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New Technologies in Personalized Decision Support to Enhance Patient Choice: Applications and Challenges
Abstract
Medical decisions are difficult when there are two or more reasonable options and each option has good and bad features that different people may value differently because of differences in health, risk factors, preferences, or values. Personalized decision support tools are being developed in many areas, but two particularly promising areas are patient decision aids and Risk Prediction Models (RPMs). These personalized decision support tools can help patients and/or providers make better decisions about preventing, managing, or treating disease, taking into consideration specific aspects of an individual patient that distinguish them from an ’average’ patient or the population at large. Decision aids tend to focus on individual differences in preferences and values, whereas RPM’s focus on individual differences in clinical, biological, and behavioral risk factors. There are tremendous opportunities with both approaches, and both have been shown to be able to improve clinical judgment and decision making. Decision support tools are needed that provide personalized service that addresses important individual differences in biology, values, and preferences, and that targets the provider-patient dyad.
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