Increase Early Detection + Stage Shift with AI

See how an AI-driven approach helped Sarasota Memorial Health (SMH) double the state and national average rates of early-stage lung cancer detection.

75%

early-stage lung cancer diagnosis rate (2025)

100x

increase in incidental findings managed

92%

adherence rate among high-risk patients

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THE CHALLENGE

Scale early detection and follow-up for lung cancer

To build on a strong early detection foundation, SMH sought to standardize incidental findings management.

Opportunity Areas

  • Incidental Lung Findings: Elective screenings were only capturing a percentage of the at-risk population.
  • High Imaging Volumes: With 430k+ radiology exams each year, clinical details for incidental findings were often buried in radiology reports.
  • Standardization Goal: SMH aimed to ensure patients received timely follow-up care regardless of how a lung finding was discovered.

THE SOLUTION

Deploy a tech-enabled approach to longitudinal care

The health system implemented Eon to expand coordination, follow-up, and standardization.

Key Enablers

  • AI-Powered Platform: SMH deployed Eon to support incidental pulmonary nodule management.
  • Real-Time Analysis: The technology analyzes radiologist reports, extracting meaningful information and identifying at-risk patients early.
  • Automated Tracking: Using established clinical guidelines, SMH tracks patients over time, alerting staff to anticipated care gaps.

THE RESULT

Diagnose more cancers earlier and drive adherence

SMH's screening and incidentals team diagnosed 75% of lung cancers at Stage I or II in 2025.

“We knew there was more we could do for our community. We just needed a reliable way to flag incidental findings in real time so we could proactively reach all of the people who could benefit from earlier evaluation.”

Amie J. Miller, MSN, APRN, Program Lead