How to Automate GE Centricity PACS Data Export (No API...

Introduction

GE Centricity PACS is a leading Picture Archiving and Communication System (PACS) that manages medical imaging, radiology workflows, and diagnostic image storage. While GE Centricity PACS provides integration capabilities, browser automation offers a powerful solution for automating image metadata extraction for research, syncing radiology reports with primary care EHRs, and streamlining medical imaging workflows when direct API access is limited or unavailable.

Why Use Browser Automation for GE Centricity PACS Data Export?

• Limited API Access: GE Centricity PACS has restricted API access for many imaging and reporting operations
• Research Analytics: Automate image metadata extraction for research and analytics purposes
• Clinical Integration: Sync radiology reports with primary care EHRs for better care coordination
• Dashboard-Only Features: Some imaging and reporting tools are only available through the web interface
• Historical Data: Easier access to older imaging studies and reports beyond API limits
• Bulk Operations: Process large volumes of imaging studies for metadata extraction
• Real-Time Sync: Automate syncing of radiology reports with EHR systems in real-time
• Image Management: Efficiently organize and export medical imaging data for analysis

Setting Up GE Centricity PACS Data Export Automation

Here's how to automate data collection from GE Centricity PACS using browser automation:

import { chromium } from 'playwright';

const response = await fetch("https://api.anchorbrowser.io/api/sessions", {
  method: "POST",
  headers: {
    "anchor-api-key": "YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    'headless': false,
    'proxy': {
      'type': 'residential',
      'country': 'US'
    }
  }),
});

const { id } = await response.json();
const connectionString = `wss://connect.anchorbrowser.io?apiKey=YOUR_API_KEY&sessionId=${id}`;

const browser = await chromium.connectOverCDP(connectionString);
const context = browser.contexts()[0];
const ai = context.serviceWorkers()[0];
const page = context.pages()[0];

// Navigate to GE Centricity PACS
await page.goto("https://your-pacs.centricity.com");

// Login with AI agent
await ai.evaluate(JSON.stringify({
  prompt: 'Log in to GE Centricity PACS using the provided credentials. Wait for the dashboard to fully load.'
}));

Use Case 1: Automate Image Metadata Extraction for Research

Efficiently extract image metadata from medical imaging studies for research and analytics purposes:

const extractImageMetadata = async (page, ai, studyCriteria) => {
  const metadataResults = [];
  
  // Navigate to studies section
  await ai.evaluate(JSON.stringify({
    prompt: 'Navigate to the Studies or Imaging Studies section in GE Centricity PACS'
  }));
  
  // Set search criteria
  await ai.evaluate(JSON.stringify({
    prompt: `Set search filters: date range ${studyCriteria.startDate} to ${studyCriteria.endDate}, modality types: ${studyCriteria.modalities.join(', ')}, body parts: ${studyCriteria.bodyParts.join(', ')}, patient age range: ${studyCriteria.ageRange}`
  }));
  
  // Execute search
  await ai.evaluate(JSON.stringify({
    prompt: 'Click Search or Query Studies and wait for results to load'
  }));
  
  // Wait for results
  await page.waitForLoadState('networkidle');
  
  // Get study list
  const studyList = await ai.evaluate(JSON.stringify({
    prompt: 'Extract study list including: study instance UID, accession number, patient ID, study date, and study description. Return as structured JSON array.'
  }));
  
  const studies = JSON.parse(studyList);
  
  // Extract metadata for each study
  for (const study of studies) {
    // Navigate to study details
    await ai.evaluate(JSON.stringify({
      prompt: `Open study: ${study.accessionNumber} or ${study.studyInstanceUID}`
    }));
    
    // Wait for study to load
    await page.waitForLoadState('networkidle');
    
