Abridge Core Workflow A

Abridge Core Workflow A — Encounter-to-Note Pipeline

Overview

Primary money-path workflow for Abridge: capturing a clinical encounter via ambient listening, processing it through Abridge's generative AI, producing a structured clinical note, and pushing it into the EHR. This is the workflow that runs millions of times daily across health systems using Abridge.

Prerequisites

• Completed abridge-install-auth setup
• EHR integration configured (Epic preferred)
• Audio capture infrastructure (microphone array or mobile device)
• HIPAA-compliant transport layer (TLS 1.3+)

Instructions

Step 1: Initialize Encounter Session

// src/workflows/encounter-pipeline.ts
import axios, { AxiosInstance } from 'axios';

interface EncounterContext {
  patient_id: string;           // FHIR Patient resource ID
  encounter_id: string;         // FHIR Encounter resource ID
  provider_id: string;          // NPI or FHIR Practitioner ID
  specialty: string;            // e.g., 'internal_medicine', 'cardiology'
  encounter_type: 'outpatient' | 'inpatient' | 'emergency';
  department_id?: string;
  language: string;             // ISO 639-1 (Abridge supports 28+ languages)
}

interface SessionResponse {
  session_id: string;
  websocket_url: string;        // For real-time audio streaming
  status: 'initialized' | 'recording' | 'processing' | 'completed';
  created_at: string;
}

async function initializeEncounter(
  api: AxiosInstance,
  context: EncounterContext
): Promise<SessionResponse> {
  const { data } = await api.post('/encounters/sessions', {
    ...context,
    capture_mode: 'ambient',       // Background listening, no wake word
    note_template: 'soap',         // SOAP, H&P, progress note, etc.
    real_time_preview: true,       // Enable live note preview during encounter
    smart_phrases_enabled: true,   // Support Epic SmartPhrases in output
  });

  console.log(`Encounter session initialized: ${data.session_id}`);
  console.log(`WebSocket URL: ${data.websocket_url}`);
  return data;
}

Step 2: Stream Audio via WebSocket

// src/workflows/audio-stream.ts
import WebSocket from 'ws';

interface AudioStreamConfig {
  sampleRate: 16000;      // 16kHz required
  channels: 1;            // Mono
  encoding: 'pcm_s16le';  // 16-bit PCM little-endian
  chunkDurationMs: 100;   // Send 100ms chunks
}

interface TranscriptFragment {
  type: 'transcript_fragment';
  speaker: 'provider' | 'patient' | 'unknown';
  text: string;
  confidence: number;
  timestamp_ms: number;
  is_final: boolean;
}

interface NotePreview {
  type: 'note_preview';
  sections: Record<string, string>;
  last_updated: string;
}

function streamEncounterAudio(
  wsUrl: string,
  audioSource: NodeJS.ReadableStream
): Promise<void> {
  return new Promise((resolve, reject) => {
    const ws = new WebSocket(wsUrl, {
      headers: {
        'Authorization': `Bearer ${process.env.ABRIDGE_CLIENT_SECRET}`,
        'X-Org-Id': process.env.ABRIDGE_ORG_ID!,
      },
    });

    ws.on('open', () => {
      console.log('Audio stream connected');

      // Stream audio chunks
      audioSource.on('data', (chunk: Buffer) => {
        if (ws.readyState === WebSocket.OPEN) {
          ws.send(chunk);
        }
      });

      audioSource.on('end', () => {
        ws.send(JSON.stringify({ type: 'end_of_stream' }));
      });
    });

    ws.on('message', (data: Buffer) => {
      const msg = JSON.parse(data.toString());

      if (msg.type === 'transcript_fragment') {
        const frag = msg as TranscriptFragment;
        if (frag.is_final) {
          console.log(`[${frag.speaker}]: ${frag.text}`);
        }
      }

      if (msg.type === 'note_preview') {
        const preview = msg as NotePreview;
        console.log('Live note preview updated:', Object.keys(preview.sections).join(', '));
      }
    });

    ws.on('close', () => resolve());
    ws.on('error', reject);
  });
}

export { streamEncounterAudio, AudioStreamConfig };

