abridge-performance-tuning

# Abridge Performance Tuning ## Overview Performance optimization for high-volume Abridge deployments. Large health systems process thousands of encounters daily — latency in note generation directly impacts clinical workflow throughput. ## Performance Targets | Metric | Target | Critical Threshold | |--------|--------|--------------------| | Audio stream → first transcript | < 2s | > 5s | | Encounter → completed note | < 30s | > 60s | | Note → EHR push | < 3s | > 10s | | Patient summary generation | < 10s | > 30s | | Concurrent sessions per org | 100+ | < 50 | ## Instructions ### Step 1: Audio Streaming Optimization ```typescript // src/performance/audio-optimizer.ts // Optimize audio chunk size and streaming for lowest latency interface AudioStreamMetrics { chunkSize: number; sendInterval: number; bufferUtilization: number; latencyP50: number; latencyP99: number; } class OptimizedAudioStream { private buffer: Buffer[] = []; private metrics: AudioStreamMetrics = { chunkSize: 3200, // 100ms at 16kHz 16-bit mono = 3200 bytes sendInterval: 100, // Send every 100ms bufferUtilization: 0, latencyP50: 0, latencyP99: 0, }; constructor( private ws: WebSocket, private sampleRate: number = 16000, ) {} // Optimal chunk size: 100ms for low latency, 500ms for bandwidth efficiency processAudioChunk(chunk: Buffer): void { this.buffer.push(chunk); const totalSize = this.buffer.reduce((sum, b) => sum + b.length,...