Leading Medical Tech Transcription Platform
About the Customer
This leading medical technology transcription platform leverages artificial intelligence to help healthcare providers streamline their operations, analyze extensive medical data, and make more accurate, data-driven decisions. By utilizing advanced AI and machine learning algorithms, the platform helps physicians and healthcare organizations identify patterns, predict patient outcomes, and automate tasks that traditionally involved extensive manual input. This approach enhances patient care, accelerates medical research, and fuels innovation in healthcare treatments and technologies.
Customer Challenge
For medical professionals, especially older physicians, efficiency and accuracy in clinical documentation are paramount. Errors in transcription—such as confusing drug names like "Klonopin" and "Clonidine"—can lead to serious patient harm. Thus, accuracy is non-negotiable. Simultaneously, slow transcription services significantly diminish clinical productivity, causing physicians to revert to manual entry, thus negating the benefits of speech recognition entirely.
Previous attempts to integrate AI-based speech-to-text solutions were costly and problematic, particularly regarding latency and accuracy in medical terminology. The customer needed a speech-to-text solution that could offer near-instantaneous transcriptions, exceptional accuracy tailored specifically to medical language, and a substantially lower cost than existing providers.
Proposed Solution & Architecture
The medical transcription platform selected Deepgram's advanced AI speech-to-text technology deployed within a robust and scalable AWS infrastructure to meet their stringent demands.
Technical Architecture and AWS Services Used:
Speech-to-Text AI: Leveraging Deepgram’s specialized Nova-3 Medical speech model, which is pre-trained on medical terminology, drug names, Latin-derived terminology, and medical abbreviations.
AWS Infrastructure Components:
Amazon EC2 Instances (C5a and G5):
C5a Instances manage compute-intensive tasks such as audio stream management and API load balancing.
G5 GPU Instances handle Deepgram’s AI speech model inference, ensuring fast processing times suitable for real-time transcription.
Amazon Elastic Kubernetes Service (EKS): Manages container orchestration and enables dynamic horizontal scaling of GPU-based model inference workloads, ensuring responsiveness under varying demand conditions.
Amazon Elastic File System (EFS): Serves as the shared storage solution for AI models, facilitating quick retrieval and efficient updates.
Amazon Route 53: Manages DNS routing for secure, reliable traffic handling from users directly into the AWS-hosted Deepgram APIs.
AWS VPC: Provides secure, dedicated networking infrastructure for the integration of Deepgram’s transcription service with the med-tech platform's applications.
The integrated solution workflow is as follows:
Physicians dictate medical notes directly to Deepgram via secure AWS endpoints.
Audio data is processed through Deepgram’s medical-specific model hosted on AWS infrastructure.
Physicians receive accurate transcriptions within milliseconds, directly integrated into their clinical workflow systems.
Metrics for Success
Deploying Deepgram’s speech-to-text solution on AWS infrastructure resulted in significant measurable success:
Accuracy: Deepgram achieved a 30% lower word error rate (WER) compared to other transcription providers, critical in the high-stakes medical context.
Latency: Achieved transcription speeds up to 40x faster than competitors, facilitating true real-time documentation workflows.
Cost Savings: Dramatically reduced transcription costs from 7.4 cents per minute to less than 0.5 cents per minute, saving the platform 80-90% compared to their previous solution.
Efficiency Gains: Enabled physicians, particularly those who prefer dictation over manual entry, to save substantial amounts of time—potentially hours per week, directly impacting patient care and administrative efficiency.
Lessons Learned & Outcomes
The deployment provided several valuable outcomes and insights:
Immediate Adoption: Physicians across demographics, especially older clinicians who prefer dictation, quickly adopted Deepgram’s solution due to its intuitive integration, speed, and reliability.
Minimal Customization Needed: Given the specificity of Deepgram’s medical language training, minimal fine-tuning was required, accelerating implementation timelines.
Significant ROI: The combination of cost savings, reduced latency, and improved accuracy substantially improved operational efficiencies and patient documentation quality. These enhancements directly supported better patient outcomes, reduced physician burnout, and increased organizational productivity.