    // Extract image metadata
    const metadata = await ai.evaluate(JSON.stringify({
      prompt: 'Extract image metadata including: patient demographics (name, ID, DOB, age, gender), study information (study date, accession number, study description, modality, body part), image details (slice thickness, pixel spacing, matrix size, kVp, mAs, contrast agent), DICOM tags (manufacturer, model, software version, institution), and clinical information (referring physician, performing physician, protocol). Return as structured JSON data.'
    }));
    
    const metadataData = JSON.parse(metadata);
    
    metadataResults.push({
      studyInstanceUID: study.studyInstanceUID,
      accessionNumber: study.accessionNumber,
      patientId: study.patientId,
      metadata: metadataData,
      extractedDate: new Date().toISOString()
    });
    
    // Export metadata if needed
    await ai.evaluate(JSON.stringify({
      prompt: 'Export study metadata as JSON or CSV if export option is available'
    }));
    
    // Small delay between studies
    await page.waitForTimeout(1000);
  }
  
  return metadataResults;
};

Use Case 2: Sync Radiology Reports with Primary Care EHRs

Automate the synchronization of radiology reports with primary care EHR systems for better care coordination:

const syncRadiologyReports = async (page, ai, reportCriteria) => {
  const syncedReports = [];
  
  // Navigate to reports section
  await ai.evaluate(JSON.stringify({
    prompt: 'Navigate to the Reports or Radiology Reports section in GE Centricity PACS'
  }));
  
  // Set search criteria
  await ai.evaluate(JSON.stringify({
    prompt: `Set search filters: date range ${reportCriteria.startDate} to ${reportCriteria.endDate}, report status: ${reportCriteria.status || 'finalized'}, radiologist: ${reportCriteria.radiologist || 'all'}`
  }));
  
  // Execute search
  await ai.evaluate(JSON.stringify({
    prompt: 'Click Search or Query Reports and wait for results to load'
  }));
  
  // Wait for results
  await page.waitForLoadState('networkidle');
  
  // Get report list
  const reportList = await ai.evaluate(JSON.stringify({
    prompt: 'Extract report list including: report ID, accession number, patient ID, study date, report date, report status, and radiologist name. Return as structured JSON array.'
  }));
  
  const reports = JSON.parse(reportList);
  
  // Sync each report
  for (const report of reports) {
    // Open report
    await ai.evaluate(JSON.stringify({
      prompt: `Open report: ${report.reportId} or accession ${report.accessionNumber}`
    }));
    
    // Wait for report to load
    await page.waitForLoadState('networkidle');
    
    // Extract report content
    const reportData = await ai.evaluate(JSON.stringify({
      prompt: 'Extract radiology report including: patient information, study information (modality, body part, contrast), clinical history, findings, impression, recommendations, radiologist signature, report date, and any attached images or measurements. Return as structured JSON data.'
    }));
    
    const reportContent = JSON.parse(reportData);
    
    syncedReports.push({
      reportId: report.reportId,
      accessionNumber: report.accessionNumber,
      patientId: report.patientId,
      reportContent: reportContent,
      syncStatus: 'ready',
      lastSynced: new Date().toISOString()
    });
    
    // Sync with primary care EHR (example: send to EHR API)
    if (reportContent.reportStatus === 'finalized') {
      console.log(`Report ${report.reportId} finalized - ready for EHR sync`);
      // Add integration logic here to send report to primary care EHR
      // Format: { patientId, studyDate, reportText, findings, impression, recommendations }
    }
    
    // Download report as PDF if needed
    await ai.evaluate(JSON.stringify({
      prompt: 'Download report as PDF if download option is available'
    }));
    
    // Small delay between reports
    await page.waitForTimeout(1000);
  }
  
  return syncedReports;
};

Exporting Imaging Studies

Export imaging studies and related data for external analysis:

const exportImagingStudies = async (page, ai, dateRange) => {
  await ai.evaluate(JSON.stringify({
    prompt: 'Navigate to the Studies or Archive section'
  }));
  
  // Set date filter
  await ai.evaluate(JSON.stringify({
    prompt: `Set the date filter to ${dateRange.start} to ${dateRange.end}`
  }));
  
