Predicting the Unpredictable
Predictive Health Analytics continuously analyses hundreds of patient parameters, including vital sign trends, laboratory changes, medication adjustments, and nursing observations, to calculate a personalised risk score for every patient on every ward.
When a score crosses a defined threshold, the appropriate clinician receives an immediate alert, often hours or days before a crisis becomes visible to the human eye.
- Real-time deterioration scoring for every inpatient
- Condition-specific models for sepsis, cardiac arrest, and pulmonary embolism
- Population health risk stratification for outpatients
- Trend analysis across more than two hundred clinical parameters
Beyond the Hospital Walls
Prediction does not end at discharge. MET-Ai tracks patients after they leave through wearable devices and remote monitoring, identifying readmission risk before it becomes an emergency presentation.
The population health module enables proactive, preventive outreach to high-risk patients at scale, reducing readmissions and improving long-term outcomes.
- Thirty-day readmission risk prediction at the point of discharge
- Early warning of post-surgical complications
- Progression modelling for diabetes, heart failure, and COPD
- Population-level risk segmentation for preventive care
Applications in Clinical Practice
Identification of developing sepsis up to six hours before clinical criteria are met.
Prediction of in-hospital cardiac arrest up to twenty-four hours in advance.
Automatic activation of clinical teams when deterioration scores breach thresholds.
Support for the highest-risk patients before discharge to prevent emergency returns.
Prediction of adverse drug reactions before they occur during treatment.
Accurate discharge-date forecasting to improve bed management.
Begin Predicting Before It Is Too Late
Implement MET-Ai Predictive Analytics and give your clinicians the advantage of time.