AI & Automation

The technology behind
98.4% clean claims

Rcmaxis uses AI-powered claim scrubbing, predictive denial prevention, automated eligibility verification, and real-time AR monitoring — so your billers spend time recovering revenue, not fixing preventable errors.

98.4%
First-pass clean claim rate
<18
Days in AR (industry avg: 35+)
2.1%
Denial rate (industry avg: 8–12%)
96.7%
Net collection rate
How it works

Automation at every stage of the claim lifecycle

Each step in our revenue cycle has a layer of automation running underneath — catching errors before they reach payers, not after.

01

Eligibility check

72 hours before appointment — automated benefit verification across all active payers.

Automated
02

Charge capture

Encounters flow from your EHR. AI flags undercoded visits and missing diagnoses before coding.

AI-assisted
03

Claim scrubbing

Every claim runs through 4,000+ payer-specific edits and denial prediction before submission.

AI-powered
04

Submission & tracking

Claims submitted electronically. 277CA acknowledgements monitored in real time — every batch confirmed.

Automated
05

Payment posting

ERA files posted automatically. Underpayments flagged against contracted rates. Variances queued for review.

Automated
06

AR monitoring

AI models score every open claim by collection probability and urgency — billers work the highest-value claims first.

AI-prioritized
Denial prediction — live claim queue
4%
Risk
CPT 99214 — Aetna — Dr. Patel
Diagnosis supported · Modifier present · Auth on file
Auto-submit
41%
Risk
CPT 27447 — UnitedHealth — Dr. Sharma
Missing modifier 22 · Global period conflict detected
Biller review
78%
Risk
CPT 90837 — BCBS — Dr. Chen
Prior auth expired · Payer requires auth for 53+ min sessions
Auth required
7%
Risk
CPT 45378 — Cigna — Dr. Rivera
Screening diagnosis confirmed · No prior auth required
Auto-submit
Predictive denial prevention

We flag high-risk claims before they leave your practice

Every claim in your queue is scored by our denial prediction model — trained on millions of payer decisions across 40+ specialties. High-risk claims are flagged for human review before submission, not after rejection.

4,000+ payer-specific editing rules applied before submission
Prior auth status checked automatically against payer requirements
Modifier conflicts, global period violations, and bundling issues caught pre-submission
Low-risk clean claims auto-submitted — billers review only flagged claims
Result: 2.1% denial rate vs 8–12% industry average
Eligibility verification — today's schedule
Johnson, M. · 9:00 AMVerified 2h ago
Active — Aetna PPODeductible: $1,200 metCopay: $35
Williams, T. · 10:30 AMVerified 2h ago
Active — BCBSDeductible: $400 remainingCoinsurance: 20%
Garcia, R. · 11:15 AMVerified 2h ago
Plan changed — verify coverageOld policy ID on file
Chen, L. · 2:00 PMVerified 2h ago
Active — UnitedHealthMental health carve-out: OptumAuth on file
Automated eligibility verification

Every patient's coverage confirmed before they arrive

Our system runs real-time eligibility checks 72 hours before every scheduled appointment — automatically, without staff doing manual portal lookups. Coverage details, deductible balances, and copay amounts are populated directly into your PM system.

Checks run automatically 72 hours before each appointment
Policy changes, lapses, and carve-outs flagged for front desk staff
Deductible and out-of-pocket balances pre-populated for accurate patient collections
Behavioral health carve-outs and benefit limits identified automatically
Result: Eliminates 35% of front-end denial root causes
Claim scrubber — batch results
CLM-2024-08841Clean — Ready
CPT 97110 × 3 units · Modifier GP · KX attached · Diagnosis linked
CLM-2024-08842Warning — Review
Possible undercoding: 99213 submitted — MDM complexity supports 99214 for this payer
CLM-2024-08843Auto-corrected
Modifier 25 added automatically — same-day E/M with procedure detected
CLM-2024-08844Clean — Ready
CPT 45378 · Screening diagnosis Z12.11 confirmed · No auth required for this payer
CLM-2024-08845Warning — Review
Units exceed medical necessity threshold for CPT 97140 — documentation review recommended
Intelligent claim scrubbing

4,000+ editing rules — and it learns from every denial

Our claim scrubber runs every charge through a complete library of payer-specific editing rules — checking for missing modifiers, diagnosis pointer errors, bundling violations, and coding opportunities before any claim reaches a clearinghouse.

