Case Study: Helsinki University Hospital accelerates rare disease diagnosis with Tietoevry AI data platform

Artificial intelligence revolutionizes the diagnostics of rare diseases

The Helsinki University Hospital (HUS) faced the challenge of building a certified, GDPR-compliant research environment to accelerate medical research. They partnered with vendor Tietoevry to create a secure digital platform capable of handling large data masses for advanced analytics and diagnostics, particularly for rare diseases.

Tietoevry co-developed a data lake service and the HUS Acamedic analytics workspace, which utilizes AI and machine learning to process vast datasets. This solution, part of the eCare for Me project, enables faster diagnosis of rare diseases, significantly reducing patient uncertainty and unnecessary treatments. The results include a more efficient patient journey and substantial reductions in public healthcare costs, with the potential for costs to be up to 40 times greater prior to a diagnosis.

Helsinki University Hospital

Mikko Seppänen

Chief Physician and Director