phase-1-transcription.md

Phase 1: Real-Time Transcription and ICD-10 Coding

Problem: Providers currently spend significant time or money on manual transcription of patient encounters and subsequent coding. Many physicians dictate notes into recorders and later rely on human transcriptionists or scribes. This process is slow and costly – for example, some clinics outsource audio files overseas where teams manually type SOAP notes and then pass them to medical coders, a turnaround that can take 5–10 days. This delay postpones billing and reimbursement, and each manual step introduces opportunities for errors or omissions.

Solution (Phase 1): Automate clinical note-taking and diagnostic coding at the point of care. MedTranscribeAi’s Phase 1 deliverable is a mobile application (initially iOS) that records the provider’s voice during or after a patient encounter and uses AI to generate a structured SOAP note in real time. Simultaneously, the system suggests relevant ICD-10 diagnostic codes based on the note’s content. This phase lays the groundwork by replacing the labor-intensive transcription and coding process with an instantaneous, AI-driven workflow.

Key Features & Functionality (Phase 1)

  • Real-Time Speech-to-Text Transcription: Converts the provider’s spoken narrative into accurate text nearly instantly. The app’s NLP engine is trained on medical vocabulary to recognize clinical terminology and to organize the narrative into the appropriate SOAP note sections.
  • Automated SOAP Note Structuring: Parses the transcribed text into the standard SOAP format. It intelligently identifies subjective patient-reported information, objective findings, assessments (diagnoses), and the plan/recommendations. This ensures the note is well-organized by default. Providers can further configure the template (e.g. choose to include a Review of Systems or other custom sections) to suit their specialty or preferences.
  • Transcription Preferences: MedTranscribeAi offers a “Transcription Preferences” feature that allows each provider to fine-tune how their notes are formatted. Clinicians can set guidance for each section of the note so the AI adapts to their style. For example, a doctor might specify that the Chief Complaint should be a one-line statement in the patient’s own words, or provide a prompt that the HPI (History of Present Illness) be in a narrative paragraph versus bulleted format. Similarly, they could train the model to list Medications with names, dosages, and frequencies on separate lines, or ensure the Family History section includes certain phrasing they prefer. Over time, the model learns from these user-defined prompts and examples, adapting its output to match each provider’s documentation style. This customization ensures that the generated SOAP notes feel familiar and require minimal editing, as they align with individual or practice-level preferences.
  • ICD-10 Code Prediction: Based on the transcribed content, the app suggests one or more relevant ICD-10 codes that match the diagnoses or problems discussed. For example, if the Assessment mentions diabetes with complications, the appropriate specific ICD-10 code is recommended. Providers can accept, adjust, or remove these suggestions before finalizing the note.
  • User Editing & Confirmation: The provider reviews the AI-generated note and coding suggestions on screen, making any corrections via voice or text. The AI continuously learns from these edits to improve future transcription and coding suggestions, acting like a personalized scribe that gets better with feedback.
  • Secure Data Handling: All audio and transcribed text are encrypted and processed in a HIPAA-compliant cloud environment. Users authenticate through a secure account, and the app includes an in-app Business Associate Agreement (BAA) signature on registration. This ensures all protected health information is handled legally and securely. No data is stored on the device; everything is transmitted and stored with end-to-end encryption in the cloud.

User Personas & Needs (Phase 1)

  • Physicians/Providers: These are the primary users who need to streamline documentation. They want to reduce time spent writing notes or dictating later, and avoid after-hours charting. MedTranscribeAi addresses their need to document quickly and accurately without missing billable details, helping prevent under-coding or lost charges.
  • Medical Scribes/Transcriptionists: In clinics that employ scribes, the app can serve as a digital scribe assistant. Scribes may transition to reviewing the AI-generated notes for quality rather than typing from scratch. Their need is to handle more volume with less manual effort, which the app enables by doing the heavy lifting of transcription.
  • Billing/Coding Specialists: Although Phase 1 is provider-focused, medical coders benefit from more accurate upfront documentation and suggested ICD-10 codes. This reduces back-and-forth queries to physicians and speeds up claim preparation. Their need for completeness and correctness is met by the AI acting as a second pair of eyes, suggesting codes that align with the documentation.

System Architecture & Infrastructure (Phase 1)

  • Mobile App (iOS): A user-friendly iPhone/iPad application through which providers record audio. The app handles voice capture and streams it securely to the backend. It also displays the resulting transcribed notes and suggested codes for the provider to review and confirm.
  • Cloud AI Engine: A cloud-based processing pipeline that receives audio from the app. First, a speech-to-text module (using a medical-grade speech recognition model) transcribes the audio. Next, an NLP module analyzes the raw text to segment it into SOAP note fields. A fine-tuned language model ensures contextually appropriate structuring and terminology in the output note.
  • Medical Knowledge Base & Coding Model: The backend incorporates an ICD-10 knowledge base and coding engine. Terms and phrases from the transcript are mapped to possible ICD-10 codes via a coding model or rules. For instance, if “Type 2 diabetes with neuropathy” is mentioned, the system suggests the ICD-10 code E11.40. The coding model can be enhanced with specialty-specific data (e.g., a custom model trained on cardiology vs. pediatric notes) to improve the relevance of its suggestions.
  • Secure Storage & API: All notes, audio, and metadata are stored in a secure cloud database (HIPAA-compliant). A secure API connects the mobile app and the backend services. All data transfer is encrypted (SSL/TLS). Additionally, a web dashboard is provided (as an interim solution in Phase 1) where notes can be reviewed and downloaded as PDF if needed. The architecture is built with a microservices approach, so transcription, NLP processing, and coding recommendation services are modular. This allows the system to scale and makes it easier to introduce new models or rules in later phases.

Deliverables & Milestones (Phase 1)

  • 🚀 Functional iOS MVP: A working iOS application that can record audio and output a structured SOAP note with ICD-10 codes. Note generation and code predictions occur within seconds of completing an audio recording, demonstrating real-time performance.
  • 🚀 Accuracy Benchmarks: The system meets key accuracy targets, such as >90% word transcription accuracy in typical clinic environments and high relevancy for code suggestions. Milestone: The correct primary diagnosis code is suggested >85% of the time in testing.
  • 🚀 Pilot Program Launch: Deploy the Phase 1 app to a small group of beta users (a few physicians in different specialties) and gather feedback. Milestone: The app is published on the Apple App Store (initially as a limited release or via TestFlight) and used in real clinics. (Status: As of launch, the iOS app is nearly complete and slated for App Store release.)