Measuring improved patient choice

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Abstract
Patient decision support (PDS) tools or decision aids have been developed as adjuncts to the clinical encounter. Their aim is to support evidence‐based patient choice. Clinical trials of PDS tools have used an array of outcome measures to determine efficacy, including knowledge, satisfaction, health status and consistency between patient choice and values. This paper proposes that the correlation between ‘subjective expected utility’ (SEU) and decision may be the best primary endpoint for trials. SEU is a measure usually used in behavioural decision theory. The paper first describes how decision support tools may use decision analysis to structure the presentation of evidence and guide patient decision‐making. Uses of expected utility (EU) are suggested for evaluating PDS tools when improving population health status is the objective. SEU is the theoretically better measure when internal consistency of patient choices is the objective.