AI-powered Document Indexing
With AI-powered Document Indexing, Dexit automatically classifies, tags, and organizes documents with unmatched accuracy and speed, reducing manual effort and enhancing efficiency.
Key Features
- Automatic Document Identification & Classification
- Intelligent Master Patient Index (MPI) Matching
- Purpose-built AI Models
- Content Capture & Interpretation
- Advanced Document Ingestion Methods
- Review Requests for AI Validations
1. Automatic Document Identification & Classification: Dexit’s AI intelligently analyzes text, layout, and visual cues to determine document types, ensuring precise categorization. The system recognizes and classifies clinical notes, lab reports, referrals, and other essential patient records with high accuracy.
2. Intelligent Master Patient Index (MPI) Matching: With intelligent MPI matching, documents are seamlessly linked to the correct patient records, eliminating misfiled information and improving retrieval accuracy. This reduces administrative burdens and enhances the completeness of patient records.
3. Purpose-built AI Models: Trained on more than 1,000 images per document type, Dexit’s AI continuously refines its accuracy to adapt to variations in forms and layouts. This specialized training ensures that the system remains highly effective even as document formats evolve.
4. Content Capture & Interpretation: Dexit extracts and normalizes patient data across various document formats, leveraging Machine Learning (ML), OCR, and adaptive feedback loops. This ensures that critical patient information is accurately captured, structured, and made actionable for downstream processes.
5. Advanced Document Ingestion Methods: Dexit supports multiple ingestion methods for document indexing. These include - batch uploads, direct EHR integration, API support, virtual fax server, scanning, etc. Having multiple ingestion methods ensures seamless integration into existing workflows while boosting efficiency.
6. Review Requests for AI Validations: Dexit includes an intuitive review request feature, enabling users to flag documents where AI-generated classifications require validation. This ensures continuous accuracy improvements and a collaborative review process for document integrity.