OBJECTIVES : Evaluating changes to historical treatment costs is critical for healthcare professionals to make informed business decisions. However, real-world clinical and cost outcome data is challenging to use regularly without significant data science knowledge or resources. We sought to demonstrate the potential value in user-friendly analytics tools to identify drivers of costs and outcomes.

METHODS : The IBM Access and Value Connect solution was used to analyze a patient cohort of metastatic breast cancer (mBC) patients treated in the most recent 12, 36, and 60 months in the IBM MarketScan ® Commercial and Medicare Supplement Database. We used the interactive visual explorer tool to quickly (<15 minutes) determine the mean total per-patient-per-month (PPPM) cost associated with mBC overall and for select side effects by age group (45-54, 55-64, 65-74, and 75+) and generated histograms for mean total PPPM overall and for leukopenia and neutropenia by age group for each study period.

RESULTS : The mean total PPPM across all mBC patients ranged from $6,562 for the 75+ age group at 60 months to $14,201 for the 45-54 age group at 12 months. For those who experienced leukopenia, the mean total PPPM ranged from $10,319 for the 75+ age group at 60 months to $19,598 for the 45-55 age group at 60 months. Similarly, for those who experienced neutropenia the mean total PPPM ranged from $10,593 for the 65-74 age group at 60 months to $21,784 for the 45-54 age group at 12 months.

CONCLUSIONS : Our methods show that it is possible to make PPPM costs easily available without data science, clinical, or programming knowledge with interactive, visual analytics. Our results showed that in general PPPM costs are higher for younger patients overall and among those who experience leukopenia or neutropenia. This is likely due to the practice to aggressively treat younger patients.