Solutions · Disease prediction
Predictive models built on the national electronic health record help identify patients at risk before disease develops — and give public‑health authorities a live view of what is happening across the country.
Most chronic diseases develop over years, leaving signals in laboratory results, prescriptions, visits and diagnoses long before a crisis. Health systems that analyse these signals can intervene earlier — when treatment is simpler, cheaper and more effective. Israel’s Clalit, the NHS and other systems have demonstrated the potential of this approach; see our article on predictive analytics for population health.
Models trained continuously on electronic health records — millions of records as national coverage grows — estimate individual risk for selected conditions, so care teams can prioritise screening and prevention.
Aggregated, de‑identified data streams provide public‑health authorities with near real‑time views of disease trends, unusual clusters and seasonal patterns across regions.
Predictive models can drift as populations and practice change. A dedicated validation and development environment continuously checks existing models for accuracy and fairness and tests new ones before release.
FAQ
Accuracy depends on the condition, the data available and the population. That is why we validate each model on local data before use and keep monitoring it afterwards.
Yes. As national EHR coverage rises toward 80% by 2030, models gain more complete histories and broader coverage, which generally improves their usefulness. Our infrastructure is planned for that growth.
Further reading
Population-level risk prediction has saved lives when it was validated, calibrated and tied to a clear response. It has also misled health systems when it was not. Here is what the evidence shows.
Estonia is the usual reference point for national e-health. Its success came less from any one application than from legal duties, digital identity and a shared data exchange layer put in place years before the health record. Here is what it built, in what order, and what Moldova can reuse.
Europe now has three layers of law governing health data and medical AI. Here is what GDPR, the European Health Data Space and the AI Act require, and what they mean for an EU candidate country building national healthcare AI.
Talk to our team about specification, supply, deployment and support — from a single hospital department to a national programme.