Incidental findings AI with follow-through built in.

Incidental findings are unexpected potentially clinically significant findings identified on imaging performed for another reason. Findings include lung nodules, pancreatic lesions, thyroid nodules, and coronary artery calcifications. Studies estimate that up to 30% of imaging exams include an incidental finding, yet nearly 70% of those findings are not followed up on appropriately.

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This gap exists because manual processes, spreadsheets, or EHR inboxes are often relied upon to manage incidental findings. These fragmented workflows make it difficult to consistently identify findings across radiology reports, apply guideline-based follow-up recommendations, and ensure patients return for care. As a result, many actionable findings fall through the cracks—leading to delayed diagnoses, patient safety risk, and lost downstream care opportunities.

Eon’s AI identifies incidental findings within radiology reports, extracts clinically relevant details, and generates evidence-based follow-up recommendations. When paired with workflow automation and care management services, Eon helps health systems move beyond detection alone—ensuring findings are systemically captured, communicated, and continuously monitored so that patients return for timely care and that cancer and other serious conditions are identified at the earliest possible stage.

Eon supports a broad range of incidental findings and screening programs, including lung screening and incidentals, breast screening and incidentals, aortic aneurysms, coronary artery calcification, pancreas, thyroid, liver, and kidney findings. The platform is designed to scale across multiple disease states within a single enterprise solution, allowing health systems to manage incidental findings consistently across service lines.

Unlike EHR modules or AI tools like image analysis that focus primarily on detection, Eon is purpose-built to manage the full lifecycle of incidental findings. Eon combines AI-driven identification, smart validation, evidence-based care plans, and long-term follow-up tracking—so patients don’t fall through the cracks after a finding is identified. Eon integrates directly with leading EHRs, including Epic, to enhance existing workflows rather than replace them.

Eon automatically generates evidence-based follow-up recommendations tailored to each patient’s specific imaging findings and risk factors. Care plans align with widely adopted clinical guidelines, including Fleischner Society Guidelines for lung nodules, ACC/AHA guidelines for aortic aneurysms and coronary artery calcification, and pancreatic cyst guidelines from ACG, ACR, AGA, IAP, and European guidelines. These intelligent care plans adapt over time as new imaging or clinical events occur, supporting consistent, guideline-aligned decision-making without added manual effort across multiple disease states.

By automating the identification, validation, and tracking of incidental findings, Eon significantly reduces the manual workload placed on care teams. Specifically with Eon’s Care Management Services, it allows clinicians to focus on higher-complexity cases while ensuring lower-risk patients are still managed appropriately and at scale. Health systems use Eon to improve patient adherence, reduce leakage, and grow service line volume—without increasing headcount.