JMIR Publications

ABSTRACT

Population screening developed in an era when diagnostic information was constrained by the cost of testing, laboratory capacity, specialist interpretation, and healthcare infrastructure. Home diagnostics, point-of-care testing, wearable technologies, artificial intelligence (AI), and connected digital health systems are changing these conditions. We introduce the concept of diagnostic abundance to describe a transition in which the generation and availability of health-relevant diagnostic information are becoming progressively less constrained by traditional limitations of location, infrastructure, cost, and specialist interpretation. Diagnostic abundance does not imply universal or equitable access; diagnostic abundance and diagnostic scarcity can coexist between countries, within health systems, and across populations. Rather, the concept highlights a shift in the central problem facing screening: from obtaining diagnostic information toward determining which information is meaningful, trustworthy, actionable, and beneficial. We argue that increasingly abundant but fragmented diagnostic information creates opportunities for earlier detection, risk-based screening, expanded participation, and stronger public health intelligence, while also intensifying risks of overdiagnosis, false-positive findings, unnecessary follow-up, inequity, privacy loss, and health-system overload. To translate diagnostic abundance into public health value, we propose a diagnostic abundance value chain linking data generation to action and identify three foundations for responsible implementation: governance, interoperability, and enabling infrastructure. The next generation of screening policy should therefore focus not only on what can be screened, but on how increasingly abundant diagnostic information can be governed, integrated, interpreted, and translated into equitable public health benefit.