Accelerating Decision-Making Through Automated Data Extraction

Managing patient data efficiently is crucial for healthcare providers. Yet, with mountains of unstructured medical documents—like discharge summaries and handwritten prescriptions—manual data processing becomes a time-consuming and error-prone task. These challenges slow down insurance claims and impact patient care coordination. Knackforge stepped in to automate and simplify data handling with cutting-edge AI solutions.

Challenges

Healthcare providers often find themselves overwhelmed with high volumes of unstructured patient information. Discharge summaries, handwritten prescriptions, and scanned images make data processing slow and prone to error.

Manual verification not only drains staff productivity but also delays insurance claim processing and patient care coordination. As the volume of data grew, it became clear that automation was essential to maintain efficiency and accuracy.

The Solution

Knackforge implemented an AI-powered OCR solution using Azure AI Document Intelligence to extract text from medical documents, including scanned and handwritten files.

We then utilized OpenAI to intelligently categorize the data into medical, demographic, and insurance categories. The structured data was stored in PostgreSQL, enabling seamless retrieval and RAG-based insights.

The Impact

Faster, More Accurate Data Handling

• 90% Reduction in Manual Verification Time – Staff can now quickly access verified data without manually combing through documents.

• Enhanced Decision-Making – Readily available patient data speeds up decision-making processes, leading to more efficient patient care.

• Reduced Errors and Improved Accuracy – Automated categorization ensures consistent and accurate data handling.