AR Aging Benchmarks by Specialty: How Do You Compare?

"Days in AR" is one of the most cited revenue cycle metrics, and one of the most misleading when used without specialty context. A days-in-AR figure that signals trouble in primary care might be perfectly normal in oncology. Here's how to benchmark correctly.

Why a Single AR Benchmark Doesn't Work

Days in AR (total accounts receivable divided by average daily charges) is influenced heavily by claim complexity, payer mix, and the typical dollar value per claim. A specialty with high-dollar claims that require extensive documentation, prior authorization, medical necessity review, multi-line drug billing, will naturally carry higher days-in-AR than a specialty with simple, high-volume, low-dollar visits, even if both practices are managed equally well.

MGMA's annual cost and revenue surveys consistently show meaningful variation in AR metrics across specialties, and practices that benchmark themselves against an overall "healthcare industry average", often cited as 30-40 days, frequently draw the wrong conclusions, either complacent when they shouldn't be or alarmed when their numbers are actually typical for their specialty.

Specialty-Level Benchmark Ranges

While exact figures vary by source year and practice size, the following ranges reflect commonly cited benchmarks for total days in AR (current through 120+ days, net of credit balances) among well-performing practices:

• Oncology / Hematology: 45-55 days. Driven by high claim values, prior authorization requirements for drugs, and complex multi-payer coordination for patients often covered by both primary insurance and supplemental plans.
• Cardiology: 35-45 days. Procedure-heavy billing with device and implant components adds documentation complexity relative to E/M-only specialties.
• Orthopedics / Surgical specialties: 35-45 days. Global surgical packages and bundled payment considerations extend the claim lifecycle.
• Rheumatology / Infusion-heavy specialties: 40-50 days. Similar drivers to oncology, high-cost biologics, prior auth, and buy-and-bill complexity.
• Primary care / Family medicine: 25-35 days. Lower claim complexity and dollar value generally support faster adjudication.
• Behavioral health: 30-40 days, though this varies significantly with payer mix, practices with high Medicaid volume often see longer cycles due to state-specific processing timelines.

These ranges represent "well-performing" benchmarks, practices significantly above these ranges for their specialty typically have identifiable process issues (slow charge entry, high denial rates, ineffective follow-up), while practices significantly below may be writing off balances prematurely rather than truly collecting faster.

The Aging Bucket Distribution Matters More Than the Total

Two practices can have identical total days-in-AR figures with very different underlying health. A practice with 80% of AR in the 0-30 day bucket and 5% over 120 days is in a fundamentally different position than one with 50% in 0-30 days and 20% over 120 days, even if the blended average looks similar.

A healthy aging distribution for most specialties looks roughly like: 55-65% in 0-30 days, 15-20% in 31-60 days, 8-12% in 61-90 days, 5-8% in 91-120 days, and under 10% over 120 days. Once the over-120-day bucket exceeds 15% of total AR, the probability of eventual collection drops sharply, claims this old are disproportionately likely to require write-off, and a growing over-120 bucket is often the earliest warning sign of a systemic follow-up gap.

Benchmarking by Payer Category

Total days-in-AR also masks payer-mix effects. Medicare claims typically adjudicate within 14-30 days under prompt payment requirements, while commercial payers vary from 15 to 45 days depending on the payer and claim complexity, and Medicaid timelines vary substantially by state, some states process claims within 30 days, others take 60-90 days as standard.

A practice with a high Medicaid concentration will show higher blended days-in-AR than an otherwise identical practice with predominantly commercial payers, not due to any operational difference, but due to payer processing speed. Segmenting AR aging by payer category, rather than relying on a single blended figure, reveals whether a high overall number reflects payer mix or genuine follow-up gaps.

Using Benchmarks Effectively

The most useful application of AR benchmarks isn't a single comparison against an industry number, it's establishing a specialty- and payer-mix-adjusted baseline for your own practice, then tracking trend over time. A practice trending from 42 to 48 days over six months, even if 48 is "within range" for its specialty, likely has a developing issue worth investigating before it becomes a larger problem.

Combining days-in-AR with denial rate, clean claim rate, and net collection rate gives a fuller picture: a practice can have acceptable days-in-AR while masking a denial rate problem if denied claims are quickly written off rather than worked, a pattern that looks fine in AR aging but represents real revenue loss.