Think Beyond the Obvious

The real challenge is finding what was missed.

In an earlier post we explored how clinically diagnosed lung cancers often escape case finding. But the problem runs deeper: incomplete casefinding does not just miss patients—it reshapes the national picture of cancer itself.

When symptom-based encounters, LDCT screening and imaging reports with ambiguous terminology, or clinical diagnoses are not reviewed for reportability, thousands of cases vanish from population metrics that guide screening, treatment, staffing, and funding. Each missed reportable case distorts what hospital and national agencies believe about incidence, stage at diagnosis, and outcomes. Even a few cases for a single hospital add up to thousands of missed cases at the national level.

AI-powered case finding is not just about efficiency—it’s about restoring truth and credibility to the data and visibility to the patients who’s stories we must tell.

Complete case finding is more than compliance—it is the foundation of cancer surveillance.

To read the post “Close the Casefinding Gap: Lung Cancer,” click here. https://lnkd.in/g5vWcwe6