Variability in hospital treatment costs: a time-driven activity-based costing approach for early-stage invasive breast cancer patients

OBJECTIVES: Using a standardised diagnostic and generic treatment path for breast cancer, and the molecular subtype perspective, we aim to measure the impact of several patient and disease characteristics on the overall treatment cost for patients. Additionally, we aim to generate insights into the drivers of cost variability within one medical domain. DESIGN, SETTING AND PARTICIPANTS: We conducted a retrospective study at a breast clinic in Belgium. We used 14 anonymous patient files for conducting our analysis. RESULTS: Significant cost variations within each molecular subtype and across molecular subtypes were found. For the luminal A classification, the cost differential amounts to roughly 166%, with the greatest treatment cost amounting to US$29 780 relative to US$11 208 for a patient requiring fewer medical activities. The major driver for these cost variations relates to disease characteristics. For the luminal B classification, a cost difference of roughly 242% exists due to both disease-related and patient-related factors. The average treatment cost for triple negative patients amounted to US$26 923, this is considered to be a more aggressive type of cancer. The overall cost for HER2-enriched is driven by the inclusion of Herceptin, thus this subtype is impacted by disease characteristics. Cost variability across molecular classifications is impacted by the severity of the disease, thus disease-related factors are the major drivers of cost. CONCLUSIONS: Given the cost challenge in healthcare, the need for greater cost transparency has become imperative. Through our analysis, we generate initial insights into the drivers of cost variability for breast cancer. We found evidence that disease characteristics such as severity and more aggressive cancer forms such as HER2-enriched and triple negative have a significant impact on treatment cost across the different subtypes. Similarly, patient factors such as age and presence of gene mutation contribute to differences in treatment cost variability within molecular subtypes.