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https://catalogartifact.azureedge.net/publicartifacts/ltim.ltm-data-and-ai-medical-voice-transcriber-1013fefd-fd2c-45d7-8f33-c45aff23cf1e/image0_LTM216X216px.png

LTM Data And AI Medical Voice Transcriber (MVT)

LTIMindtree Limited

Medical Voice Transcriber (MVT) by LTM is an AI-powered clinical documentation platform built on Microsoft Azure that converts patient–healthcare professional (HCP) conversations into structured medical records, including transcriptions, SOAP notes, nursing notes, and prescriptions. It improves documentation completeness by 15–20%, reduces daily charting time by up to two hours, increases patient throughput, and accelerates billing cycles by 15–25%.

The 6-week Proof of Concept (POC) enables healthcare organizations to evaluate improvements in clinical efficiency and documentation accuracy using a secure, scalable Azure platform while ensuring data security, ethical integrity, and regulatory readiness.

Problem Statement

Clinical documentation is essential but time intensive. Manual recording by clinicians leads to high administrative burden, reduced patient interaction, delayed documentation, and burnout. It also results in inconsistent quality, data fragmentation, increased risk of human error, and compliance challenges.

Solution Overview

Business Group: Healthcare Provider | Clinical Documentation & Care Delivery

MVT enables real-time voice capture and AI-assisted documentation within a secure Azure ecosystem. It converts conversations into structured, editable, EHR-ready records, supporting doctors and nurses with accurate and standardized outputs.

Key Capabilities

  • Voice capture and transcription with Healthcare professionals identification (Doctors and nurses)
  • AI-generated SOAP and nursing notes (editable)
  • Secure management of patient data, vitals, and history
  • Printable/downloadable documents (PDF)
  • Role-based workflows for clinicians
  • Built-in auditability and compliance readiness
  • Target Personas

  • Doctors
  • Nurses
  • Key Benefits

  • 15–20% improvement in documentation quality of Electronic Health Records
  • Saves ~2 hours/day per clinician
  • Enables 1–2 additional patients/day
  • Reduces manual errors and missed documentation
  • Enhances patient interaction time
  • Improves billing efficiency by 15–25%
  • Ensures secure, scalable Azure deployment
  • Technology Stack

  • Azure Services: Azure OpenAI, ML, Monitor, Security Center
  • Storage: PostgreSQL, Azure Blob Storage
  • AI Services: AssemblyAI, Azure OpenAI
  • Frameworks: Python, Django REST
  • Frontend: Vue.js, Vuetify, TypeScript
  • Governance: Swagger/OpenAPI
  • Security & Compliance

  • Role-based access and authentication
  • Encrypted data storage and transmission
  • HIPAA-aligned principles
  • Azure-native monitoring and audit controls
  • No production PHI required for POC
  • POC Scope (6 Weeks)

  • Assess workflows and Azure readiness
  • Deploy MVT securely with access controls
  • Configure transcription and note generation
  • Validate outputs using sample data
  • Demonstrate end-to-end workflows
  • Optimize performance and scalability
  • Deliver final report with recommendations and roadmap
  • At a glance

    https://catalogartifact.azureedge.net/publicartifacts/ltim.ltm-data-and-ai-medical-voice-transcriber-1013fefd-fd2c-45d7-8f33-c45aff23cf1e/image4_MVT2.png
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