Can AI Actually Fix the Medical Claims Denial Mess?
Jon Jaroska - CTO - Red Sky Health
If you've ever been involved in healthcare billing, you know this much is true: claim denials are brutal.
They're a drain on time, staff, and revenue. We're talking billions of dollars lost every year—not because the care was bad, but because of small administrative failures. A code gets mistyped. A required authorization is missing. A payer changes its rules with zero notice.
The worst part? Most of it was preventable. That’s why providers are looking beyond spreadsheets and siloed billing systems—and turning to AI to help clean up the mess.
Denials Are Expensive. Here's the Data:
Around 10% of all claims are denied on the first try
Two-thirds of denied claims are never appealed or resubmitted
Each appeal costs $25 to $100+ in staff time
Denials slow down cash flow and burn out billing teams
This isn't just a back-office annoyance—it's a full-blown revenue problem.
What Red Sky Health's AI Actually Does
At Red Sky Health, we built an AI platform called Daniel to take on this exact challenge. And we didn’t build it to automate the same old process—we built it to fundamentally rethink it.
Here’s how Daniel works:
✔ Real-Time Denial Detection and Correction
Daniel uses machine learning and AI to scan every denial as it comes in. It compares the claim against a massive set of historical data and known denial patterns to flag potential issues. When it finds a problem, it doesn’t just point it out—it fixes it on the spot in real time, with a documented accuracy of over 95%.
✔ Intelligent Resubmission
If a claim has already been denied, Daniel can automatically apply the necessary correction and resubmit it directly to the payer. That means no waiting for a human to chase it down or rework it manually. The entire process is programmatic and built for speed.
✔ Built to Learn and Improve
Daniel’s models get smarter the more they’re used. With every new denial reason, every successful fix, and every payer response, the system refines itself to become more precise and more proactive.
What Daniel Doesn’t Do (Yet)
We’re not going to pretend AI can do everything. Here’s what Daniel doesn't do—at least not today:
It doesn't auto-generate full appeal letters from scratch
It doesn't integrate directly with EMRs to pull full clinical narratives
It doesn’t claim to “understand” payer policies in the way a human compliance officer might
And that’s fine—because what it does do is eliminate thousands of preventable errors before they cost you money.
What’s Next?
We’re working on deeper integration with clearinghouses. The goal? Push corrections even earlier in the pipeline—right where claims are exchanged, validated, and transmitted. If we can intercept denials before they happen at that level, we can cut them off at the source.
Bottom Line
If you're still managing denials the old way—with legacy systems, disconnected teams, and too much manual work—you're fighting with one hand tied behind your back. AI isn't some future promise. It's working now. It’s recovering revenue now. And it’s helping real healthcare orgs get paid faster, with less stress and more accuracy.
We're not just reacting to denials anymore. With Daniel, we're engineering them out of the system.
