HCB News: What challenges do you foresee in the widespread adoption of AI imaging technologies in specialty practices?
SN: One of the primary challenges in the widespread adoption of AI imaging technologies in specialty practices is ensuring that these new medical technologies are properly reimbursed. While it's encouraging that the American Medical Association (AMA) has introduced new coding guidelines for AI products, there is still a significant amount of work needed to guarantee that these innovations are accessible to all. Reimbursement frameworks often lag behind technological advancements, creating a barrier for the integration of cutting-edge AI solutions into everyday clinical practice. Without adequate reimbursement, healthcare providers may be hesitant to invest in and adopt these technologies, limiting their availability to patients. To address this, it’s crucial that insurance companies, policymakers, and medical institutions collaborate to develop comprehensive reimbursement policies that reflect the value and benefits of AI in improving patient care. This includes educating stakeholders on the effectiveness of AI technologies and ensuring that reimbursement rates are fair and incentivize adoption. By doing so, we can ensure that the benefits of AI imaging technologies are fully realized and accessible to patients across all demographics and regions, ultimately improving our healthcare system.

HCB News: What are some key considerations for healthcare providers looking to implement AI-powered imaging technologies in their practices, particularly in the context of prostate cancer care?
SN: Data quality has to come first. When acquiring information to diagnose patients, it’s imperative the emphasis is on quality of the data. AI technologies must be trained and validated on data sets that are representative of the real world. In prostate cancer, we can’t overlook the use of AI to guide targeted prostate biopsy. It’s considered the standard of care in clinical guidelines, but it’s not always used in diagnostics and treatment planning for a variety of reasons. We know, however, this gets the patients the best diagnosis. Using AI to help guide targeted biopsy can enable more precise prostate cancer care that avoids unnecessary downstream procedures.

HCB News: How can healthcare practices and institutions collaborate to integrate AI imaging technology into existing workflows and treatment protocols?
SN: The biggest hurdle currently is data standardization and streamlined IT processes. Datasets and formats need to be standardized to be able to efficiently treat patients and appropriately benchmark different algorithms and products. With more organizations integrating or developing their own AI, we are seeing a growing need for standardized data formats to ensure that these tools are interoperable and their outcomes are comparable. Patients and providers will run into roadblocks in their care pathways if everyone can’t access the same systems.

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