ML-based Solution Reduced Patient
  • ML solution predicted on a weekly basis patients’ risk of non-compliance with treatment regimen
  • Pre-emptive intervention by Patient Services led to 18% increase in compliance across all of client’s brands. This translated to $74M incremental annual revenue
  • The Compliance Optimizer solution continued to be successfully deployed for the 3rd year post launch
Compliance measures how closely a patient follows the prescribed frequency and dosage of a therapy. Decline in compliance had significant adverse impact on revenue for the client, a large rare-disease Biotech. However, past interventions occurred when patients had already discontinued therapy.
  • Build a dynamic Patient Journey solution with realtime tracking of KPIs
  • Enable the Patient Support Program (PSP) to proactively address refill or shipment delays and reimbursement hurdles which were causing patients to drop off therapy
All plausible drivers for patients’ non-compliance were identified based on realtime tracking by PSP. Multiple AI/ML classification techniques (Logistic Regression, Random Forest, Gradient Boosting, SVM) were comparatively evaluated using cross-validation accuracy metrics. The final model predicted each patient’s non-compliance risk on a weekly basis with an accuracy greater than 80%.
The weekly list of high-risk patients from a non-compliance perspective were targeted for pre-emptive patient-specific intervention by the Patient Services team leading to a turnaround in compliance rates across brands.