A large healthcare facility was spending significant time manually extracting patient demographic information from scanned hospital entry forms. Key details such as patient name, date of birth, gender, and contact information had to be reviewed and entered by staff, causing delays during patient check-ins and increasing the risk of data entry errors.
The facility needed a reliable way to automate patient form processing while improving speed, accuracy, and overall check-in efficiency.
Infognana implemented its Cognitive Data Extractor (rannsCDE), an AI-powered data extraction solution that combines OCR and Generative AI to process scanned hospital entry forms. The solution adapted to different form layouts, converted scanned images into searchable PDFs, and accurately extracted critical patient demographic details.
To improve reliability, CDE applied confidence-based corrections and validation checks, helping reduce errors and ensuring cleaner data capture across high-volume form processing workflows.
With rannsCDE in place, the healthcare facility achieved 96% AI extraction accuracy and successfully processed more than 100,000 patient forms per month. Patient check-ins became faster, smoother, and more accurate, improving the overall patient experience.
By automating patient check-in form processing, the facility improved operational efficiency, reduced paperwork, and enabled healthcare staff to focus more on delivering care.
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