Physicians operate at the intersection of 2 conflicting imperatives: the clinical mandate to avoid missed diagnoses and the ethical requirement to avoid unnecessary interventions. While advanced imaging can reduce diagnostic uncertainty, overuse introduces systemic inefficiencies, financial waste, and physical harm. This article argues that the solution lies in transitioning from an information maximization mindset to a satisficing framework, rooted in the theory of bounded rationality. Beyond biological risks, additional imaging often identifies insignificant incidental findings, triggering diagnostic cascades and psychological distress. Over-ordering may be motivated by defensive medicine, patient satisfaction pressures, and financial conflicts of interest. A satisficing framework clarifies when additional information is no longer needed. When satisficing, one stops acquiring information once current information is sufficient for action, whereas under a Value of Information (VOI) framework, one stops when the expected incremental benefit of additional information no longer exceeds its incremental costs and harms. Both frameworks reflect that the relationship between clinical utility and imaging data volume is nonlinear; eventually, incremental contributions diminish while cumulative costs continue to rise. Putting this approach into practice requires leveraging Clinical Decision Support Systems (CDSS), minimalist protocols, and increased visibility regarding opportunity costs. Robust safety protocols, including departmental reviews of exception rates and peer reviews, can be used to ensure that satisficing does not lead to increased diagnostic errors. Ultimately, quality in radiology should be defined by whether imaging appropriately informs management, rather than by the volume of data gathered. The goal is to provide the information necessary to act safely and effectively while recognizing when to stop.
U.S. healthcare spending has remained persistently high despite repeated efforts at correction. This essay offers a structural explanation. Waste, excess prices, and administrative complexity matter, but much spending growth reflects durable features of the sector that cannot be readily eliminated. Baumol's cost disease provides the core framework: in labor-intensive services with limited productivity gains, costs rise because wages in them must keep pace with more productive sectors. Medical technology more often expands capacity, utilization, and clinical expectations than it reduces labor inputs. The U.S. physician training pathway is unusually long and expensive, and federal residency caps have artificially constrained physician supply, reinforcing a high compensation floor. The healthcare and social assistance sector functions as a de facto industrial policy, as it is the nation's largest employment sector and the top employer in 38 states, making aggregate cost compression politically costly in ways that are structural, not incidental. Domestic multiplier effects deepen that political durability. Five distinctively American features further limit centralized cost control: population scale and decentralization, higher per capita income, a heavier chronic disease burden, the absence of a national health technology assessment authority, and weaker redistributive institutions. Given the constraints, the aspiration to make American healthcare dramatically cheaper without major disruption is unrealistic. A more credible agenda is to foster local stewardship within a structurally high-cost system.
