One AI Workflow for Referral Extraction, Validation, and Processing
Devine Globe combined medical OCR, large language models, document preprocessing, cloud APIs, and secure data storage to build an intelligent referral processing system for high-volume home healthcare operations.
1. AI-Powered Medical Document OCR
Google Cloud Vision API extracts printed and handwritten text from referral packets, including medical records, insurance claim forms, clinical notes, diagnostic reports, prescriptions, and supporting documents. This eliminates much of the manual transcription previously required during referral intake.
2. LLM-Based Referral Data Extraction
An LLM extraction layer interprets the OCR output and identifies relevant patient, insurance, clinical, and referral information. It converts unstructured document content into a consistent data format that can be validated and used by downstream healthcare systems.
3. Medical Document Preprocessing
Advanced preprocessing improves document clarity before OCR begins. The workflow prepares scanned pages, handwritten records, checkboxes, and inconsistently formatted documents for more reliable recognition and structured data extraction.
4. Parallel Referral Processing
A parallel processing architecture supports bulk uploads and processes more than 50 documents concurrently. RESTful APIs allow referral files to be submitted and processed in real time while supporting integration with existing healthcare operations systems.
5. Secure AWS Document Storage
Referral documents and extracted information are stored using encrypted AWS cloud storage. Amazon S3 versioning preserves document history, prevents accidental data loss, and supports complete audit trails across the referral processing lifecycle.
.2qinst50l_1uj.png)
