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AI medical coding and notes review that codes ICD-10, CPT, HCPCS, and DRG at 95%+ first-pass accuracy

Cut coding-driven denials below 1.5%, lift first-pass yield to 95%+, and shrink coder time per chart from 8-12 minutes to 3-4. FHIR/HL7 native - live in 2-4 weeks.

Coding Accuracy Dashboard

96.2%
First-Pass Yield
-2.9
Days to Bill
-41%
Denial Rate
+29%
Coder Throughput

Why this vs. QuickCode?

QuickCode is the underlying AI coding engine. Coding & Notes Review is the HIM and RCM workflow layer around it: worklists, claim scrub, CDI clarifications, audit trails, and downstream claim handoff.

Problem

You're stuck with slow coder throughput, inconsistent documentation that triggers denials, and opaque QA/audits. It costs days of cash, write-offs from preventable denials, and compliance risk.

Solution

Here's the simple way: Coding & Notes Review uses specialty-trained NLP + clinician-in-the-loop workflows to extract, validate, and normalize codes with >95% precision, so you submit cleaner claims, faster.

What is AI-powered coding and notes review?

AI-powered coding and notes review is the automated analysis of clinical documentation to extract, validate, and suggest medical codes — including ICD-10, CPT, HCPCS, and DRG — before claims are submitted to payors. Traditional coding review requires certified medical coders to manually read physician notes, match diagnoses and procedures to the correct codes, and verify documentation supports the codes selected. This process is slow, error-prone, and contributes to 15-20% of all claim denials. QuickIntell's AI coding and notes review uses natural language processing trained on 50M+ medical documents to analyze clinical notes in seconds, flag under-coded or over-coded encounters, suggest missing diagnoses supported by the documentation, and validate code specificity against payer rules. The system integrates with Epic, Cerner, and other EHR platforms via FHIR and HL7 APIs. Organizations using QuickIntell report 15-25% fewer coding-related denials and 40-60% faster coding turnaround.

The 8-Step Claim Scrub

Before coded work moves into claims processing, every encounter runs through payer-aware edits that catch code-pair conflicts, quantity limits, medical necessity gaps, coverage rules, frequency limits, bundling issues, missing documentation, and modifier logic.

  1. Step 1
    NCCI
  2. Step 2
    MUE
  3. Step 3
    Medical Necessity
  4. Step 4
    LCD/NCD
  5. Step 5
    Frequency
  6. Step 6
    Bundling
  7. Step 7
    Documentation
  8. Step 8
    Modifier
PASS

Clean to release with evidence, edit history, and payer logic attached.

WARN

Can move forward after coder review, note, or manager policy approval.

FAIL

Blocks release until the code, quantity, modifier, or documentation gap is fixed.

Benefits

92%+

First-Pass Coding Acceptance

First-pass coding acceptance within 90 days.

<1.5%

Coding-Driven Denials

Down from a typical 4-7% baseline.

8-12%

Reimbursement Lift

Average reimbursement lift per encounter.

Specialty Coverage

Specialty-tuned prompts, payer rules, and review queues help coding leaders route work by documentation pattern, code family, and reimbursement risk.

Primary care
Cardiology
Orthopedics
Oncology
GI
OB/GYN
Radiology
Anesthesia
ED
Hospitalist
ASC
Behavioral health

How it works

1

Connect

Secure FHIR/API connection to your EHR and document sources (scanned PDFs, HL7, CCD).

2

Configure

Select specialties, payer rules, and confidence thresholds; enable clinician-review gates.

3

Run

NLP + ML convert notes into ICD-10/CPT/HCPCS/DRG with traceable evidence and fix-ups for gaps.

4

Measure

Dashboards show accuracy, denial root causes, coder productivity, and revenue lift.

5

Clarify

CDI workspace sends provider queries, then Reprocess with Answers updates codes without restarting the workflow.

"Denied claims dropped 37% in 60 days and coder throughput rose 28% without adding headcount. Audit trails made physician education painless."
— Revenue Integrity leader, multi-specialty group (~1,400 providers)

Customer name withheld under HIPAA / BAA confidentiality. Outcomes reflect a single deployment and may vary.

Feature Groups

Automate

  • • Dual-engine NLP (structured + unstructured) to propose ICD-10, CPT, HCPCS, DRG with confidence scores.
  • • Payer-aware rules auto-flag missing documentation (laterality, severity, medical necessity, modifiers).

Collaborate

  • • Clinician-in-the-loop review queues with side-by-side note highlights and guideline snippets.
  • • Coder worklists with bulk actions, comments, and assignment SLAs.

Control

  • • Versioned policies & edits (local rules, payer nuances, LCD/NCD, MUE/NCCI) with safe rollbacks.
  • • Role-based approvals and threshold gates that escalate low-confidence cases.

Report

  • • Real-time dashboards: FPY, denial rate, days-to-bill, coder productivity, documentation quality.
  • • Root-cause analytics with trendlines and suggested provider education topics.

