OmegaCare, a renowned pharmaceutical company, was unable to gain the required insights for their drug compensation process. They lacked the needed visibility into how their drug reimbursement system was performing as per profitability metrics. The company faced difficulties while analyzing data across various pharmacy benefit managers (PBMs). While tracking a huge volume of transaction data, their staff came across various challenges. As such, OmegaCare approached Clarion with three specific requirements:
AI industry experts at Clarion helped OmegaCare build and implement a clustering-based analytics engine. This solution enabled automated isolation of NDCs by profitability and provided valuable and actionable insights for strategic decision-making. Our team aggregated, cleaned, normalized, and eliminated potential outliers from the historical data. K-means clustering and the elbow method were used to segment NDCs and form accurate clusters. Moreover, advanced Python libraries, such as Plotly and Streamlit to build interactive dashboards.
The newly developed AI-embedded clustering solution helped OmegaCare identify frequent PBM-NDC pairs that showcased high margins. The company was able to experience various valuable business outcomes, including:
Know how Clarion’s AI-powered clustering solution helped OmegaCare better discover profitability patterns within their drug reimbursement process and ensure long-term business success. Explore our strategic consulting, implementation strategy, and technology expertise in detail.