Evaluating data-driven breast surgery treatment path visualizations from registry and administrative data.

195 Background: Breast cancer patients face difficult decisions about their surgical care without a full understanding of their options. The learning health system goal is to use information from the care of prior patients to inform the care of future patients. We aim to apply this concept to generate data-driven surgical paths, develop interactive path visualizations to inform patients, and evaluate their impact.

METHODS: We used cancer registry and administrative CPT codes for women diagnosed with stage 0-III breast cancer between FY2010-14 at a comprehensive cancer center. We generated surgical event sequences and visualized them using interactive Sankey diagram path visualizations. We will run a prospective educational intervention this winter to evaluate their impact on the shared decision making process. A web-based application will be available to patients prior to, during, and after their surgical clinic visit; we will survey their reaction pre-visit, post-visit, and post-surgery.

RESULTS: 1556 patients had 1951 surgical events in the registry and 48% started their surgical care with a breast conserving surgery while 52% began with a mastectomy. Mastectomy paths are presented in Table 1. We have developed interactive visualizations for patients to view, will be conducting our prospective educational intervention this winter, and will be ready to present preliminary results in February.

CONCLUSIONS: We have been able to develop interactive, data-driven surgical path visualizations for breast cancer patients from cancer registry and administrative data. We will be conducting a prospective educational intervention to evaluate our implementation of this learning health system concept. [Table: see text].