But she also cautioned against the “dissemination of technology without adequate evidence, validation, and training.”
Schilsky offered several scenarios that could be considered to improve patient access to expertise and technologies in oncologic imaging and pathology. These scenarios included the following:
- Building a specialized workforce, potentially by creating an integrative medical specialty in diagnostic oncology, that trains individuals in pathology, radiology, cancer biology, and new computational methods involved in these fields;
- Supporting a less specialized workforce through the use of clinical decision support tools and clinical pathways, facilitated by advances in AI and machine learning; and
- Expanding capacity in community care settings and promoting access to oncologic expertise through programs such as Project ECHO.
“It may be some combination of these activities that is the optimal strategy, and it is unlikely that any one particular strategy will work best in every clinical venue,” Schilsky noted. He added that the primary challenges in improving cancer diagnosis and care are primarily cultural and organizational, rather than technological: “It’s rare in so many areas of medicine that technology is the actual barrier to implementation. It’s almost always a cultural or organizational barrier, and we need to think about overcoming those barriers.” He also pointed out that “much of what we do in medicine is determined by our payment models, and a lot of patient support services in oncology are typically not well reimbursed, even though they are essential to delivering high-quality care to cancer patients.” Hricak agreed, and said the next steps are to operationalize and support these strategies to improve cancer diagnosis and care.
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