Risk Adjustment & HCC Capture

For Medicare Advantage, ACO, and other risk-bearing populations, Coding & Notes Review maps validated ICD-10 codes to HCC v28, applies hierarchy exclusion, and prepares RAF score finalization before submission. Teams that need a dedicated RAF program can connect this workflow to Medicare Advantage operations.

HCC v28 Mapping

Map diagnosis evidence to current CMS-HCC versions, including dual-mapped ICD-10 codes and patient segment checks.

RAF Finalization

Finalize RAF after coder or clinical review, with every accepted, rejected, or suppressed condition logged for audit.

Hierarchy-aware capture

  • • Dominant HCCs suppress lower-severity categories automatically.
  • • CDI queries route ambiguous chronic conditions to providers.
  • • MA, ACO, and ICP teams see recapture gaps before year-end.
  • • Final HCC list and RAF score stay tied to source evidence.

Integrations

Works with Epic, Cerner/Oracle Health, athenahealth, eClinicalWorks, NextGen, MEDITECH, OpenEMR, plus clearinghouses (Availity, Waystar) and data pipes (HL7 v2, FHIR R4, X12 837/835).

What it enables:

  • • Zero-disruption onboarding via FHIR/HL7 interfaces.
  • • Closed-loop learning from 835 remits to improve next-claim precision.
  • • Modifier & DRG alignment to payer rules before submission.
  • • Push-button export of finalized codes to PMS/claim scrubber.

Supported Platforms

Epic
Cerner/Oracle Health
athenahealth
eClinicalWorks
NextGen
MEDITECH
OpenEMR
Availity
Waystar
HL7 v2
FHIR R4
X12 837/835

Pricing

Starter

for clinics & small RCM teams

$2.5k+/mo

Directional platform fee; implementation and usage vary.

  • • Up to 10k encounters/month
  • • Core NLP coding (ICD-10/CPT/HCPCS), basic rules, dashboards
  • • Email support, standard BAA
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Growth

for multi-site groups & mid-market hospitals

$8k+/mo

Directional pricing for larger volumes and advanced workflows.

  • • Up to 100k encounters/month
  • • Adds DRG, advanced payer rules, custom queues, SSO/MFA
  • • API access, priority support, quarterly optimization review
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Scale

health systems & enterprise BPOs

Custom

Typically $25k+/mo with enterprise rollout scope.

  • • 100k+ encounters/month (volume pricing)
  • • Dedicated VPC, private connectors, enterprise security controls
  • • SLA 99.9%, rollout services, bespoke analytics & model tuning
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Security & Compliance

Encryption: AES-256 at rest, TLS 1.2+ in transit • Identity: SSO (SAML/OIDC), MFA • Access: fine-grained RBAC, least-privilege service roles • Audits: immutable event logs, exportable trails • Compliance: HIPAA, SOC 2 Type II controls; signed BAA; data residency options.

Frequently Asked Questions

Benchmarked >95% precision across core specialties; improves as it learns from your 835 outcomes.

Progress notes, H&Ps, discharge summaries, operative notes, imaging reports, problem lists, and scanned PDFs/OCR.

No—augments coders and clinicians. You choose thresholds to auto-accept or route to review.

Payer-aware rules catch medical necessity, specificity, modifier, and documentation gaps before submission.

Yes—provider review queues with evidence highlights and coding guidelines improve acceptance and education.

Primary care, cardiology, orthopedics, oncology, GI, OB/GYN, radiology, anesthesia, ED, hospitalist, and more.

We map 835 adjudication outcomes back to features to auto-tune models and surface root-cause fix lists.

Typical 2–4 weeks via FHIR/HL7; faster for athenahealth/OpenEMR with prebuilt connectors.

Set auto-accept thresholds; route low-confidence items to coder/clinician review with highlighted evidence.

QuickCode is the underlying AI coding engine. Coding & Notes Review packages that engine into the HIM and RCM workflow layer: chart worklists, the 8-step claim scrub, CDI clarification queues, audit trails, and claim handoff.

No. QuickIntell connects through FHIR, HL7 v2, REST APIs, and supported EHR integrations including Epic, Cerner/Oracle Health, athenahealth, and OpenEMR. Most teams go live in 2-4 weeks without replacing their EHR.

A 50-provider group usually fits Growth, with directional pricing from $8k/month plus implementation and any usage above included volume. Final pricing depends on encounter volume, specialties, DRG/HCC scope, integrations, and support needs.

Yes—export finalized codes to your PMS, scrubber, or clearinghouse; supports X12 837 generation.

DRG grouping with CC/MCC detection, present-on-admission flags, and attending vs. consultant differentiation.

Encrypted end-to-end, isolated environments for Scale tier, signed BAA, configurable retention/purge policies.

Ready to cut coding denials and accelerate cash?