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Introduction
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At a glance
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To protect confidential information, some figures are rounded and some screens are recreated. Happy to go deeper in conversation.
Impact
The decision
Required collected more. Optional kept more people in care. I recommended optional.
Relative values · not to scaleWhere it started

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Where it broke
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Examples of discovery artifacts
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And after the bill, paying was a maze: a separate portal, a separate login. {{ journey.reframe }}
9% of hotline calls were people just trying to pay.
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My role
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Alignment
Billing was a major driver of support calls, and leadership made it a core problem. But the problem cut across billing, care, support, data, product, engineering and a vendor, and no one owned it. My first job was to make it visible and turn it into one plan.
The clearest answer came from a workshop. With my PM partner, I asked billing staff, care teams and executives one question: why don’t patients pay? The votes clustered on one answer: they assumed insurance would cover it. Not unwillingness. An expectation we never corrected.
With a copywriter, I turned the research into three rules:
Each broken handoff became a step, in the order members meet them, prioritized with RICE:
ServiceBilled care looked free
01Make billable care explicit
InsuranceMissing or unverified at the visit
02Capture insurance while intent is high
Price and paymentNo estimate, no checkout
03Prepare for a copay, honestly
The maze after the bill
04Surface unpaid balances
Staff chasing and digging
05Improve resolution
We started upstream. Verified insurance made an estimate possible, and an estimate made consent meaningful. I turned the roadmap into the first requirements docs, paired with my mockups.
Three designers worked with me, on billable care, copay collection and check-in research. I scoped and reviewed their work weekly, steered the research, and trained all three on billing, so the domain didn’t live only in my head.
Design vision
The member from the opening had a name in our research: Virtual Vickie. Budget-conscious, remote-first, managing all her care from her phone. For her, a surprise bill isn’t an inconvenience. It breaks her budget.
The insight told me what she needed. Not a better bill, but the truth, earlier.
First, consistent meaning. Billed versus included would become Step 01 of the roadmap. The other three broken handoffs became three rules, written with a copywriter and held on every surface:
Submitted is not verified.
An estimate is not a bill.
A card on file is not consent.
Then, a sequence. Most of the pain showed up after the bill, in systems we didn’t own. But it started with that uncorrected expectation, before the visit, in our own product. So I ordered the work along Vickie’s journey, beginning where the surprise begins. Each step unblocked the next, so we could measure one before building the one after it.
Vickie
Sees billed vs included while choosing care.
Adds or confirms insurance while booking.
Sees an estimate or honest pending state, and picks how to pay.
Finds what she owes in the app.
Gets a clear answer on the first try.
Staff
Fewer “wasn’t this included?” calls.
Coverage on file before the visit.
Copay authorized at the visit, not chased after.
Fewer “where do I pay?” calls.
Balance and bill context in Patient EHR.
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Solution
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Vision / Ideal E2E experience
Alongside the roadmap, I designed the whole journey in one set of mocks. It got the work funded, shaped every step of the roadmap, and became the spec for the balances API.
Concept mocks for the full flow: scan the card, know the price before booking, an honest self-pay estimate, a bill that explains itself, and an AI assistant that answers bill questions before handing off to a person.
Roadmap
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Why it mattered
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Explorations with my team · where to ask
Before
After
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After
v1 · Shipped first
v2 · Upgrade
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Then came the payment question. Billing wanted every copay. The business feared losing bookings. I feared people not getting to care. Instead of arguing, I proposed a test.
First, before any code, I locked the calls we could undo:
Senior leadership approved them, which left one question: required or optional?
New web members got one of three flows.
Both flows cost some completed visits, and required cost a little more. On the numbers alone, it was close. So the numbers didn’t decide it; the principle did. We couldn’t ask for a card before we could tell people what they’d pay. Without a real estimate, “required” isn’t consent. A card on file is not consent. I recommended optional.
Copay collection rose 32 percentage points.
In healthcare, a better payment metric can’t be the only definition of a better experience. People still have to get to care.
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Result. 3 steps and about 2 minutes per patient, rolled out to all staff. I co-drafted the requirements doc and tied it to the cost of collecting each dollar, which came down with the balance view as a major driver.
“One specialist forwarded the design to her whole team, saying it addressed every step we had discussed.”
Future
Process
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Options weighed
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Decision
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Trade-off
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Experiment
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{{ e.a }}copays collected{{ e.b }}bookings completedCopay collection rose 32 points, more members added insurance before the visit on web, and fewer called surprised by a bill.
Balance prep went from 8 steps and 5+ minutes to 3 steps and about 2.
The insurance step traded some bookings for more completed visits. For payment, I chose the gentler option, with completed visits as the guardrail.
Copay on mobile and bills in the app. The bills design became the balances API instead.
One number shouldn’t decide access to care.
Saving members a field created staff tasks.
Not the same input.
Where it landed
You wake up sick and book from your laptop. The visit says it’s billed. Your insurance is verified in seconds, and you see your $25 copay before you confirm. When the bill comes, it’s no surprise.