Enterprise SaaS HealthTech Ops App
I led the design of an enterprise feature to improve efficacy on Fraud, Waste and Abuse FWA investigations.
SaaS/ HealthTech / Enterprise
The Challenge
Manual, Error-Prone Process
Investigators were copying data across multiple systems, where one mistake could cost millions.
Opportunity
A unified hub, eliminating system switching, reducing manual errors, and accelerating case resolution.
My Role & Team
My role
Lead Product Designer
(Strategy & Hands-On)
Team
2 Product Designers,
1 Product Manager,
1 Product Owner,
~15 Engineering,
~2 Data Analysts,
Core Skills
Qualitative research,
Usability testing,
Interaction design,
User interface design,
Team management,
Roadmapping,
Workshop facilitation,
Stakeholder management...
Timeline
12 months
Impact at a Glance
80%
Error Reduction
Estimated reduction in data entry errors
7x
Speed Increase
Data collection: 1 week → 1 day
+25%
Efficiency Gain
Operational efficiency through design system
Research
User Interviews
Gathering qualitative user feedback.
Persona Development
Creating profiles of target users.
AI Analysis
Processing data with machine learning.
Journey Mapping
Visualizing the end-to-end user experience.

Key Challenge: HIPAA regulations prevented direct tool access—we relied on screenshot analysis during video interviews
Adapting to Challenge
  • I conducted "look-over-the-shoulder" interviews. This let us see the user's workflow first-hand.
  • I adapted our research methods to overcome HIPAA constraints. This ensured user privacy.
We uncovered daily frustrations, risks, and "workarounds." These defined the users' process.
Finding 1: Fast, Accurate Case Creation
Fraud detection specialists needed fast, accurate case creation flows.
Finding 2: Seamless Platform for User Groups
Our two user groups needed a seamless platform, less switching between systems and tools.
Finding 3: Clarity in ML Data Reports
Data analysis from ML data reports needs clarity in order to improve adoption among all user groups.
Design Evolution
1
Wireframes
Began with low-fi wireframes to explore broad concepts and align on the initial flow.
2
Usability Testing
Tested interactive prototypes with 10 investigators. Their feedback was direct and invaluable.
3
Pivot: "Too Complex"
Users ignored our first "search" flow. They just wanted a simple 'Create Case' button ✨
4
Final: The Contextual Form
An e-commerce "cart" concept for gathering data tested as the clear and intuitive winner.
First Iterations
A search flow to find duplicate cases before adding and creating new ones
🔎 Key Finding:
Users ignored the first "Search Flow" prototype.
👉 User Need:
Testers wanted a simple "Create Case" button.
The Solution in Action
Unified Platform
All investigation tools in one place—no more system switching
Smart Pre-Fill
Forms auto-populate with relevant report data
Intuitive Flow
Seamless interactions validated through user testing
User validation
I love this! This is what we were looking for.
— Special Investigation Unit User
Iterating and Scaling
Positive feedback led to the introduction of a drawer layout, functioning like an e-shopping cart for data.
User testing confirmed this approach was met with enthusiastic feedback.
The "cart" drawer in action
Continuous Improvement
Scalability of the system
I continuously revised for system scalability as we moved towards an integrated platform—addressing user pain points.
Improving ML reports
Future work will focus on improving ML report clarity, a key user concern (not covered in this case study).
Cross-Functional Collaboration
Our integrated approach brought diverse expertise together, ensuring a comprehensive and user-validated solution from concept to implementation.
The Team
Product Design
Spearheaded user-centered solutions and intuitive interfaces.
Product Management
Defined vision, prioritized features, and ensured business alignment.
Engineering
Built robust, scalable systems for AI/ML functionalities.
Data Analysts
Gave insights which helped the team's understand the data and the system
And many other business stakeholders–FWA and other departments
How we achieve good results as a team:
Team alignment
Led workshops to set priorities and create collaborative roadmap
Design Handover
Detailed annotations and interactive mockups for smooth development
Agile Integration & Issue Tracking
Embedded with teams across US, Ireland, and India
Design System Leadership
Led development of flexible component library for global teams
3 countries
And over 21 people shared visual language across
25%
Estimated operational efficiency increase
Impact at a Glance (Recap)
80%
Error Reduction
Estimated reduction in data entry errors
7x
Speed Increase
Data collection: 1 week → 1 day
+25%
Efficiency Gain
Operational efficiency through design system
Key Learnings & Next Steps
1
Complex Systems Scalability
Designing for scalable, interconnected complex systems.
2
Adapt Research to Constraints
"Look-over-shoulder" interviews overcame HIPAA restrictions
3
Global Collaboration Tool
Design system essential for teams across US, Ireland, and India
What's Next
1
Validate Metrics
Implement analytics to track 80% error reduction
2
Scale Workflow
Integrate next legacy system
3
Enhance AI
Iterate on ML recommendations
Thank You
Let's talk on how I can bring this impact to your team
Raul M. Vicente
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