With the promise of artificial intelligence (AI) and its potential to positively impact healthcare, comes the challenge of how to assess the feasibility and value associated with implementation of AI tools.

Although we have made some progress in ways of increasing clinical trial access to underserved communities, inequities persist. Education in this area is important because increasing access to clinical trials will have a positive impact on patient outcomes and help address current disparities in cancer treatment.

Intersectional stigmas in cancer care can exacerbate disparities by compounding the challenges faced by individuals who belong to multiple marginalized groups, leading to inequities in access, treatment, and outcomes. There is often a lack of consistent implementation of screening and support services that address the unique needs of marginalized patients, resulting in disparities in early detection, treatment, and follow-up care.

Patient navigation is highly variable; therefore, it is important to understand the factors that contribute to program success. It is also timely given the expansion of reimbursement for these types of services, as programs are looking at the sustainability of their programs and examining ways to better build or refine existing services.