Key result
AI-assisted centralized navigation is linked to a ~43% lung cancer screening rate, outperforming national benchmarks.
Why the study?
Despite mortality benefits of LDCT for lung cancer screening, national uptake remains stagnant due to primary care burden and rural geographic disparities.
Does a centralized navigator-led and AI-assisted platform improve lung cancer screening rates and early detection in eligible high-risk patients?
Observational
Yes
Does a centralized navigator-led and AI-assisted platform improve lung cancer screening rates and early detection in eligible high-risk patients?
A centralized, AI-assisted navigation model effectively doubled the national benchmark for lung cancer screening uptake and improved early-stage detection.
Answers are grounded in this paper and cite their sources.
May support testing centralized navigation-AI models in other systems; leaves open effects on mortality and generalizability.
109 Background: Despite the known mortality benefits of low-dose computed tomography (LDCT) for lung cancer screening (LCS), national uptake remains stagnant (~15-20%). Significant barriers include primary care burden and geographic disparities in rural areas. This study evaluates the impact of a centralized navigation model combined with AI-assisted electronic health record (EHR) alerts on LCS rates and stage distribution within a large integrated health system. Methods: We conducted a retrospective analysis of LCS performance across a 16-hospital system (OSF HealthCare) from 2019 to 2025. The intervention included: 1) centralization of LCS navigators to manage registries and scheduling, and 2) implementation of AI-assisted EHR alerts to identify eligible high-risk patients. Outcome measures included absolute LDCT volume, system-wide screening rates, and AJCC staging at diagnosis. Benchmarks were derived from American Lung Association (ALA) national and state (Illinois) data. Results: The system-wide LCS screening rate increased from 18.2% in 2020 to 42.8% in 2025, significantly outperforming the projected 2025 US national average (19.5%) and the Illinois state average (20.8%). Absolute screening volume nearly doubled, rising from 2,257 scans in 2019 to 4,108 in 2025. Notably, the program demonstrated high resilience during the 2020 COVID-19 pandemic, maintaining 98.5% of prior-year volume compared to a 5% national decline. Early-stage detection (Stage I) showed the greatest improvement in rural facilities, with some centers seeing a +21% increase in Stage I diagnoses over the study period. Conclusions: A centralized, technology-enabled navigation model effectively doubles the national benchmark for lung cancer screening uptake. By removing administrative burdens from primary care and utilizing AI-assisted EHR alert system to close the "eligibility gap", this model provides a scalable blueprint for improving early cancer detection and addressing rural health inequities. OSF HealthCare lung cancer screening performance vs. national benchmarks (2020–2025). Year OSF Annual LDCT Volume OSF Screening Rate (%) National Screening Rate (%)* Performance Gap (Percentage Points) 2020 2,223 18.2% 14.5% +3.7% 2021 2,647 21.4% 14.8% +6.6% 2022 3,280 27.8% 15.5% +12.3% 2023 3,406 33.6% 16.0% +17.6% 2024 3,522 38.2% 18.2% +20.0% 2025 4,108 42.8% 19.5% +23.3% *National benchmarks based on American Lung Association "State of Lung Cancer" annual reports and CDC/ACS prevalence estimates.
No takes yet. Share an insight, caveat, or question.
Zhang et al. (2026) conducted an observational in Lung cancer screening. Centralized navigation model combined with AI-assisted EHR alerts vs. US national average was evaluated on System-wide lung cancer screening rate. A centralized navigation model with AI-assisted EHR alerts increased the system-wide lung cancer screening rate to 42.8% in 2025, outperforming the projected US national average of 19.5%.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: