Outbound AI
Claims Console
Problem
Outbound AI is an AI-powered platform that uses virtual agents to automate claims and billing workflows across the healthcare revenue cycle. Its core product, the Claims Console, supports high-volume, detail-heavy work, where teams need to quickly scan, filter, and act on large datasets. As usage scaled, there was an opportunity to improve how information was structured and how workflows like filtering, assignment, and claim review were supported.
Solution
I redesigned key areas of the claims console to better support high-volume workflows, streamlining four key workflows—filtering, batch actions, assignment, and claim review—to improve clarity, speed, and scalability.
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My Role
Lead Product Designer & Researcher
🙌🏼
The Team
1 Designer / Researcher
4 Engineers
2 Product Owners
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Our Timeline
1 year
My Work
Over the course of my time at Outbound AI, I designed solutions to improve claims workflows, informed by research across interviews, card sorting, and observational studies. These four highlights showcase some of my most impactful work.
1️⃣
Claims page filters
Redesigned filtering to make it faster and easier to surface relevant claims.
2️⃣
Batch details drawer
Improved hierarchy and structure to support faster batch decision-making.
3️⃣
Claim assignment flow
Streamlined assignment workflows with bulk actions to support work at scale.
4️⃣
Claim details page
Simplified the layout to reduce cognitive load and improve decision-making.
Each of these is broken down further below, from problem to solution.
1. Claims page filters
Filtering claims was inefficient due to limited search, buried key controls, and default AG Grid constraints that made it difficult to quickly surface relevant data. I redesigned the filtering experience to improve visibility, flexibility, and speed, making it easier to find and act on relevant claims.
This snippet shows a new and improved filtering section with close-up of the updated date selection levers.
2. Batch details drawer
The batch details drawer lacked clear hierarchy and consistent visual structure, making it difficult to understand and act on grouped claims. I introduced clearer hierarchy and structured layouts to improve scanability and support faster batch decision-making.
Before
After
3.Claim assignment flow
Assignment workflows were limited and manual, preventing users from efficiently assigning claims. I designed a more flexible assignment flow, enabling bulk actions and reducing friction in managing claim ownership.
First, I redesigned the claim management experience to allow users to assign or reassign single claims directly within the context of their work, removing the need to navigate away or rely on limited self-assignment options.
Next, I introduced bulk assignment from the claims table, allowing users to select multiple claims and assign or reassign them in just a few clicks, making it significantly faster to manage work at scale.
When this shipped, we heard directly from users that assignment went from a multi-step bottleneck to a fast, reliable action, freeing teams to focus on higher value work.
4. Claim details page
The experience of reviewing claim details was fragmented and overwhelming, with excessive navigation and competing information that slowed down decision-making. I simplified the layout and consolidated key information to reduce cognitive load and support faster, more focused decision-making.
Below are three of the most important claim details page sections I redesigned.
1. I improved the claim snapshot and supporting panels to make key information easier to scan, and introduced accordions to organize dense call data and reduce visual clutter.
2. I consolidated multiple call views into a single experience using a dropdown, and simplified the layout so recordings and transcripts are accessible without competing with primary claim information.
3. I refined the layout and hierarchy of call notes to support quick entry and review without competing with other information on the page.
Calls
I consolidated multiple call views into a single experience using a dropdown, and simplified the layout so recordings and transcripts are accessible without competing with primary claim information.
Here is a visual of the legacy UI, indicating some of the competing visuals and hierarchy addressed above.
Although the full claim details page redesign was not released end-to-end, core features shipped incrementally and contributed to meaningful improvements in how users navigate and manage claims.
My Process
Learning about our users
Through interviews and observational studies, we spoke with a range of stakeholders across the revenue cycle. These included roles like billing leads, A/R specialists, and operational leaders, each interacting with claims workflows in different ways but all managing high volumes of information and time-sensitive work.
From insights to solutions
Each research initiative translated directly into early design exploration. Using synthesized insights from Dovetail, I sketched concepts to improve key workflows and explore directions that could better support users at scale.
The Outcome
Over the course of my time at Outbound AI, I helped make claims workflows faster, clearer, and easier to manage at scale. These outcomes reflect that work.
Source: internal AutoCheck processing analysis and operational estimates (Outbound AI, 2024)
Together, this work made it easier for teams to move faster, reduce manual effort, and focus on the work that matters most: bringing greater clarity and efficiency to how claims are managed at scale.