Breast Cancer Coverage From Every Angle
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Identifying Educational Needs of the Multidisciplinary Cancer Team in the Treatment of Metastatic Breast Cancer

According to a global patient survey, many women with breast cancer, and especially those with metastatic disease, report that most aspects of their lives have changed in a negative way. Moreover, patients note that oncologists are not addressing their psychosocial needs and do not communicate effectively regarding medical treatment, prognosis, health-care costs, insurance coverage, and quality-of-life and survivorship issues. To determine how the breast cancer care team can improve the delivery of care for women with advanced breast cancer, researchers used a number of validated tools to assess knowledge, practice, and attitudes among 186 physicians (surgical, medical, and radiation oncologists; pathologists; and palliative care specialists) and 2 nurse practitioners across 36 states. Analysis of results revealed five key practice performance gaps: (1) selecting optimal treatment; (2) personalizing therapy; (3) monitoring metastatic breast cancer; (4) engaging in effective communication; and (5) balancing patient access and time.

Findings suggest that some medical oncologists need additional education about making treatment decisions for specific patient subpopulations, such as premenopausal and postmenopausal women, patients with comorbidities, and others with unique challenges. The use of clinical vignettes indicated that medical oncologists may not consider the entire patient’s clinical condition, including comorbidities, when evaluating possible treatment strategies. Medical oncologists rated high cost to patients, patients’ lack of insurance coverage, and lack of time to learn about new therapies as their top three barriers to adopting new therapies, suggesting that patient-access issues are a significant concern. The full findings from this study shed light on areas that cancer care teams can improve, even when they are not internally perceived by the teams as subpar.