Submitted
2025 Global Health Challenge

Medical lab Digitizer.

Team Leader
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The Medical Lab Digitizer is an AI-powered system that converts physical lab reports (scanned copies or images) into a digital database, making patient data accessible, searchable, and actionable. Using Microsoft Azure's Document Intelligence, it extracts patient details, test types, and results, reducing manual data entry by 80%. Healthcare staff upload scanned reports via a secure web portal. Azure AI processes...
What is the name of your organization?
Onyx Data
What is the name of your solution?
Medical lab Digitizer.
Provide a one-line summary or tagline for your solution.
AI-powered system that digitizes paper lab reports into searchable records, enabling better healthcare decisions and reducing manual processing time.
In what city, town, or region is your solution team headquartered?
United Kingdom
In what country is your solution team headquartered?
GBR
What type of organization is your solution team?
For-profit, including B-Corp or similar models
Film your elevator pitch.
What specific problem are you solving?
Healthcare facilities worldwide struggle with inefficient manual management of lab reports, leading to fragmented patient records and compromised care. In developing regions, 67% of healthcare providers face significant data management challenges, with lab technicians spending an average of 4 hours daily on paperwork rather than patient care. Manual lab records are slow and error-prone, resulting in lost patient histories, limited access to past test data, and no structured insights from critical health information. These inefficiencies cost millions annually and directly impact patient outcomes through delayed diagnoses, unnecessary repeat testing, and preventable medical errors. In low-resource settings, paper records are easily damaged or lost, and rural clinics often have no reliable way to access a patient's complete medical history. This problem affects hundreds of millions of patients globally who rely on lab diagnostics for treatment decisions, with the burden falling heaviest on vulnerable populations in resource-constrained healthcare systems where digital infrastructure is limited.
What is your solution?
The Medical Lab Digitizer is an AI-powered system that converts physical lab reports (scanned copies or images) into a digital database, making patient data accessible, searchable, and actionable. Using Microsoft Azure's Document Intelligence, it extracts patient details, test types, and results, reducing manual data entry by 80%. Healthcare staff upload scanned reports via a secure web portal. Azure AI processes the images, organizes the extracted data, and creates unified patient records with complete test histories. Providers can quickly search by name, ID, or test type. Key features include: AI-driven data extraction from paper reports Unified patient records for complete test history Trend analysis for better diagnostics Secure web access with role-based permissions Microsoft Fabric integration for data pipeline and analytics Built on Azure’s cloud infrastructure, the system ensures encrypted storage, audit logs, and secure backups, meeting healthcare compliance standards. It scales to support clinics and large hospitals, optimizing efficiency and accuracy in medical data management.
Who does your solution serve, and in what ways will the solution impact their lives?
The Medical Lab Digitizer serves three primary groups in healthcare settings with limited digital infrastructure: medical staff, laboratory technicians, and patients. For medical staff (doctors, nurses, and healthcare administrators), our solution eliminates the frustration of searching through paper files by providing instant access to complete patient lab histories. Clinicians can make faster, better-informed decisions with visualized trend data across multiple tests, directly improving diagnostic accuracy and treatment outcomes. Laboratory technicians, who currently spend up to 4 hours daily on paperwork, will reclaim this time for actual laboratory work. The 80% reduction in manual data entry not only improves job satisfaction but increases lab throughput capacity in resource-constrained facilities. Most importantly, patients in underserved communities will receive higher quality care through reduced wait times for results, fewer repeat tests due to lost records, and more accurate diagnosis from comprehensive health data. In rural and low-resource settings where medical records are frequently lost or damaged, this digital transformation ensures patients' medical histories remain intact even when seeking care at different facilities. The system particularly benefits those with chronic conditions requiring regular monitoring, as trend analysis enables early intervention and more personalized treatment plans based on their complete testing history.
Solution Team:
izuafa abdulrafiu
izuafa abdulrafiu