Patients of a particular therapy were either discontinuing use of their brand or switching to a competitor’s brand after a single script. EVERSANA was brought in to identify the key drivers of a patient’s switch to a competitor’s brand or discontinuation of use of the brand. In addition, the client was looking for clarity on how hub efforts were affecting results.
Using predictive analysis and machine learning, EVERSANA’s team of experts developed a model to inform personas of patients who discontinued and switched, provided data-driven predictions for patients to inform hub action, and then tracked how hub performance improved, along with the impact on hub resource utilization.
As a result of this model:
- Hub costs were decreased by 40%
- Nurse utilization and overall call numbers decreased by 35%
- Hub app usage rose from 20% of patients to 35%.
- Total copay spend decreased by $80K, while assistance per patient rose by $50.