Pattern Data - Get the proof without the burden.

Pattern Data Get the proof without the burden.

What is Pattern Data?

Pattern Data is a sophisticated AI-powered platform designed specifically for mass tort litigation management. The software revolutionizes the traditional approach to medical record review by automating the extraction and analysis of relevant information from extensive documentation.

The platform combines artificial intelligence with legal expertise to accelerate case reviews, enhance accuracy in document analysis, and streamline the settlement process. It enables law firms to efficiently process thousands of medical records while maintaining high accuracy standards, significantly reducing the time spent on manual document review.

Features

Automated Medical Record Review: AI-powered analysis of medical documentation
Quick Case Quality Assessment: Rapid determination of case quality at intake
Settlement Analysis: Automated categorization based on established matrix
Document Digitization: Converting and analyzing medical records
Executive Reporting: Generation of strategic operational insights
Rapid Validation: Quick verification of extracted information

Use Cases

Mass tort case management
Medical record review automation
Settlement analysis and processing
Case quality assessment
Litigation document processing
Law firm operations optimization

FAQs

What types of mass tort cases does Pattern Data support?

Pattern Data supports various mass tort litigations including Zantac, Camp Lejeune, Talcum Powder, CPAP, Ozempic, JUUL Settlement, Roundup, 3M Earplugs, and Aqueous Film Forming Foam (AFFF).
How does Pattern Data improve review efficiency?

Pattern Data performs full case reviews at 10x the speed with greater accuracy by automating medical record reviews and presenting relevant information for quick validation.
What are the main stages of litigation that Pattern Data assists with?

Pattern Data assists with three main stages: Collect/Intake for case quality determination, Case Review for efficient document analysis, and Settlement for automated analysis and categorization.