When AI in Revenue Cycle Management Is No Longer Optional

Hi and happy Wednesday,

We just released something important, and if you're watching denials climb or cash flow slow, you'll want to see it.

Initial claim denials have hovered near 12% since 2016. Hospitals are still spending close to $20B per year appealing claims they thought were clean the first time. 

Patient collection rates have slipped to around 48%, leading to more balances being written off at the back end, even after the claim is paid.

Behind those numbers are familiar issues: 

• Inconsistent front-end capture, 

• Gaps in documentation, and 

• Manual checks that can't keep up with payer rules that change every few weeks.

This week, we're sharing our newest healthcare report: "Transforming Revenue Cycle Management: State of AI in Healthcare RCM."

It's a practical guide built for CFOs, practice owners, and RCM leaders who need to understand:

Where preventable denials actually start, across scheduling, intake, coding, and billing, and how much revenue is sitting in those gaps

What the numbers mean for your organization, using current benchmarks for initial denial rates, clean-claim rates, and patient collections to size the real financial impact

Which workflow changes deliver results by introducing AI into specific steps rather than "automating everything" and hoping it works

The aim is to give CFOs, practice owners, and RCM leaders a concise, evidence-based starting point for discussions about denials, cash flow, and where to adjust processes next.

We’re signing off for the rest of the month. Wishing you happy holidays and a great start to the new year. We’ll return in January with new insights.

Dino Gane-Palmer