Luh, Join Y.

Retrieval-augmented generation (RAG) is rapidly emerging as a transformative paradigm for large language models (LLMs), especially in high-stakes domains like oncology that demand precision, factual grounding, and up-to-date knowledge. By pairing LLMs with external knowledge repositories, RAG systems explicitly ground model outputs in relevant retrieved documents, helping to reduce hallucinations and ensure responses reflect current evidence. In oncology, where clinical knowledge evolves continually with new research and drug approvals, RAG offers a way to integrate the latest data (e.g., trial results, guidelines, genomic databases) into decision-making. This review synthesizes the technical foundations of RAG, including its architecture and key components, and examines current applications in oncology such as clinical decision support, patient education, radiology reporting, pathology analysis, and genomics-driven precision medicine. We highlight recent studies that demonstrate RAG’s potential—for instance, improving treatment recommendations by incorporating genetic profiles and literature, and enhancing diagnostic accuracy by integrating guidelines. We also discuss emerging developments like multimodal RAG (combining text with imaging or other data), ensemble model approaches, and new explainability tools that trace model outputs to sources. Finally, we critically analyze the limitations and challenges of deploying RAG in healthcare, including computational costs, retrieval errors, noise or conflicts in retrieved information, and ethical and regulatory considerations. While RAG-based systems show promise in augmenting oncologists’ expertise with timely knowledge, careful implementation, high-quality curation of knowledge bases, and human oversight will be crucial for safe and effective adoption in clinical practice.

98 Background: Prior authorization (PA) purports to control costs and ensure adherence to evidence-based guidelines but negatively impacts cancer care. Radiation oncology (RO) represents a minority of overall cancer spending yet bears a disproportionately high PA burden. Limited research exists on the effects of PA on patient outcomes and administrative workload within RO clinics. Methods: From 9/2024 to 10/2024, an online survey was open to U.S. members of the American Society for Radiation Oncology assessing experiences with PA including disposition (approval/denial/appeal including peer-to-peer [P2P] review) and perceived impact on patient care and administrative workload. Outcomes included treatment delays, changes from recommended treatment, and patient event including hospitalization, ED visits, permanent disability, or death. Descriptive statistics evaluated responses. Results: Of 736 responding radiation oncologists (16% response rate), 83% reported a rise in PA over the past three years, with 58% noting the burden has increased greatly. In the past year, 50% reported that more than half of their cases required PA, with a median approval rate of 75% and median overturn rate of 82% for denials. For more than half of their cases, nearly half of physicians (43%) noted that P2P was a futile effort to overturn PA denials due to insurance policies. Most (75%) reported that PA resulted in their practice needing to reallocate staff; 91% reported worsening burnout due to PA. P2P reviews were particularly burdensome, averaging 1.65 hours per week. A third (30%) reported that PA requirements had caused serious complications for their patients, including 7% who reported PA had contributed to patient death. Almost all (91%) reported PA-related treatment delays for some of their patients, with 58% indicating average delays of ≥5 days. Most (81%) reported that at times they had to use radiation techniques they considered less optimal due to PA, including 58% who were forced to deviate from national guidelines. The most common reasons for not appealing a PA denial were anticipated delays (73%), perceived futility based on prior PA experiences (62%), and administrative burden (45%). Conclusions: The administrative and clinical burdens associated with PA have significant implications for patient care, physician well-being, and healthcare resource allocation in RO. Treatment delays, compromised therapies, and adverse patient outcomes are commonly reported and underscore the need for PA reform to improve patient outcomes, reduce physician burnout, and improve efficiency.