Multicriteria Decision Support Would Avoid Overdiagnosis and Overtreatment
Rajput, Vije Kumar;
Dowie, Jack;
Kaltoft, Mette Kjer;
(2020)
Multicriteria Decision Support Would Avoid Overdiagnosis and Overtreatment.
Studies in Health Technology and Informatics.
ISSN 0926-9630
DOI: https://doi.org/10.3233/shti200717
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Population-level studies confirm the existence of significant rates of overdiagnosis and overtreatment in a number of conditions, particularly those for which the screening of asymptomatic individuals is routine. The implication is that the possibility of being overdiagnosed and/or overtreated must be mentioned as a possible harm in generating informed consent and participation from the individual invited to be screened. But how should the rates of such preference-insensitive population-level phenomena be introduced into preference-sensitive individual decision making? Three possible strategies are rejected, including the currently dominant one that involves presenting the rates relevant to overdiagnosis and overtreatment as discrete pieces of information about a single criterion (typically condition-specific mortality). Extensive quotation from a review of cancer decision aids confirms that processing this complex and isolated information is not a practical approach. However, the task is unnecessary, since an outcome-focused multicriteria decision support tool will incorporate the effects of overdiagnosis and overtreatment – along with the effects of any underdiagnosis and undertreatment.