Predictive Adherence Modeling
Using machine learning and data analytics to predict which patients are at risk for medication non-adherence.
Predictive adherence modeling uses machine learning algorithms and data analytics to predict which patients are at risk for medication non-adherence. These models analyze patient demographics, medication history, prescription patterns, and other factors to identify patients who may need additional support or interventions to improve adherence. Early identification of adherence risks enables proactive interventions, such as patient education, reminders, or medication therapy management, to improve outcomes.
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