  // Export studies
  await ai.evaluate(JSON.stringify({
    prompt: 'Click Export or Download button, select format (DICOM, PDF, or CSV), and wait for the download to complete'
  }));
  
  const download = await page.waitForEvent('download');
  return await download.path();
};

Collecting Study Information

Extract study information and patient demographics:

const collectStudyInformation = async (page, ai, accessionNumber) => {
  await ai.evaluate(JSON.stringify({
    prompt: `Navigate to study with accession number: ${accessionNumber}`
  }));
  
  // Extract study information
  const studyInfo = await ai.evaluate(JSON.stringify({
    prompt: 'Extract study information including: patient demographics, study details (date, time, modality, body part), referring physician, performing physician, study description, protocol, contrast information, and image count. Return as structured JSON data.'
  }));
  
  return JSON.parse(studyInfo);
};

Generating Custom Reports

Create custom reports with specific filters and criteria:

const generateCustomReports = async (page, ai, reportConfig) => {
  await ai.evaluate(JSON.stringify({
    prompt: 'Navigate to the Reports or Analytics section'
  }));
  
  // Configure report
  await ai.evaluate(JSON.stringify({
    prompt: `Create a new report with: report type ${reportConfig.type}, date range ${reportConfig.startDate} to ${reportConfig.endDate}, filters ${JSON.stringify(reportConfig.filters)}, output format ${reportConfig.format}`
  }));
  
  // Generate report
  await ai.evaluate(JSON.stringify({
    prompt: 'Click Generate Report, wait for processing to complete, then download'
  }));
  
  const download = await page.waitForEvent('download');
  return await download.path();
};

Best Practices for GE Centricity PACS Automation

• Security: Use secure credential storage and enable 2FA handling for PACS system access
• HIPAA Compliance: Ensure all data handling meets HIPAA privacy and security requirements for protected health information (PHI)
• Rate Limiting: Add delays between requests to avoid overwhelming the system and account restrictions
• Data Validation: Verify exported data completeness and accuracy before processing, especially for research metadata
• Error Handling: Implement retry logic for transient failures and network issues
• DICOM Compliance: Ensure all image metadata extraction maintains DICOM standard compliance
• Research Ethics: Ensure all research metadata extraction complies with IRB and research ethics requirements
• EHR Integration: Format radiology reports for easy integration with primary care EHR systems
• Data De-identification: Ensure proper de-identification of patient data for research purposes when required
• Regular Updates: Monitor for changes in GE Centricity PACS' interface and update scripts accordingly

Handling Authentication

GE Centricity PACS may require multi-factor authentication. Here's how to handle it:

const handlePACSAuth = async (page, ai, credentials) => {
  // Navigate to login
  await page.goto("https://your-pacs.centricity.com");
  
  // Enter credentials
  await ai.evaluate(JSON.stringify({
    prompt: `Enter username: ${credentials.username} and password: ${credentials.password}, then click Login`
  }));
  
  // Handle 2FA if required
  await ai.evaluate(JSON.stringify({
    prompt: 'If a 2FA prompt appears, wait for the code to be provided and enter it, or click "Remember this device" if available'
  }));
  
  // Wait for dashboard
  await page.waitForLoadState('networkidle');
};

Resources

• Anchor Browser Documentation - Complete API reference and guides
• Anchor Browser Playground - Try browser automation in your browser

Conclusion

Browser automation provides a flexible alternative to API access for GE Centricity PACS data export. By leveraging intelligent browser agents, you can automate image metadata extraction for research, sync radiology reports with primary care EHRs, and streamline medical imaging workflows that aren't easily achievable through API calls alone. Whether you need to extract metadata for research, synchronize reports with EHR systems, or generate custom reports, browser automation enables efficient data management from GE Centricity PACS while maintaining HIPAA compliance and supporting clinical research.

Start automating your GE Centricity PACS workflows today and streamline your medical imaging data management processes!