Skip links

Healthcare Optical Character Recognition (OCR)

Transforming Patient Data Management & Accessibility

What is OCR

Optical Character Recognition (OCR) is that solution that transitions healthcare systems from paper-based archives to digital platforms, ensuring efficiency and accuracy. OCR scans and converts printed/handwritten documents like patient forms, doctor’s notes, prescription labels, lab results, medical histories, imaging reports, etc., into digital data which simplifies the tasks of storage & organization of healthcare records. Once digital, this information becomes more accessible & can be leveraged to extract meaningful insights.

Drive Productivity to the next level

Swift Workflows

Automate repetitive tasks for data entry, record keeping, & billing.

Availability of Data

Digitally stored data is
available 24*7.

Eliminate Human Errors

Higher data accuracy with automation.

Seamless Integration

Integrate with existing systems
i.e., EHR & PMS.

HIPAA Compliance

Complete documentation of
patient consent.

Safety

Safeguard sensitive data in comparison to paper docs.

OCR & NLP: Enhancing Data Extraction

De-identification of Sensitive Information

Advanced models such as OCR, NLP, and Computer Vision, together can classify documents and images, including DICOM files, to pinpoint and redact personal identifiers, ensuring privacy and compliance with regulations.

Data Extraction from Custom Images & Forms

By training bespoke models, OCR systems can pinpoint and standardize specific details, capturing essential data from various types of healthcare imagery and forms.

Table Data Extraction

OCR can identify and extract complete tables from scanned images, converting printed data from sources like financial disclosures and lab results into structured, usable formats.

Entity Recognition in Scanned PDFs

Utilizing a regular NER pipeline, OCR can import, pre-process, and recognize text from scanned images, correcting errors to extract meaningful entities.

Skew Correction in Scanned Documents

OCR, in particular, offers the ability to correct document skewness, significantly enhancing OCR accuracy.

Text Recognition in Natural Scenes

OCR can identify and extract text from natural scenes, using image segmentation and pre-processing to handle complex backgrounds and layouts.

Background Noise Removal

The OCR is designed to finely tune image pre-processing, removing background noise to improve OCR outcomes.

DICOM Text Recognition

OCR technology can extract text not only from the visual content of DICOM images but also from the accompanying metadata, offering a comprehensive text extraction solution.

Use Cases