Managing long term relationships with members is vital to every healthcare payer. This not only allows them to maintain a sustainable stream of premiums but also enables them to coordinate the health of their members by understanding their unique conditions and preventing avoidable diseases. Disenrollments hurt both the members themselves and the payer. When members churn, payer’s are unable to continue their coordination of care, reducing the premiums they earn, but also resulting in worse health outcomes. Over 30% of members that churn from their health plans end up skipping doses or stopping medication. This potentially leads to a greater amount of avoidable health conditions that increase the overall cost of healthcare due to rising hospitalization and administrative costs. Not to mention, churn impacts payers even more when done on entire groups or employers.
AI helps you reduce disenrollment, either on the member or employer level, by predicting ahead of time which are likely to churn. By learning patterns among historical churn and its associated characteristics, AI is able to create forward looking predictions on which current entities have the highest risk of churn. AI also informs your care managers of the top statistical reasons why, enabling them to implement preventative measures unique to every member or employer’s condition. This helps you prevent churn and not only improve the health outcomes of individual members, but also maintain your relationships with enterprises who have significant contributions to your premiums.
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Healthcare companies are using machine learning and AI to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from readmission risk and occupancy rates to marketing, in order to make data-driven decisions that lead to increased profitability.