Days in AR is the number every billing company reports to its clients and benchmarks itself against — the industry target lives under roughly 40-50 days. But the firm managing a dozen practices has the metric scattered across a dozen PM systems, one login at a time. This dashboard pulls receivables from every client into one book-wide view so you can see, on one screen, how much is outstanding, how old it is, and which accounts are dragging the average.
What this dashboard answers
The overview answers the questions an operations lead asks every morning: how much AR is open across the whole book, what's our dollar-weighted days in AR, and how much is aging past 90 and 120 days? Aging buckets (0-30 / 31-60 / 61-90 / 91-120 / 120+) show the shape of the receivables, and a cut by PM system reveals whether one platform's exports or workflows are consistently slower to collect.
The metrics that matter
Weighted days in AR is the headline — and it has to be weighted by dollars, not a simple average, so a handful of large balances don't get washed out by many small ones. AR > 90 Days % is the early-warning line: the share of money that's started aging out. AR > 120 Days $ is the at-risk pile, the dollars closest to a timely-filing write-off. Reading those three together tells you whether the book is healthy or whether a few accounts are quietly going bad.
Why the data is trapped across the systems
Every client practice runs its own instance of athenahealth, AdvancedMD, Tebra/Kareo, eClinicalWorks, or DrChrono, each behind its own login. To answer 'what's my book-wide days in AR,' someone has to sign into each system, run the aging report, export it, and paste it into a master spreadsheet — which is stale the moment it's built. There is no native view that unifies receivables across clients because no single system owns more than one client's data.
How to read it
Start with weighted days in AR against your target, then look at the client matrix: open AR, weighted days, AR>90 %, AR>120 $, and claim count per practice, with the worst aging cells heat-formatted. The bubble scatter of weighted days versus total AR, sized by claim count, surfaces the problem accounts — high days and high dollars in the same client is where to put a biller this week. The sample uses entirely synthetic, anonymized data, so there is no PHI to see the finished layout.
Metrics it tracks
| Metric | What it means |
|---|---|
| Total Outstanding AR $ | Sum of open AR dollars across every client practice. |
| Weighted Days in AR | Dollar-weighted average age of receivables — SUM(AR × days) ÷ SUM(AR), so big balances count for more. |
| AR > 90 Days % | Share of open AR sitting in the 91-120 and 120+ buckets — the receivables aging out. |
| AR > 120 Days $ | Open AR aged past 120 days — the at-risk pile most likely to be written off. |
| Open Claim Count | Count of open claim rows still carrying an unpaid balance. |
| Avg AR Balance per Open Claim | Open AR ÷ open claim count — dollars tied up per outstanding claim. |
Used by: Billing-company owners and RCM operations directors
Frequently asked questions
What is a good days-in-AR number for a billing company?
The widely cited target is under roughly 40-50 days, with high-performing operations pushing lower. Because a billing firm's book mixes specialties and payers, weighted days in AR — dollar-weighted, not a simple average — is the fair way to compare clients and track the whole book over time.
Why weight days in AR by dollars instead of averaging?
A simple average treats a $40 balance and a $3,000 balance equally, which hides where the real money is stuck. Dollar-weighting (SUM of AR × days, divided by SUM of AR) makes the large, slow balances count for what they're worth — the number that actually reflects cash at risk.
Can I build this across multiple clients' PM systems at once?
Yes — that's the point. You export each client's aging report from athenahealth, AdvancedMD, Tebra/Kareo, eClinicalWorks or DrChrono, and the template models them into one book-wide AR view with a client and PM-system slicer. The sample uses synthetic data so you can see the unified shape first.
Build this report on your own data
Clone this RCM / billing companies template — describe it and we’ll generate sample data so you can try it free, or upload your own export. You get a fully modeled, branded Power BI project that opens in Power BI Desktop.
Use this as a template →