Predict avoidable after-discharge readmission cases of heart failure
Reduce 30, 60 and 90 days readmission risk with ML-based risk management model
Readmission Risk Prediction ML solution helps healthcare providers focus on high-risk patients who can avoid readmission if additional care is provided, thereby noticeably reducing the risk for 30-, 60-, and 90-day readmissions.
The solution is designed to predict heart failure readmission risk, rank patients by their risk level, and then identify potentially avoidable causes. The solution is capable of analyzing a wide range of clinical factors and identifying predictable readmission risk as early as possible.
If there’s a proper custom dataset of non-clinical socio-economic factors, it can be included into the solution's database for significantly more accurate prediction.
How it works?
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Forecasting heart failure readmission risk for 30, 60, 90 days
Capable of being trained on a client’s datasets
Detection of potentially avoidable readmission
Ability to analyze and consider clinical and non-clinical factors, including associated costs
High usability for medical staff