Part 7: Treatment Adherence
This new series focuses on how Machine Learning, Natural Language Processing, and Robotic Process Automation are changing the face of business. Each post contain a specific use case, the business value derived, and the technology synopsis to achieve the outcome.
The goal of Treatment Adherence is to create a strategy to identify members with low adherence to their treatment plan and a create value-based partnership with care-providers to improve outcomes. Ensemble machine learning techniques are used to predict a patient’s level of adherence.
Supervised Machine Learning models are combined with unsupervised models to predict patient-level adherence down to the month. Machine learning models are built in R, and Tableau is used to visualize insights.