Healthcare organizations face significant challenges with traditional transcription services: manual processes, delayed turnaround times, limited integration with EMR systems, and cost inefficiencies. HealthTranscribe addresses these challenges head-on with a production-ready, Azure-powered solution.

The Challenge

Traditional medical transcription creates bottlenecks in healthcare workflows:

  • Manual Processes — Require manual uploads and lack automation
  • Delayed Turnaround — Transcripts can take days, slowing research and decision-making
  • Limited Integration — Minimal interoperability with EMR systems or analytics platforms
  • Cost Inefficiencies — Pricing models that scale poorly for large volumes

The Solution

Built with Azure AI Services, HealthTranscribe delivers:

  • Real-time transcription with speaker diarization
  • Medical entity extraction identifying 33+ clinical entity types
  • FHIR R4 compliant output for healthcare interoperability
  • 99% cost reduction compared to traditional services

Key Capabilities

High-Accuracy Speech Transcription

Using Azure Speech Services Fast Transcription API:

  • Multi-format support (WAV, MP3, M4A, FLAC, OGG)
  • Real-time speaker diarization
  • Multi-speaker recognition (doctor, patient, others)
  • Word-level timestamp precision

Medical Entity Recognition

Azure Text Analytics for Health extracts clinical entities including:

Category Entities
Medications Drug names, dosages, frequencies, routes
Conditions Diagnoses, symptoms, diseases, disorders
Procedures Treatments, surgeries, examinations
Anatomy Body structures, organs, systems

Advanced features include:

  • Assertion Detection — Negation, uncertainty, conditional detection
  • UMLS Entity Linking — Automatic linking to medical codes
  • Relationship Mapping — Drug→Dosage, Condition→Body Structure

FHIR R4 Standard Compliance

Seamless healthcare interoperability:

  • Standards-compliant resource generation
  • EHR system integration ready
  • Privacy-preserving data structures

Architecture

The solution leverages:

  • Azure Static Web App — Modern UI with dark/light mode
  • Azure Functions — Serverless Python backend
  • Azure Speech Services — Fast transcription with diarization
  • Azure Text Analytics for Health — Medical NER and FHIR export
  • Cosmos DB — Results and state management
  • Managed Identity — Zero secrets architecture

Cost Comparison

Service Cost per Minute 100 Hours/Month
Azure Speech (Batch) $0.003 $18
Azure Speech (Real-time) $0.017 $102
Traditional Services $0.79 $4,740

Monthly savings: Up to $4,700 for 100 hours of transcription.

Try It Out

The demo application is available on GitHub with one-click deployment:

GitHub Repository

Deployment options:

  1. GitHub Actions — Automated CI/CD pipeline
  2. Azure CLI — Manual deployment

Quick Deploy Steps

# Fork the repository
git clone https://github.com/samueltauil/transcription-services-demo.git

# Create Azure service principal
az ad sp create-for-rbac --name "github-transcription-sp" \
  --role contributor \
  --scopes /subscriptions/{subscription-id} \
  --sdk-auth

# Add AZURE_CREDENTIALS secret to GitHub
# Run "Deploy All" workflow from Actions tab

Learn More

This demo application was developed to help organizations explore Azure AI solutions for healthcare transcription workflows. It demonstrates the capabilities but is not intended as a production-ready solution without additional customization.