AR Days Benchmarks for Orthopaedic Practices: What "Good" Looks Like in 2026

For most orthopaedic group practices, a healthy days in accounts receivable (AR) benchmark sits in the low-to-mid 30s, with high-performing groups often operating under 30 and anything drifting past 45 signaling a revenue cycle that needs attention. AR days measures how long, on average, it takes to collect payment after a service is billed, and it is one of the clearest single indicators of revenue cycle health that a CFO or COO can watch.

But the headline number hides as much as it reveals. This benchmark guide explains what good looks like in 2026, how to calculate AR days correctly, what pulls the number in the wrong direction, and how to bring a creeping AR back under control.

How to Calculate Days in AR

Days in AR is calculated by dividing your total accounts receivable by your average daily charges. The standard approach takes total AR, divides by total gross charges over a defined period (commonly the trailing three months), and multiplies by the number of days in that period. The result is the average number of days a dollar sits in receivables before it is collected.

The calculation is simple; the interpretation is not. A practice can post a respectable aggregate AR days figure while hiding a serious problem in a specific payer or aging bucket. That is why the aggregate number should always be read alongside its components.

What “Good” Looks Like: 2026 Benchmarks

Benchmarking bodies such as the Medical Group Management Association (MGMA) publish revenue cycle metrics that give practices external reference points, and orthopaedics generally targets days in AR in the low-to-mid 30s. Strong groups push under 30. Equally important is the aging distribution: a common benchmark is keeping the share of AR over 90 days in the single digits to low double digits as a percentage of total AR. A practice with acceptable average AR days but a swelling over-90 bucket is often masking denials and appeals that are quietly aging out toward write-off.

Treat these figures as directional rather than absolute. Payer mix, surgical volume, and subspecialty composition all shift the realistic target, so the most useful benchmark is a blend of external reference and your own historical trend.

Why AR Days Creep Up

Rising AR days rarely has a single cause; it is usually the cumulative effect of upstream problems. Denials are the most common culprit. Every denied claim restarts the collection clock and adds rework. Slow or incomplete prior authorization pushes cases and payments later. Coding errors and documentation gaps generate rejections that bounce claims back before they are ever adjudicated. Undercoding depresses the value collected per case even when the days look fine. And thin or high-turnover billing staff means follow-up on aging claims slips, letting receivables drift into older buckets.

The pattern to notice is that AR days is a downstream symptom. You do not fix it by working AR harder at the back end; you fix it by preventing the denials, rejections, and coding errors that create the aging in the first place.

How to Bring AR Days Back Down

Start by segmenting. Break AR down by payer and by aging bucket to find where the days actually live, because the fix for a commercial-payer denial backlog is different from the fix for slow patient collections. Attack clean claim rate next, since first-pass accuracy is the highest-leverage lever on AR - a claim that is coded and documented correctly the first time simply does not age.

Tighten the denial and appeal loop so denials are worked quickly and, more importantly, prevented systematically. Shorten prior authorization cycle time so cases and their payments are not delayed at the front end. And ensure follow-up on aging claims is consistent rather than dependent on whichever staff member has capacity that week.

Each of these levers connects back to the same root cause: accuracy and speed at the point of coding and submission. That is why practices increasingly treat AR days as a coding-quality problem, not just a collections problem.

The Coding-to-Collections Connection

The link between coding quality and AR days is direct. When codes, modifiers, and documentation are correct before submission, clean claim rate rises, denials fall, and receivables age slower, so AR days compress almost mechanically. This is where orthopaedic-specific automation earns its place in the revenue cycle.

Maia’s AutoCoder generates and populates accurate CPT and ICD-10 codes with the right modifiers and justification before a human coder finalizes the claim, and Maia’s Insights surface the performance trends that let leaders see where AR is aging and why.

Frequently Asked Questions

What is a good days-in-AR benchmark for an orthopaedic practice in 2026?

Most orthopaedic groups target days in AR in the low-to-mid 30s, with high performers operating under 30. Read the figure alongside your aging distribution, aiming to keep AR over 90 days as a small percentage of total AR.

How do I calculate days in AR?

Divide total accounts receivable by average daily charges. A common method takes total AR divided by gross charges over the trailing three months, multiplied by the number of days in that period, to get the average days a dollar sits in receivables.

Why are my AR days rising even though collections seem busy?

Rising AR days usually reflects upstream problems (denials, slow prior authorization, coding  errors, and inconsistent follow-up) that create aging faster than back-end collections can clear it. The durable fix is preventing those errors, not just working AR harder.

What is the fastest lever to reduce AR days?

Improving clean claim rate. A claim that is coded and documented correctly on the first pass does not get denied or rejected and therefore does not age, which compresses AR days more reliably than any back-end effort.

How does AI coding affect AR days?

By improving first-pass coding accuracy and reducing denials, AI coding slows the rate at which receivables age. Cleaner claims collect faster, so AR days fall as a downstream effect of better coding quality.

See how Maia’s AutoCoder helps handle this automatically for orthopaedic practices. Book a demo at usemaia.com.