abridge-performance-tuning

name	abridge-performance-tuning
description	Optimize Abridge clinical AI integration performance for high-volume deployments. Use when reducing note generation latency, optimizing audio streaming throughput, improving FHIR push performance, or scaling for multi-site health systems. Trigger: "abridge performance", "abridge latency", "abridge optimization", "abridge slow", "abridge scale".
allowed-tools	Read, Write, Edit, Bash(npm:*)
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","healthcare","ai","abridge","performance"]
compatible-with	claude-code

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

// 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: ,
    : ,
  };

  () {}

  
  (: ):  {
    ..(chunk);

     totalSize = ..( sum + b., );
     (totalSize >= ..) {
       combined = .(.);
      . = [];

       (.. === .) {
         start = performance.();
        ..(combined);
        .(performance.() - start);
      }
    }
  }

   (: ):  {
    
    .. = ms; 
  }

  ():  {
     { .... };
  }
}