Is my medical billing company doing a good job?

Pull five numbers and hold them against the benchmarks. Land in the good ranges and your biller is doing the job. Land outside them, or get no straight answer when you ask, and that is where to look.

Net collection rate matters most. It is what you collected against what you were allowed to collect, after contractual write-offs. Good is 95% or higher. Under 90 means money you earned is not coming in.

Days in A/R tells you how fast claims turn into deposits. Under 35 to 40 is healthy; the median practice sits at 47. The share of your A/R over 90 days old should stay under 15%, because old money is money you are about to lose. Every payer runs a filing and appeal clock, and it does not stop.

Clean claim rate, the share that pays on first submission, should sit near 95%. Denial rate should land between 5 and 10%. Over 10% is worth looking into.

One number rarely tells the whole story, but one habit does. A billing company doing good work pulls an A/R aging report while you are still on the phone. One that stalls, or needs a week, is worth a second look.

None of this means you have to switch. If your numbers are healthy, stay. If they are not, you now know what to ask for. And if you do move, Altair replaces your billing service with AI, backed by our expert in-house billers: we run in parallel through the cutover so no claims drop, work the aged A/R your old biller leaves behind, and show you these numbers by default in a live view.

Talk to us and we will pull your numbers with you.

Common questions

Which number should I check first?

Net collection rate. Good is 95% or better; under 90% means you are collecting less than you earned.

My biller will not produce an A/R aging report.

A billing company should be able to hand it over on demand. If yours cannot, that is the one to press on.

What if my numbers are only a little off?

Small gaps compound. A few points of net collection or an extra week in A/R adds up over a year.

Sources: MGMA 2024 Cost and Revenue Survey, MGMA DataDive, AAFP, HFMA.