When More Information Stops Helping: Satisficing in Radiology

Area of Science:

• Radiology and Medical Imaging
• Health Economics
• Decision Science

Background:

• Physicians face a conflict between avoiding missed diagnoses and preventing unnecessary interventions.
• Overuse of advanced imaging leads to inefficiencies, costs, and patient harm, often due to incidental findings and external pressures.

Purpose of the Study:

• To advocate for a shift from information maximization to a satisficing framework in medical imaging.
• To define when additional imaging information is no longer clinically necessary.

Main Methods:

• The article discusses the theory of bounded rationality and contrasts satisficing with the Value of Information (VOI) framework.
• It proposes practical implementation strategies including Clinical Decision Support Systems (CDSS) and minimalist protocols.

Main Results:

• The relationship between imaging data volume and clinical utility is nonlinear, with diminishing returns.
• Satisficing aims to stop information acquisition when it is sufficient for safe and effective action, unlike VOI which weighs incremental costs and benefits.

Conclusions:

• Quality in radiology should be redefined by appropriate management guidance rather than data volume.
• Implementing satisficing requires CDSS, clear protocols, and safety measures to prevent diagnostic errors while optimizing resource use.