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Revolutionizing Medical Claim Processing with OCR

Enhancing Accuracy and Efficiency in Document Data Extraction


To minimize human error and optimize the efficiency of processing faxed medical claim documents using Artificial Intelligence.


We implemented an OCR pipeline that automates data extraction from faxed documents, turning data entry staff into supervisors who ensure AI accuracy.


Our solution trimmed document processing time by 73%, from 11 minutes to just under 3 minutes, amplified productivity by 70%, and slashed the document backlog from 3 days to 1 day.

Business Introduction

Specializing in medical claims management, our client’s operations hinged on processing critical information received via faxes from healthcare providers and patients. This complex task was the backbone of their claim-processing workflow, ensuring accurate and efficient claim resolution for enhanced patient care management.

Processing Faxed Documents with Artifacts and Skew

The received documents were faxed, not digital PDFs, requiring information extraction.
Some faxes needed to be clearer or had artifacts, making them difficult to process.
Faxes were sometimes skewed or slanted, complicating the extraction process.

AI-Powered Document Processing Pipeline

We created a solution that took these documents through a pipeline. From this pipeline, we first straightened the documents, and then we applied various image processing techniques to improve image quality.

Once the image quality was improved, we passed the document for creating bounding boxes around the text to be extracted and then extracted the text.

After obtaining the required text, we added it as a task for a data entry person to compare the extracted information with the original document side by side and edit the information wherever it was extracted incorrectly.

Automated Preprocessing and Human Verification

Automated document straightening and image quality improvement
OCR text extraction with bounding box creation
Human-in-the-loop verification and correction process

Measurable Results and Impact

Reduced time per document from 11 minutes to under 3 minutes (73% reduction)
Boosted overall productivity by ~70%
Reduced document backlog from 3 days to 1 day (67% reduction)

Key Achievements

Developed a robust document processing pipeline
Integrated AI and human expertise for accurate data entry
Significantly improved efficiency and productivity
Reduced document backlog and turnaround time


By leveraging OCR, image processing, and heuristics, combined with human supervision, we successfully streamlined the data entry process for faxed “medical claim processing documents. This solution improved accuracy and substantially reduced the time and effort required, leading to increased productivity and a significant reduction in document backlog.

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