Lindsey·Frein
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Medlaunch Case Study
Reducing complexity with a unified QMS platform
Overview
I led the design of Quality Core, expanding our product suite from three to four offerings while partnering with product, engineering, and data teams to align business goals, user needs, and scalability. We launched the core experience in two weeks and, over the next two months, delivered a full ecosystem of features including event reporting, risk management, effectiveness monitoring, quality planning, quality objectives, and AI integration.
Working across 20+ collaborators, we expanded the platform by 25%, introduced AI-powered workflows, and reduced cognitive load by creating a unified system experience.
ROLE
Lead UX Designer (1 of 2)
RESPONSIBILITIES
UX & UI Design
Product Planning
Design System
End to end Design
COLLABORATORS
20+ team members:
UX Design, Product, Business,
Data, & Engineering.
TIMELINE
2 Week MVP Sprint
2 Months Total
Spring 2026
Goals
- Unify complexity into a single, navigable experience across all audit activities and accreditation workflows.
- Ship fast and scale sustainably: core experience in two weeks, full ecosystem in two months.
- Drive platform growth through AI-augmented workflows that surface critical information and reduce manual effort.
The Challenge
USER PROBLEM
Healthcare quality teams had no unified system to track audit activities, workflows, and compliance across internal hospital operations and external accreditor requirements, creating cognitive overload, siloed information, and compliance risk.
SOLUTION
Quality Core centralizes quality management into one scalable platform with AI-powered workflows, giving teams full visibility across all audit activity and the confidence to manage accreditation at scale.
Competitive Analysis
Delve Compliance
Compliance automation
PRIMARY USE CASE
SOC 2, HIPAA, and GDPR certification for tech companies.
AI CAPABILITIES
Automated evidence collection, infrastructure scanning, code-level vulnerability detection on every push.
HEALTHCARE FIT
HIPAA compliance only: focused on data security certification, not clinical or accreditation workflows.
STRENGTHS
Purpose-built for compliance automation
Fast onboarding. Audit-ready in ~1 week
Real-time infrastructure monitoring
GAPS
No DNV / accreditor workflow support
No audit event reporting or risk management modules
No unified view across hospital operations
Not designed for quality objectives or effectiveness monitoring
Jira
Project management
PRIMARY USE CASE
Software development tracking, agile project management, issue and ticket management.
AI CAPABILITIES
Atlassian Intelligence: summarization, automation suggestions, NL search, but must be disabled in HIPAA-eligible accounts.
HEALTHCARE FIT
Configurable for compliance workflows with significant setup; HIPAA-eligible only on Standard/Premium tiers with BAA signed.
STRENGTHS
Highly flexible and extensible via plugins
Familiar interface, widely adopted
Strong audit trail and traceability
GAPS
Not built for healthcare accreditation, requires heavy customization
AI features incompatible with HIPAA-compliant configuration
No accreditor-facing (DNV) workflow visibility
Cognitive load of generic tool adapted to complex domain
Quality Core
Our approach
PRIMARY USE CASE
End-to-end quality management and accreditation for healthcare organizations.
AI CAPABILITIES
AI-powered workflows embedded natively. Surfacing insights, automating task routing, reducing manual overhead across all modules.
HEALTHCARE FIT
Purpose-built for hospital quality teams and accreditors. Covers both internal operations and DNV-facing workflows in one system.
DIFFERENTIATORS
Unified view: internal + accreditor activity in one platform
Domain-specific modules: event reporting, risk, quality planning, effectiveness monitoring
AI built for compliance, not disabled by it
Scalable architecture shipped in 2 weeks, full ecosystem in 2 months
Emerging Themes
INFORMATION HIERARCHY
Users need critical information immediately.
Jira: Displays status, assignee, labels, and priority directly in the list view.
Delve: Highlights compliance status and risk indicators.
Takeaway: Surface key information upfront = reduce clicks.
WORKFLOW VISIBILITY
SCALABILTY
Rapid Iteration
Week 1–2
MVP: Quality Management Page
Medlaunch is scaling rapidly and users need a workflow overview page NOW. We ship the Quality Management System Tracking Backlog in 2 weeks with visibility as the key tenant of design. Scalability, RBAC, and AI agent integration are also centrifugal to decision-making.
V1: QMS Tracking Backlog
V2: Quality Management
V3: Quality Management via Quality Core
FOCUS
- Jira-style table
- Clean ticket side panel
- Customization and filtering
ISSUE
- Ticket side panel lacks space for future expansion and feels DE-emphasized
- How to integrate events?
SOLUTION
- Side panel expands to full screen
- Introduce tabbed pagination consistent with design system
Scalable Design Patterns for Module Expansion
Weeks 3–8
Quality Core Suite of 7 Products
Each module shared many of the same list and panel patterns established in Quality Management, but surfaced distinct design constraints around user type, data density, and workflow context.
Tables Across Quality Core
Quality Management/All
Quality Management/Events
My Events
Survey Readiness
Progress Indicators as a Visual Staple
Quality Planning
Effectiveness Monitoring
Survey Readiness/Framework Progress
Survey Readiness/Overview Page
Survey Readiness/Policies Tab
Survey Readiness Table
Tabbed Pagination for Sub-Navigation
Quality Management Page
Events Page
Survey Readiness Page
AI Workflow Integration
AI was designed in from day one, not bolted on. Clara routes tasks, surfaces insights, and reduces manual entry across every module.
RISK MANAGEMENT MODULE
What it does: AI reviews submissions, identifies potential risks and opportunities, and pre-populates key fields for review.
How it helps users : Reduces manual triage and data entry while improving consistency and review speed.
EFFECTIVENESS MONITORING MODULE
What it does: AI continuously monitors configured criteria and surfaces relevant activities, trends, and recurring events.
What it does: Provides ongoing visibility into performance indicators and eliminates manual monitoring.
INCIDENT FEEDBACK MODULE
What it does: AI generates incident correspondence letters and emails that users can edit directly or refine through conversational prompts.
How it helps: Streamlines and accelerates regulatory communication workflows while maintaining user control over final messaging.
Impact
Expanded Flagship Portfolio
+25%
4 → 5 Core Products
Full Quality Core Suite
+7
new sub-products
MVP Shipped
2 Weeks
Full Sprint
Key Outcomes
Delivered a unified platform replacing fragmented tools across audit, event reporting, risk, and accreditation workflows.
MVP shipped in 2 weeks, full suite of 7 products delivered in 2 months. Shared design system made each subsequent module faster to build than the last.
Architected to support AI-native workflows from: automated risk identification, suggested actions, and real-time monitoring.
Reflection
One of my biggest takeaways was the value of designing for scale from the outset. As Quality Core expanded to support additional modules, role-based permissions, and more complex data relationships, several foundational experiences required iteration to accommodate evolving requirements. While these refinements ultimately strengthened the product, investing more time in long-term architecture and growth scenarios upfront could have reduced redesign effort and accelerated future development.
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