Abstract
Unrestrained enthusiasm for "wellness" testing has spawned a marketplace of direct-to-consumer genomics, broad laboratory panels, wearable sensors, and whole-body imaging that outpaces supporting evidence. In the USA, such low-value diagnostics account for over $100 billion in annual downstream US costs while exposing patients to false-positive cascades, anxiety, and bias. We synthesize data across omics, sensors, imaging, and lifestyle medicine to propose a three-tier precision health framework that leverages AI population assessment with high-value testing based on pre-test probability: Tier 1 high-sensitivity screens, Tier 2 targeted confirmation, and Tier 3 precision interventions. Adopting this model could markedly reduce unnecessary medical exams and redirect resources toward proven preventive measures.