[Risk, uncertainty and ignorance in medicine]

Exploration of healthy patients' risk factors for disease has become a major medical activity. The rationale behind primary prevention through exploration and therapeutic risk reduction is not separated from the theoretical assumption that every form of uncertainty can be expressed as risk. Distinguishing "risk" (as quantitative probabilities in a known sample space), "strict uncertainty" (when the sample space is known, but probabilities of events cannot be quantified) and "ignorance" (when the sample space is not fully known), a typical clinical situation (primary risk of coronary disease) is analysed. It is shown how strict uncertainty and sometimes ignorance can be present, in which case the orthodox decision theoretical rationale for treatment breaks down. For use in such cases, a different ideal model of rationality is proposed, focusing on the patient's considered reasons. This model has profound implications for the current understanding of medical professionalism as well as for the design of clinical guidelines.