Model-based patient adherence classification and intervention

Abstract

Systems and methods for using predictive modeling to improve patient adherence to prescription medication regimens are provided. Training data may be generated using historical prescription adherence data associated with a patient population. A prescription adherence machine learning model may be trained using the training data, and the trained model may be applied to current prescription adherence data associated with a patient to predict a likelihood that a proportion of days that the patient will be covered by a prescribed medication will be below a threshold value over a calendar year. A patient risk score may be generated for the patient based at least in part on the predicted likelihood that the proportion of days covered by the prescribed medication will be below the threshold value. Based on the patient's patient risk score, the patient may be automatically contacted for intervention.