By Ethan Zhu + Justin Wolkowicz
From Burden to Breakthrough: Tackling Document Chaos with AI
At HealthEdge, our AI-first approach isn’t about abstract promises. It’s about solving real, persistent pain points across the healthcare ecosystem. One of the most pressing? The manual, error-prone world of document processing. Despite the digital transformation sweeping through the industry, faxed and scanned forms still clog workflows and slow down care.
Our AI Team saw this challenge as an opportunity. What began as a targeted experiment in intelligent document recognition has evolved into a powerful, enterprise-grade Optical Character Recognition (OCR) platform that’s transforming how health plans handle prior authorizations and other document-heavy processes.
The Bottleneck: Why Prior Authorization Forms Are So Painful
In healthcare settings, large volumes of documents are still submitted via scanned or faxed pages in non-uniform formats. This creates a significant workload that necessitates manual, error-prone processes for data conversion into standardized formats. Traditional OCR methods can extract text and numbers from images, but they cannot intelligently understand the meaning of the surrounding context of the interesting data.
Prior authorization forms are a prime example. The volume is substantial: our customers process between 50,000 to 100,000 documents each quarter. Each form requires extracting approximately 50 fields from documents with variable layouts, field names, handwritten sections, and non-standardized formats.
The current manual process is inefficient and error-prone. Staff must open a faxed document and must first identify the correct patient. They manually search for member information, but handwritten names often don’t match system records exactly. When the initial search fails, staff must try alternative search methods like member IDs, requiring multiple passes through the fax document to locate the correct identifier.
Once the member is identified, staff manually build the digital prior authorization form, navigating across 10–12 different workflow screens, copying and pasting information, and transcribing handwriting from the fax into various fields. They must cross-reference member eligibility, verify benefit information, check authorization history, and ensure all data points align correctly. This process is time-intensive and introduces errors that can delay patient care or create compliance issues.
The impact extends beyond efficiency. Approximately 45% of processed fax documents are never entered into any digital system and thus will never be used for authorizing a downstream claim. For patient care, this becomes a significant bottleneck as many major care services must wait for authorization before they can be delivered.
Building a Platform for Real-World Complexity
To address this, the HealthEdge AI Team designed a configurable OCR solution that reduces manual workload while maintaining confidence and auditability of results. Our solution is not restricted to processing prior authorization forms. It can be expanded to process a variety of documents, including provider demographics documents, appeals processing, care management documents, and claims-related forms.
Our approach focused on three objectives:
- Eliminate manual data entry through intelligent document processing
- Ensure healthcare compliance with built-in security and audit trails
- Enable rapid deployment across different document types and use cases
The solution classifies documents into categories for targeted processing. For each category, we use specific strategies that deliver better performance and enable the extraction of different field types. This allows us to adapt the solution to new use cases and customer needs.
Our OCR engine is capable of converting fax information into structured JSON data, reducing manual data entry and improving productivity. The field names of the detected output can be easily matched to whatever data model our users need. It handles diverse document formats, including handwritten notes and multilingual content, which traditional OCR systems cannot process effectively.
Most methods are capable of providing confidence scores and bounding boxes for every field, giving users visibility into processing accuracy. The confidence score helps identify fields that may require human verification, and the bounding boxes let the human quickly verify the origin of the extracted information. All extracted data remains editable, ensuring human oversight for sensitive healthcare information. The system never takes automated actions without user approval.
Proven Results: Measurable Workflow Improvements
The transformation from manual to AI-assisted document processing delivers measurable operational improvements:
- The automated workflow eliminates most manual steps through intelligent member-matching algorithms that pre-populate patient information. Relevant data is extracted and highlighted with confidence scores, allowing staff to create authorizations with minimal manual input.
- What previously required extensive searching, copying, and cross-referencing across multiple screens now happens automatically in the background. Organizations can scale from processing 10 fax files per day to over 100 per person through asynchronous, background processing that can handle large volumes of data.
- Healthcare staff can now focus their expertise on authorization decisions and patient care coordination instead of repetitive data entry tasks. This shift improves both job satisfaction and care quality by allowing clinical staff to spend more time on clinical activities. Staff no longer have to struggle with handwritten text interpretation or member identification challenges that previously consumed significant time.
- Comprehensive audit trails can now be easily captured, tracking every user action and decision. This supports HIPAA compliance while providing transparency for healthcare quality assurance and regulatory requirements. Every processing step is documented and attributable to specific users, creating a complete compliance framework without adding administrative burden.
From Experiment to Essential: What Comes Next
This document processing platform is just one example of how HealthEdge’s AI teams are creating tools that not only work but also scale. Built for real-world complexity, with guardrails for compliance and transparency, it embodies our vision: use AI to augment teams, not replace them.
Looking ahead, our focus is on expanding adoption across customers and product lines, integrating across HealthEdge solutions, and continuing to evolve the platform to handle new document types and emerging use cases.
AI-enabled document processing is becoming a viable solution to long-standing inefficiencies, offering health plans a clearer path toward reducing manual effort and administrative error, while enhancing cost savings.
To learn more about our AI strategy, visit our AI blog series on our website.