A healthcare claims management organization needed to overcome the inefficiencies of fax-based document handling. Their claim-processing workflow relied on receiving physical or low-quality faxed documents, resulting in errors, delays, and operational bottlenecks. The goal was to digitize the process, reduce turnaround time, and enhance accuracy using AI-powered automation.
Problem Points
- Documents received as faxed images instead of clean digital PDFs
- Poor image quality due to distortions, artifacts, and skewed scans
- Manual data extraction was slow, repetitive, and error-prone
- Backlogs grew quickly, delaying claim approvals
- No centralized system for accessing, tracking, or organizing documents
- Significant time lost sorting, validating, and indexing physical faxes
Solutions Implemented
- Developed AI-driven OCR pipelines to automate document processing
- Applied image enhancement and de-skewing to improve readability
- Implemented OCR with bounding boxes for accurate text extraction
- Added human-in-the-loop verification for high-accuracy data validation
- Introduced centralized document access and tracking
- Combined automation and manual review for optimal performance and compliance
Key Features Added
- AI-powered image cleaning and straightening
- High-accuracy OCR with structured text extraction
- Automated indexing and classification of documents
- Real-time processing dashboards and tracking
- Human-assisted review module for improved precision
By integrating AI-based OCR and streamlined verification workflows, the organization achieved a 73% reduction in processing time, improved accuracy, and nearly 70% higher productivity. Backlogs that once took days were cleared within hours, resulting in faster claim resolutions and significantly enhanced customer satisfaction. This transformation modernized their claims process and set a strong foundation for scalable, automated healthcare operations.
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