The Christ Hospital

Incidental lung findings buried in radiology reports frequently go untracked, delaying cancer diagnosis until later stages when treatment options are more limited. Without systematic AI-driven review, patients with early indicators may not receive timely follow-up.

Epic's Art AI was deployed to automatically extract incidental findings from radiology results and trigger follow-up workflows, ensuring patients with potential lung cancer indicators receive structured next steps within the EHR.

The Christ Hospital achieved a 69% early-stage detection rate for lung cancer, compared to the national average of 46%. This represents significantly more patients diagnosed at earlier, more treatable stages of the disease.

• Systematic AI review of radiology text reports can surface critical findings that would otherwise fall through the cracks
• Automated follow-up triggers embedded in the EHR improve care continuity without adding manual workload
• EHR-integrated AI can lift early detection rates substantially above national benchmarks