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November 30,2025

AI-Powered ICD-10 Coding Automation

About Customer

A leading multi-facility healthcare organization processing over 500,00+ patient encounters annually faced increasing pressure to modernize its medical coding operations while maintaining compliance and financial performance.

  • Industry: Healthcare Services
  • Organization Type: Multi-facility healthcare system
  • Annual Claims Volume: 500,000+ encounters
  • Coding Team: 45+ certified medical coders

The organization required a scalable, AI-driven solution to optimize coding workflows, reduce errors, and accelerate revenue realization.

Business Problem

The existing manual ICD-10 coding process created significant operational bottlenecks and financial risks.

1️. Operational Inefficiencies

  • 15–20 minutes required per chart
  • 3–5 day average coding turnaround time
  • 2,000+ chart backlog during peak periods
  • Heavy reliance on senior coders for complex cases

2️. Accuracy & Compliance Risks

  • 12–15% initial coding error rate
  • Inconsistent interpretation of ICD-10-CM guidelines
  • Difficulty adapting to annual coding updates
  • Increased audit exposure and denial risk

3️. Financial Impact

  • $2.3M annual revenue loss from denials and coding errors
  • $85 average cost per chart for manual coding
  • Delayed claims submission impacting cash flow
  • Rising overtime and staffing expenses

Manual coding had become a critical bottleneck in the revenue cycle, limiting scalability and increasing compliance exposure.

 

Solution

Calyza Tech implemented an AI-powered ICD-10 coding automation system combining advanced clinical NLP, medical knowledge bases, and intelligent validation layers.

 

Core Capabilities

 

Automated Diagnosis Extraction

AI-driven extraction of diagnoses from unstructured clinical documentation.

 

Guideline-Driven Validation

Real-time application of official ICD-10-CM guidelines to ensure regulatory compliance.

 

Intelligent Rule Engine

  • Manifestation detection
  • Combination code recognition
  • Specificity enhancement
  • Billable code validation
  • Sequencing logic application

Full Audit Traceability

Every code assignment includes:

  • Source clinical text reference
  • Official guideline linkage
  • Confidence score

Processing Time: 30–90 seconds per document

Business Outcome

The AI-driven solution delivered measurable operational, financial, and compliance improvements.

 

 Operational Efficiency

  • 85% reduction in coding time (18 → 2.5 minutes per chart)
  • 400% throughput increase (200 → 800+ charts/day)
  • 95% of encounters coded same-day
  • 2,000-chart backlog eliminated within 2 weeks

Accuracy & Quality

  • Coding accuracy improved from 85% → 94%
  • Specificity score increased to 91%
  • Guideline compliance improved to 98%
  • Audit pass rate increased to 96%

 Financial Impact

  • 70% reduction in cost per chart ($85 → $25)
  • $3.2M annual operational savings
  • $1.8M revenue recovery from reduced denials
  • 45% reduction in claim rejection rates
  • Days in A/R reduced from 42 → 31

 Workforce Optimization

  • 60% staff optimization through redeployment
  • Reduced coder burnout
  • Faster onboarding (6–8 weeks → 2–3 weeks)
  • Greater focus on complex case review and quality improvement

 

 

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