2026 RCM Benchmarks: Where Does Your Practice Stand?

Every healthcare practice tracks revenue cycle metrics, but few know whether their numbers are good, average, or a red flag. Without benchmarks, a 28-day AR might feel acceptable — until you learn that top-performing practices in your specialty collect in under 16 days.

This report presents 2026 RCM benchmarks drawn from aggregated data across Revenue Synergy's client base and publicly available industry sources including MGMA, HFMA, and AAPC. Use these numbers to evaluate where your practice stands and identify the highest-impact areas for improvement.

Overall Industry Benchmarks (All Specialties)

Before diving into specialty-specific data, here are the aggregate benchmarks that apply across healthcare:

Metric	Best-in-Class	Average	Needs Improvement
Days in AR	< 24 days	25-35 days	> 40 days
Clean Claim Rate	> 97%	92-96%	< 90%
Denial Rate	< 4%	5-10%	> 12%
Net Collection Rate	> 96%	91-95%	< 88%
Cost to Collect	< 4%	4-6%	> 7%
First Pass Resolution Rate	> 92%	85-91%	< 80%
Days to Bill (post-encounter)	< 2 days	3-5 days	> 7 days

Benchmarks by Specialty

Revenue cycle performance varies significantly by specialty due to differences in coding complexity, payer mix, authorization requirements, and average charge amounts. Here is how the benchmarks break down for the major specialties:

Primary Care / Family Medicine

Metric	Best-in-Class	Average
Days in AR	14 days	26 days
Denial Rate	3.2%	7.8%
Net Collection Rate	97.1%	93.2%
Clean Claim Rate	98.2%	94.1%

Primary care benefits from relatively straightforward E/M coding, but high patient volume means even small inefficiencies compound quickly. The biggest improvement opportunity is typically eligibility verification — catching coverage changes before the appointment rather than after denial.

Cardiology

Metric	Best-in-Class	Average
Days in AR	16 days	32 days
Denial Rate	3.8%	11.4%
Net Collection Rate	96.5%	89.7%
Clean Claim Rate	97.4%	91.2%

Cardiology has the widest gap between best-in-class and average performance of any specialty. The complexity of procedural coding, LCD compliance requirements, and prior authorization for diagnostic and interventional procedures creates numerous denial opportunities. Practices that invest in cardiology-specific coding expertise consistently outperform those using general billers.

Behavioral Health

Metric	Best-in-Class	Average
Days in AR	17 days	38 days
Denial Rate	4.2%	14.6%
Net Collection Rate	96.8%	84.3%
Clean Claim Rate	97.1%	88.5%

Behavioral health shows the largest gap between best-in-class and average collection rates — nearly 12.5 percentage points. The primary driver is authorization management. Practices with automated auth tracking and proactive concurrent review consistently operate at the top of the benchmark range. Those relying on manual tracking fall dramatically behind.

Orthopedics

Metric	Best-in-Class	Average
Days in AR	15 days	28 days
Denial Rate	3.5%	9.2%
Net Collection Rate	97.2%	91.8%
Clean Claim Rate	98.0%	93.5%

Orthopedic practices that code implants correctly, use proper laterality modifiers, and manage pre-surgical authorization efficiently tend to outperform significantly. The most common under-billing pattern is missing implant-specific HCPCS codes on surgical claims.

Ambulatory Surgery Centers

Metric	Best-in-Class	Average
Days in AR	14 days	30 days
Denial Rate	3.1%	8.7%
Net Collection Rate	97.5%	90.4%
Avg Revenue per Case	Contract max	82% of contract

ASC performance is uniquely driven by per-case coding accuracy. Because each case represents a high-dollar claim, a single coding error can mean thousands in lost reimbursement. Top-performing ASCs have dedicated facility coders who understand implant billing, multi-procedure coding, and surgical modifier stacking.

Hospital Systems (200+ beds)

Metric	Best-in-Class	Average
Days in AR	38 days	52 days
Denial Rate	4.5%	10.8%
Cost to Collect	3.2 cents	5.4 cents
Clean Claim Rate	98.5%	93.8%
Case Mix Index Accuracy	Within 0.02	0.08-0.15 variance

Hospital benchmarks operate on a different scale than physician practices due to the complexity of DRG-based reimbursement, multiple revenue-producing departments, and the volume of secondary and tertiary payer processing. CDI programs are the single largest driver of hospital revenue accuracy, with well-run CDI programs shifting CMI by 0.05-0.15 points.

How to Use These Benchmarks

Benchmarks are only useful if you act on them. Here is a framework for turning these numbers into improvement:

1. Calculate your current metrics. If you do not already track these KPIs monthly, start now. Pull 12 months of data to establish your baseline and identify trends.
2. Identify your biggest gap. Compare each metric to the benchmark for your specialty. The metric with the largest gap between your performance and best-in-class is typically your highest-ROI improvement target.
3. Diagnose the root cause. A high denial rate could be caused by coding errors, authorization failures, eligibility issues, or documentation gaps. Each root cause requires a different intervention.
4. Set 90-day targets. Do not try to reach best-in-class overnight. Set realistic 90-day targets that move you from your current tier to the next. If your denial rate is 14%, aim for 9% in 90 days, then 5% in the next 90.
5. Measure weekly during improvement periods. Monthly reporting is fine for maintenance, but during active improvement initiatives, you need weekly visibility to catch problems early and validate that interventions are working.

Methodology and Data Sources

The benchmarks in this report are derived from three primary sources: Revenue Synergy's aggregated client performance data (340+ providers across 16 specialties), the Medical Group Management Association (MGMA) 2025-2026 cost and revenue surveys, and the Healthcare Financial Management Association (HFMA) revenue cycle benchmarking reports. Best-in-class figures represent the top 10th percentile of performers in each category, while average figures represent the 50th percentile.

All data reflects performance through Q4 2025 and Q1 2026. Benchmarks are updated annually. Individual practice performance will vary based on payer mix, geographic market, practice size, and operational maturity.