Embarrassing mistakes I made trying to prove social care roi (don't do these)
Over the last 8 months I've been working on a model to prove the value of non-claims based care.
This is basically a story about a single spreadsheet.
Not a fancy one. No macros. No AI. Just rows, columns, and some math meant to answer a simple question:
“Does this care program save money?”
I built it myself. Carefully. It was clean. Conservative. Cited. Built to quantify non-claims based care.
I was trying to prove what so many people in healthcare already know:
Helping people early costs less than reacting too late.
After reworking, pressure testing, overhauling the whole thing & starting over several times,
I finally sent my model in for professional review last month.
To the real gatekeepers: the actuaries, the people who determine risk for insurance companies, Medicaid plans, and government budgets.
I wasn't great with math, so my stomach was in knots over whether it would hold up against the real pressure.
But to my ultimate surprise:
The math didn’t fail.
But it also wasn’t enough.
The verdict after months of work:
“This is a solid start.”
What I built made sense.
It was even accurate directionally. But that wasn’t the standard.
I hadn’t built something that finance people could trust without me in the room.
What I Learned About Healthcare Funding (That Nobody Tells You)
You’d think funding in healthcare works like this:
But it really works like this:
Even if your outcomes are incredible. Even if your story is airtight.
If your math doesn’t match the system’s modeling norms, your care might not get funded.
Here are the mistakes I made:
1. I didn't embed the proof in the file.
I had research, yes. But I didn’t link the source logic directly into the model. So when reviewers opened it, they saw numbers but not why those numbers existed.
Though I had the right sources, the proper citations, I left it out of the thing that mattered the most. So in the end it held up like "trust me, bro" logic.
👉🏽 Why did I make this one critical, freshman english class flunkie mistake?
Because,
2. I assumed I’d be in the room to explain it.
I was still thinking like a visionary.
To me, my spreadsheet existed to support the bigger story.
I did what so many good programs do when they face scrutiny.
I treated my own model like it was support material.
3. I measured individuals, not programs.
I ran 10k simulations, thinking that was enough to yield a credible output.
10,000 individual simulations ≠ reliable program-level insight.
So even though it looked accurate, it didn't answer the real question: “How reliable is this at the program level?”
4. I used a normal distribution for healthcare costs.
I later learned this is a common outsider mistake. Healthcare costs are not bell curves.
They’re wild and lopsided. Of course.
I literally laughed when it was read back to me, I basically created a model where people could have NEGATIVE emergency room visits and $400 bills.
Expectation vs Reality:
What This Spreadsheet Taught Me
Your model may be grounded in truth. You may have a solid logic layer. You may even have stellar outcomes. But If your work isn’t formatted in the right financial language, it won’t be heard , let alone funded.
Here's What I’m Doing Now:
Version 1: I built the entire model myself with citations, a passable logic layer, and a vision to model social care.
Version 2: I broke it down by service line, stress-tested every assumption, and rebuilt the logic in actuarial-friendly format.
Version 3: I’m submitting it for re-review. Same firm. Same standards. New math.
See the evolution? That part matters. 🌱
As the audience got more technical, the model has to get more rigorous.
Your business case can’t outgrow your math.
What I Actually Got Right
For all its flaws, I still built something fast enough for real conversations.
✔ I accounted for service overlap, not just stacked savings.
✔ I designed for toggles, scenarios, and real-world variability.
✔ I got real feedback from the actual gatekeepers: the actuaries.
✔ I was honest about what the model could and couldn’t do.
✔ And maybe the biggest success here: I invented a brand-new framework, from scratch, with no finance degree and it made sense to people who matter.
If you’re building, funding, or defending non-claims based care and you’ve ever had to make the math speak louder than the mission , I’d love to connect.
I’m pressure-testing Version 3 of this model right now, and I’m sharing insights as I go.
DM me if you want a preview, or follow this newsletter to watch it unfold.