Efficient decision support tools can process large amounts of diverse data and formulate insights quickly.
Healthcare data is often stored in closed systems. Duplicate measurements are costly and decisions based on incomplete information form a risk.
Case example: after a patient has had cardiac surgery it may in many cases be difficult to assess when the person is ready to be discharged. A large proportion of patients return to hospital in the first months, or worse.
A modern research database together with advanced analytics and machine learning is combined in VTT’s solution which recognises electrophysiological mechanisms and helps identify high-risk patients.
Precise diagnosis enhances safety and brings cost savings. VTT’s solution has wide application potential, beyond healthcare.