Step 3: Generate and Retrieve Clinical Note

// src/workflows/note-generation.ts
interface ClinicalNote {
  note_id: string;
  session_id: string;
  template: 'soap' | 'hp' | 'progress' | 'procedure';
  sections: {
    chief_complaint: string;
    history_present_illness: string;
    review_of_systems: string;
    physical_exam: string;
    assessment: string;
    plan: string;
    medications?: string;
    allergies?: string;
  };
  coding: {
    icd10: Array<{ code: string; description: string; confidence: number }>;
    cpt: Array<{ code: string; description: string; confidence: number }>;
    hcc: Array<{ code: string; raf_score: number }>;  // Risk adjustment
  };
  source_map: Array<{
    section: string;
    note_text: string;
    source_transcript: string;
    audio_start_ms: number;
    audio_end_ms: number;
  }>;
  quality_metrics: {
    confidence_score: number;
    completeness_score: number;
    coding_accuracy: number;
  };
}

async function generateAndRetrieveNote(
  api: AxiosInstance,
  sessionId: string
): Promise<ClinicalNote> {
  // Finalize session and trigger note generation
  await api.post(`/encounters/sessions/${sessionId}/finalize`);

  // Poll for completed note (typically 10-30 seconds)
  for (let i = 0; i < 60; i++) {
    const { data } = await api.get(`/encounters/sessions/${sessionId}/note`);
    if (data.status === 'completed') {
      return data.note;
    }
    await new Promise(r => setTimeout(r, 1000));
  }
  throw new Error(`Note generation timed out for session ${sessionId}`);
}

Step 4: Push Note to EHR via FHIR

// src/workflows/ehr-push.ts
import axios from 'axios';

interface FhirDocumentReference {
  resourceType: 'DocumentReference';
  status: 'current';
  type: { coding: Array<{ system: string; code: string; display: string }> };
  subject: { reference: string };
  context: { encounter: Array<{ reference: string }> };
  content: Array<{ attachment: { contentType: string; data: string } }>;
}

async function pushNoteToEpic(
  fhirBaseUrl: string,
  accessToken: string,
  note: { patient_id: string; encounter_id: string; content: string }
): Promise<string> {
  const docRef: FhirDocumentReference = {
    resourceType: 'DocumentReference',
    status: 'current',
    type: {
      coding: [{
        system: 'http://loinc.org',
        code: '11506-3',
        display: 'Progress note',
      }],
    },
    subject: { reference: `Patient/${note.patient_id}` },
    context: { encounter: [{ reference: `Encounter/${note.encounter_id}` }] },
    content: [{
      attachment: {
        contentType: 'text/plain',
        data: Buffer.from(note.content).toString('base64'),
      },
    }],
  };

  const response = await axios.post(
    `${fhirBaseUrl}/DocumentReference`,
    docRef,
    { headers: { Authorization: `Bearer ${accessToken}`, 'Content-Type': 'application/fhir+json' } }
  );

  console.log(`Note pushed to Epic: DocumentReference/${response.data.id}`);
  return response.data.id;
}

Output

• Ambient encounter session with real-time transcription
• Structured SOAP note with ICD-10, CPT, and HCC codes
• Source-mapped citations linking AI output to conversation audio
• FHIR DocumentReference created in Epic EHR

Examples

In a non-production integration test, initialize an encounter with synthetic patient and encounter identifiers, then stream a short pre-recorded synthetic conversation. Wait for the finalized SOAP note, inspect its source map and quality metrics, and submit a DocumentReference to the sandbox FHIR endpoint. Treat the returned resource ID as the success signal. If the resource fails validation, retain only the redacted OperationOutcome, correct the FHIR payload, and retry without replaying real clinical audio.

Error Handling

Resources

• Abridge Clinician Platform
• FHIR R4 DocumentReference
• Epic FHIR API

Next Steps

For patient-facing summaries and portal integration, see abridge-core-workflow-b.