Breast cancer risk prediction models’ adoption by Canadian providers - an in-depth qualitative comparative analysis

Abstract

The use of risk prediction models (RPMs) for breast cancer (BC) is expected to increase in the near future and is essential for BC risk stratification, which makes it crucial to better understand their adoption. To identify the conditions that impact the use of BC RPMs by Canadian healthcare professionals (HPs), a database of the clinical activities of 176 providers was used to perform statistical bivariate tests and qualitative comparative analysis. The results showed that training in BC genetics is essential for the use of BC RPMs, the proximity of genetic services is a relevant factor for users, and extended clinical experience impedes the use of such models. To increase the use of BC RPMs, two main solutions have emerged: targeting non-users and offering them training and more opportunities for inter-professional collaborations, and targeting experienced HPs with tools that provide them with a significant added value over the risk calculation.