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Précising definitions as a way to combat overdiagnosis
Author(s) -
Rogers Wendy A.,
Walker Mary J.
Publication year - 2018
Publication title -
journal of evaluation in clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.737
H-Index - 73
eISSN - 1365-2753
pISSN - 1356-1294
DOI - 10.1111/jep.12909
Subject(s) - overdiagnosis , vagueness , harm , disease , medicine , intensive care medicine , medical diagnosis , psychology , pathology , social psychology , computer science , artificial intelligence , fuzzy logic
Roughly, overdiagnosis (ODx) occurs when people are harmed by receiving diagnoses (often accompanied by interventions) that do not benefit them, usually because the diagnosed conditions do not pose a threat to their health. ODx is a theoretical as well as a practical problem as it relates to definitions of disease. Elsewhere, it has been argued that disease is a vague concept and that this vagueness may contribute to ODx. In response, we develop a stipulative or précising definition of disease, for the specific purpose of decreasing or preventing ODx. We call this disease ODx , aimed at distinguishing cases where it would be beneficial to identify (and treat the condition) from those where diagnosis is more likely to harm than benefit. A preliminary definition of disease ODx is that X is a disease ODx iff there is dysfunction that has a significant risk of causing severe harm. This paper examines the 3 concepts in this definition, using a naturalistic account of function, a Feinbergian account of comparative harm, and a probabilistic understanding of risk. We then test the utility of this approach using examples of clinical conditions that are currently overdiagnosed.