The Three Levers that Keep Revenue Moving

A simple dashboard view that shows where cash is slowing, and how to fix it fast

Author

Dino Gane-Palmer
August 19, 2025

Hi and happy Tuesday,

Last month, I sat with the CFO of a large multi-specialty group. 

“We’re doing more visits, our clean-claim rate is high, but cash still feels slow,” she said.

We pulled their AR data, and within minutes, the story was clear: 

Side-by-side, three metrics revealed the single biggest drag on cash flow.

The three levers

These three metrics act like pressure points in your revenue cycle, small changes here create big shifts in cash flow.

First-pass yield: Every % drop = more rework, staff hours, and delays.
A 2-point gain freed $400K for one 15-site group.

Median days to payment: Cut 3 days on $2M/month = $200K more cash in hand.
Faster payments = payroll security + growth flexibility.
One multi-specialty practice shortened median days to payment from 22 to 18.

Denial-to-resolution time: Faster resolution = less AR >30 days, lower bad-debt risk.
One group cut resolution time from 15 to 8 days and reduced AR >30 by 25%.

Why this matters

Short answer: Because cash velocity determines how much working capital you have. For example:

  • Improving first-pass yield from 88% to 92% on 10,000 claims/month can put $144K in the bank sooner (based on $360 average claim value).

  • Cutting denial-to-resolution time from 15 to 8 days can reduce AR over 30 days by 20%–30% in many specialties.

Your simple dashboard

Three tiles, updated weekly:

  • Tile 1: First-pass yield % (target: 90%+)

  • Tile 2: Median days to payment (target: payer-specific, but generally <20 days)

  • Tile 3: Denial-to-resolution days (target: <10 days)

Update these from your billing or analytics platform each week. A single-page view will tell you if cash is moving faster or slower, and where to focus.

Want to try how?

Use de-identified claims data. Before you start  make sure your dataset includes: 

Claim status (to identify which claims were paid in full on the first submission)

Service date and Payment date (to calculate days to payment)

Denial date and Resubmission date (to measure denial-to-resolution time)

Payer ID (to spot payer-specific trends)

Once you have this information paste the data set into your favorite conversational AI Chatbot and use these example prompts to calculate the three metrics:

1. First-pass yield

“From this claims dataset, calculate the percentage of claims paid in full on first submission for each month. Flag months below 90%.”

2. Median days to payment

“Using this dataset with service_date and payment_date, calculate the median days to payment per payer and overall.”

3. Denial-to-resolution time

“From this denial log, calculate the median days from denial_date to resubmission_date. Highlight any payers above 10 days.”

Even running this once on a single week of data will show you where cash is moving quickly, and where it’s getting stuck.

P.S. Last week we asked: Out of every 100 claims you submit, how many get paid without a single denial?

  • 18% said 95+ claims | 27% said 90–94 | 32% said 80–89 | 15% said fewer than 80 | 8% not sure

Most teams are falling short of the 95%+ clean claim benchmark, which means there’s still a lot of cash being left on the table.

You can also get a quick ROI check with our free calculator to see how much revenue cleaner claims could bring back.

Calculate your ROI for FREE

Next week, I’ll cover a simple weekly check that uncovers underpayments, recovers lost dollars, and prevents repeat shortfalls.

See you next Tuesday,
Dino Gane-Palmer

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Dino Gane-Palmer
[email protected]

About the Author

Dino Gane-Palmer is the founder of Auxee and CEO of PreScouter, an Inc. 5000–recognized innovation consultancy that helps Fortune 500 companies and global organizations capitalize on new markets and emerging technologies. He launched PreScouter while earning his MBA at Kellogg and later founded Auxee to help teams use AI to tackle complex, research-heavy workflows. His work has supported decisions at some of the world’s leading healthcare, manufacturing, and consumer brands. Dino is also the author of the best-selling book Do More With Less: The AI Playbook, a practical guide to applying AI where it matters most.