Identifying patterns of breast cancer care provided at high-volume hospitals: a classification and regression tree analysis.

There is a growing body of literature linking hospital volume to outcomes in breast cancer. However, the mechanism through which volume influences outcome is poorly understood. The purpose of this study was to examine the relationship between hospital volume of breast cancer cases and patterns of processes of care in a population-based cohort of Medicare patients. A previously described and validated algorithm was applied to Medicare claims for newly diagnosed breast cancer cases in 2003 to identify potential subjects. Breast cancer patients were recruited to participate in a survey study examining breast cancer outcomes, and data were merged with Medicare claims and state tumor registries. Hospital volume was divided into tertiles. A Classification and Regression Tree (CART) model was performed to look for statistically significant relationships between patterns of processes of care and hospital volume. Using CART analysis, eight patterns of care were identified that differentiated breast cancer care at high- versus low-volume hospitals. Sentinel lymph node dissection (SLND) was the single process of care that demonstrated the greatest differentiation across hospitals with differing volumes. Four patterns of care significantly predicted that a patient was less likely to be treated at a high-volume hospital. Our study demonstrates differences in patterns of processes of care between low- and high-volume hospitals. Hospital volume was associated with several patterns of care that reflect the most current standards of care, particularly SLND. Greater adoption of these patterns by low-volume hospitals could improve the overall quality of care for breast cancer.