Use Cases

Predicting Patient Readmission Risk


It is challenging to keep track of patients after they have been released from the hospital. This lack of contact may negatively affect the patients’ health, leading to their readmission.


LogicPlum’s built models can efficiently and effectively detect those patients whose readmission likelihood is high, and their problems (chronic disease, physical deterioration, an abusive relationship, etc.). Organizations can use LogicPlum’s platform to create models based on a variety of data features ( e.g., demographics, medical records, diagnosis). These AI models can then help provide proactive measures allowing for healthcare providers to help avoid readmission, save on costs, and improve the quality of health care.

Why LogicPlum

LogicPlum provides a platform that helps to automatically create process models, which, when used with patients’ data, can estimate their readmission risks before they are discharged.

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