence & Content States
Given the realities of emergency care, the system explicitly tracks confidence and completion states: Confidence level - Confirmed - Estimated - Unknown Content state - Draft - Reviewed - Final Making uncertainty visible reduces downstream risk and supports safer handoffs and QA review.
Handoff-Aware Information Heirarchy
During handoff, the system surfaces: - Time-critical summaries - Unresolved questions or estimates - Changes since last update This ensures hospitals receive usable context, not just raw data.
How IA & Taxonomy Reduce Risk
This structure: - Reduces the need for memory-based reconstruction - Preserves clinician agency and review authority - Improves continuity across ground, flight, hospital, and QA teams - Makes uncertainty explicit instead of implicit - Treats content as part of patient safety infrastructure
Outcome
By aligning information architecture and taxonomy to real-world clinical workflows, Curo reframes documentation as a parallel clinical activity—not an administrative afterthought. The result is a system that supports accuracy, trust, and continuity of care when time and attention are limited.
UX WRITING & MICROCOPY
Overview
Writing for clarity, confirmation, and clinical trust In Curo, UX writing functions as part of the clinical workflow. Language is designed to reduce ambiguity, confirm system state, and support fast, accurate decision-making—without interrupting care or undermining clinician judgment. The guiding principle: Say only what’s necessary, exactly when it’s needed.
UX Writing Principles
Calm and confirmatory Language reassures users that actions were captured without demanding extra attention. Action-oriented, not verbose Microcopy prioritizes clear next steps over explanation. Minimal alerts, high signal Interruptions are used sparingly and only when review or action is required. Clinician authority preserved The system assists, flags, and suggests—but never overrides or decides. Uncertainty is explicit When data is incomplete or estimated, the language makes that visible.
Tone by Context
Active care: neutral, brief, and non-distracting Review moments: clear, directive, and confirmation-focused Errors or gaps: factual, calm, and respectful of clinician expertise Handoff moments: concise summaries with emphasized changes
Microcopy Examples by Workflow Stage
During active care - Designed to confirm system state without pulling attention away. - “Assessment mode active” - “Voice capture on” - “Event recorded” Documentation review Supports accuracy and clinician sign-off. - “Review chart before locking” - “Some details need confirmation” - “Estimated values detected — please review” Handoff - Surfaces what matters most in time-critical moments. “Patient transferred — documentation paused” - “Changes since last update” - “Key details pending confirmation” AI-assisted guidance - AI language is intentionally conservative and transparent. - “We couldn’t confidently capture this information. Please review.” - “This value may be incomplete.” - “Suggested summary — clinician review required.” Errors & edge cases Focused on resolution, not blame. - “Connection lost. Data saved locally.” - “Unable to confirm input. Please review when safe.” - “This entry can’t be finalized yet.”
Microcopy Patterns that Reduce Cognitive Load
To balance structured data with clinical nuance, content is classified by type: - Structured data (vitals, timestamps, identifiers) - Narrative notes (free-text clinical observations) - System-generated events (arrival confirmed, transport started) - Clinician-confirmed entries (reviewed and signed information) This distinction allows AI assistance and validation without flattening clinical judgment.
Outcome
State confirmation instead of success messaging Progressive disclosure instead of instructions upfront Consistent verbs for key actions (Review, Confirm, Lock) Visible content states (Draft → Reviewed → Final) These patterns help clinicians trust the system without second-guessing it.
CONCEPTS & WIREFRAME DIRECTION
Designing for speed, safety, and situational awareness
Curo’s interaction model is intentionally minimal. In emergency and flight care, attention must remain on the patient—not the interface. Every concept prioritizes glanceability, confirmation, and continuity across care phases. The experience is designed to function reliably in real-world conditions: noise, motion, gloves, poor connectivity, and high cognitive load.
Core Interaction Principles
Event-driven, not screen-driven The interface responds to clinical moments rather than forcing navigation through forms. Voice-first, touch-second Voice capture supports hands-free documentation; touch is reserved for confirmation and review. Glanceable confirmation Large, readable indicators confirm system state without requiring interaction. Progressive engagement Active care requires minimal input; deeper review happens only when clinically appropriate.
End-to-End Workflow
Active call - Call assigned and route confirmed - System enters documentation-ready state automatically Assessment - Voice-assisted capture during triage and evaluation - System records events and timestamps without interrupting care Transport - Key updates captured in motion - Hospital communication initiated with structured summaries Handoff - Time-critical details surfaced clearly - Unconfirmed or estimated information flagged Chart review - Clinician reviews, edits, and confirms captured data - Content moves from Draft to Reviewed Finalization & QA - Chart locked after clinician sign-off - QA teams review with clear confidence and state indicators
Interaction Design Considerations
Minimal interaction during care No required typing or multi-step inputs while treating the patient. Large, legible UI elements Designed for quick confirmation at a distance or in motion. Clear mode awareness Clinicians always know whether they are in capture, review, or finalization mode. Resilient by design Supports offline capture with secure local storage and later sync.
Designing for Constraints
The workflow accounts for real-world EMS and flight conditions: - Gloves, motion, and limited visibility - High noise environments affecting voice input - Intermittent or absent connectivity - Rapid transitions between care phases - Coordination across multiple teams and systems - By designing for constraints first, the system remains usable when conditions are least forgiving.
Outcome
The resulting workflow treats documentation as a parallel clinical activity—one that adapts to urgency, preserves accuracy, and supports safe handoffs without demanding extra attention. This approach demonstrates how interaction design, content strategy, and system thinking can reduce risk and cognitive burden in safety-critical environments.
REFLECTION & LEARNINGS
Designing Curo reinforced that in safety-critical environments, content design is inseparable from clinical risk management. Documentation is not an administrative task that happens after care—it is a parallel clinical activity that must adapt to urgency, environment, and uncertainty.
This project sharpened my approach to designing under constraint. Voice-assisted capture, event-based information architecture, and explicit confidence states reduced the need for memory-based reconstruction while preserving clinician authority and review. Rather than aiming for completeness in the moment, the system prioritizes accuracy, traceability, and safe handoffs.
Curo also clarified my stance on ethical AI in healthcare. Automation must be conservative, transparent, and bounded. AI’s role is to assist, flag, and summarize—not to decide. Making uncertainty visible proved just as important as surfacing information.
Key learnings from this work include:
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Documentation is a clinical act, not an administrative afterthought
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Event-driven IA reduces cognitive load and downstream risk
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Explicit content states improve trust and accountability
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Ethical AI requires restraint, transparency, and clinician control
Overall, Curo demonstrates how content strategy, UX writing, and information architecture can function as clinical infrastructure—supporting safer workflows, clearer communication, and more reliable continuity of care in high-pressure environments.