Training Solutions
SCRIBE-MD
Cohort-basedSubsidy eligible

AI Clinical Documentation & Medical Coding

Clinical and billing teams can deploy AI to automate medical transcription, generate SOAP notes, assign ICD-10/CPT codes, and validate claims — reducing documentation time by 50-70%, cutting coding turnaround to 24-48 hours, and improving accuracy to 95%+ while maintaining payer compliance.

Equip clinical and billing teams with AI tools to automate medical transcription, clinical note generation, ICD-10/CPT coding, and claims processing. Built for hospitals, medical groups, and healthcare BPOs across Southeast Asia seeking to reduce documentation burden, accelerate billing cycles, and improve coding accuracy.

Duration3-4 days
InvestmentUSD $18,000 - $30,000
Best forClinical documentation specialists, medical coders, billing managers, and healthcare revenue cycle teams seeking to cut documentation time by 50%+ and reduce coding backlogs

THE CHALLENGE

Sound familiar?

Our doctors spend 5-6 hours per day typing notes instead of seeing patients — AI scribes could cut that to 2 hours.

Medical coding takes 12-15 days per claim because coders are manually reading 10-page consultation notes.

We're hiring more coders just to keep up with volume, but accuracy is still 75-80% due to human error.

Claims denials from payers are costing us 10-15% of revenue because of coding errors and incomplete documentation.

Clinicians hate using EHRs — they say the documentation burden is driving burnout and reducing patient interaction time.

We can't find enough certified medical coders in Southeast Asia; AI could fill the talent gap.

Trusted by enterprises across Southeast Asia

Financial Services
Healthcare
Education
Manufacturing
Professional Services
Government

OUTCOMES

What you'll achieve

Problems you'll solve

  • Clinicians spending 50-60% of time on documentation instead of patient care
  • Medical coding backlogs of 10-15 days per claim due to manual note review
  • Coding accuracy at 75-85% due to human error, fatigue, and inconsistent documentation quality
  • Claims denials at 10-20% driven by coding errors, missing documentation, and payer rejections
  • Clinical documentation fragmented across systems, causing billing delays and compliance risks
  • Medical coder shortage across Southeast Asia, limiting revenue cycle capacity

Value you'll gain

  • Time Savings: Reduce clinical documentation time by 50-70% using AI ambient scribes and note generation
  • Speed Improvement: Cut coding turnaround from 12-15 days to 24-48 hours with AI automated code assignment
  • Accuracy Enhancement: Improve coding accuracy from 75-85% to 95%+ through AI consistency and validation
  • Cost Reduction: Lower revenue cycle costs by 30-40% through AI automation of manual coding tasks
  • Revenue Protection: Reduce claims denials by 40-50% with AI-powered documentation quality checks
  • Capacity Expansion: Handle 2-3x coding volume with same team using AI coder augmentation

OUR PROCESS

How we deliver results

Step 1

Documentation & Coding Workflow Assessment

We audit your clinical documentation workflows, EHR systems, coding processes, claims denial patterns, and revenue cycle performance to identify AI automation opportunities.

Step 2

Curriculum Customisation

We tailor the training to your clinical specialties (primary care, surgery, oncology), EHR platform (Epic, Cerner, local systems), and coding environment (in-house, outsourced, hybrid).

Step 3

Hands-On AI Documentation & Coding Training

Your clinical, coding, and billing teams gain practical experience with AI ambient scribes, ICD-10/CPT code automation, and claims quality checks across 3-4 days of workshops.

Step 4

Use Case Development

Teams design 3-5 AI use cases (e.g., AI clinical note generation, automated coding, claims scrubbing) tailored to your specialty mix and revenue cycle priorities.

Step 5

Implementation & Quality Assurance

We provide 90-day support including AI model training on your documentation, coding accuracy validation, EHR integration guidance, and payer compliance checks.

What you'll receive

  • Customised AI documentation & coding training programme (3-4 days)
  • 4 training modules with hands-on labs and clinical/coding case studies
  • 3-5 AI use cases with implementation roadmaps and ROI analysis
  • Payer compliance frameworks and audit trail templates
  • Revenue cycle dashboards tracking coding accuracy and denial rates
  • EHR integration guidance for AI documentation and coding tools
  • 90-day post-training support and implementation guidance

Best for

Clinical documentation specialists, medical coders, billing managers, and healthcare revenue cycle teams seeking to cut documentation time by 50%+ and reduce coding backlogs

IS THIS RIGHT FOR YOU?

Finding the right fit

This is ideal for you if...

  • Hospitals and medical groups with heavy documentation burden and clinician burnout
  • Revenue cycle teams facing coding backlogs of 10-15 days per claim
  • Healthcare BPOs seeking to scale coding capacity without hiring 100+ coders
  • Billing managers experiencing high claims denial rates (10-20%+) due to coding errors
  • Clinical documentation improvement (CDI) teams seeking to automate quality audits

Consider another option if...

  • Small clinics without EHR systems or structured documentation (AI may not integrate well)
  • Organizations expecting AI to eliminate all coding costs (human oversight is still required)
  • Teams unwilling to invest in AI model training and payer compliance validation

See yourself in the list above?

Let's Talk

CURRICULUM

What you'll learn

2 days total

Introduction to AI in healthcare documentation, natural language processing for medical text, coding automation, and payer compliance considerations.

What you'll be able to do

  • Explain how AI automates clinical note generation and medical coding using NLP and machine learning
  • Identify documentation and coding workflows where AI delivers 5-10x productivity gains
  • Assess AI vendor capabilities for ambient scribes, coding assistants, and claims scrubbing
  • Navigate payer requirements and audit risks when using AI-generated codes and documentation
  • Understand EHR integration requirements for AI documentation and coding tools

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