CONTEXT:

A client with an oncology portfolio sought to improve market access for their new twice-monthly injectable product. A comprehensive analytics model was developed to segment sub-populations based on usage statistics. This approach helped demonstrate the product’s value to payors by focusing on the most appropriate patient population.

RESOLUTION:

Our data scientists identified target patient populations by building models using a single payor dataset. The model was validated through analysis of medical cost offsets. Findings indicated that the twice-monthly injectable regimen delivered greater value to patients compared to those with intermittent compliance. SAS and R were used to create waterfall, swimmer, and spider plots, enabling a deeper interpretation of the results.

RESULT:

The solution was delivered in phased milestones. By adhering to best practices in programming, we minimized errors and ensured high data quality. This, in turn, led to the generation of high-quality analytical outputs that supported meaningful insights and data interpretation.