Common modifiers auto-corrected (25, 59, GT, 95, GP, GN) based on claim context
Undercoding alerts — when submitted E/M level is below what documentation supports
NCCI bundling edits applied before submission — not after a denial
Denial feedback loops — every returned denial updates scrubber rules for that payer
Result: 98.4% first-pass clean claim rate
AR aging monitorLive
0–30 days
82%
31–60 days
11%
61–90 days
5%
90+ days
2%
Avg days in AR16.4 days
Claims flagged for follow-up14 claims
Timely filing risk3 claims — escalated
Real-time AR monitoring

Every open claim scored by collection probability

Instead of working claims in date order, our AI ranks your entire open AR by recovery probability, dollar value, and timely filing urgency. Billers always work the claims most likely to move — and the ones most at risk of becoming unrecoverable.

AI scores every open claim by payer response likelihood and deadline urgency
Claims approaching timely filing limits automatically escalated to senior billers
Payer non-response alerts triggered at 15 days — before claims age past the actionable window
Underpayments auto-flagged when ERA posts below contracted rate
Result: Average 16.4 days in AR — industry average is 35+
Full capability overview

Every automation layer, explained

Six interconnected systems — each one eliminating a specific revenue leakage point in the claim lifecycle.

Automated eligibility verification

Real-time benefit checks 72 hours before every appointment. No manual portal lookups. Coverage, deductibles, and copays pre-populated in your PM system.

Eliminates 35% of front-end denials

AI-powered claim scrubbing

4,000+ payer-specific edits applied before every submission. Modifier errors, bundling conflicts, and diagnosis pointer issues caught before they reach a payer.

98.4% first-pass clean claim rate

Predictive denial prevention

ML model trained on millions of payer decisions scores every claim's denial probability before submission. High-risk claims held for biller review — not rejected and appealed.

2.1% denial rate vs 8–12% industry avg

Automated payment posting

ERA files processed automatically — payments posted to correct claims, contractual adjustments applied, and patient balances calculated without manual posting.

Same-day ERA posting for all payers

AI-prioritized AR follow-up

Open AR ranked by recovery probability and timely filing urgency — not by date. Billers always work the highest-value, most-recoverable claims first.

Avg 16.4 days in AR

Underpayment detection

Every adjudicated claim compared against your contracted fee schedule automatically. Underpayments flagged and disputed — a frequently overlooked revenue source.

Avg 3–5% additional collections recovered
The right balance

AI handles the volume. Our billers handle the judgment.

Automation makes our billers more effective — it doesn't replace them. Every complex denial, clinical appeal, and payer negotiation requires human expertise that no algorithm can replicate.

How we split the work

Automation runs on 100% of claims. Human billers focus on the cases that require expertise, relationships, and judgment.

Automation handles
Real-time eligibility verification before every appointment
Claim scrubbing — 4,000+ edits applied in seconds per claim
Denial risk scoring — every claim gets a probability score before submission
ERA payment posting — matched and posted same day for 95%+ of payers
Underpayment detection — every EOB compared to contracted rates automatically
AR aging alerts — timely filing escalations triggered at 15 days
Common modifier corrections added automatically where logic is clear
277CA monitoring — every submitted claim tracked for payer acknowledgement
Our billers handle
Flagged high-risk claims — review and correct before submission
Clinical appeals — peer-to-peer escalations requiring physician-level arguments
Complex payer negotiations — underpayments, contract disputes, rate challenges
Prior authorization management — when payer portals require human follow-up
Medical necessity documentation — pulling clinical records and building appeal packages
Live payer calls — for aged or disputed claims requiring direct contact
Coding review — undercoding alerts reviewed by certified coders before action
Client reporting — account managers interpret data and provide strategic guidance
The difference it makes

What changes when automation is doing the heavy lifting

The same billing volume — but errors caught before they cost you money.

Without automation

Manual billing — where revenue leaks

Eligibility lapses discovered at checkout — patient leaves without paying
Missing modifier 25 — E/M denied as bundled with procedure
Undercoded visits — revenue left on the table visit after visit
ERA posted days late — cash flow delayed while payments sit unposted
Claims worked FIFO — oldest first, regardless of recovery probability
Underpayments accepted — no systematic comparison to contracted rates
With Rcmaxis automation

Every revenue leakage point covered

Eligibility verified 72h before appointment — issues fixed before the patient arrives
Modifier 25 added automatically when same-day E/M + procedure is detected
Undercoding alerts flag visits where documentation supports a higher level
ERA posted same day — cash in your account faster, AR aging stays low
AI ranks open AR by recovery probability — billers work highest-value claims first
Every ERA compared to fee schedule — underpayments disputed systematically

See our automation in action — free

Book a 30-minute demo. We'll show you exactly how our claim scrubber, denial prediction, and AR prioritization work using your actual specialty and payer mix as the example.

Get Your Free Revenue Audit Book a Demo Call
(function(){ var toggle = document.getElementById('nav-toggle'); var mobile = document.getElementById('nav-mobile'); if(toggle && mobile){ toggle.addEventListener('click', function(){ mobile.classList.toggle('open'); toggle.classList.toggle('open'); }); } })();