In the realm of pharmaceuticals, overt hepatic encephalopathy (OHE) poses a significant challenge. Often underdiagnosed and un-coded, this condition is associated with cirrhosis and can lead to acute patient episodes and poor outcomes. The client, a leading pharma company, recognized the urgency of addressing this issue. They sought a solution to predict which patients were likely to develop OHE and, crucially, how to identify the healthcare providers (HCPs) caring for these patients.

Our partnership with the client led to the development of an AI-driven predictive model.

• Patient Scoring: The AIML model scored patients based on their likelihood of being target patients for OHE.
• Physician Linkage: Patients meeting a certain probability threshold were then linked to their relevant physicians.

By uncovering previously undiscovered HCP opportunities, the predictive target list achieved a staggering 250% increase in Rx volume. The AIML model transformed the client's approach, demonstrating that data-driven insights can revolutionize healthcare strategies.

Our partnership with the client led to the development of an AI-driven predictive model via our solution, Dynamic HCP Profiling and Targeting.