Personalized Decision Making -- A Conceptual Introduction
This work addresses the problem of making better decisions for individuals in fields like healthcare or policy, but it is incremental as it builds on existing concepts without introducing new methods.
The paper clarifies the distinction between personalized and population-based decision making, showing that personalized approaches lead to more informed decisions by combining experimental and observational studies to improve decisions over experimental studies alone.
Personalized decision making targets the behavior of a specific individual, while population-based decision making concerns a sub-population resembling that individual. This paper clarifies the distinction between the two and explains why the former leads to more informed decisions. We further show that by combining experimental and observational studies we can obtain valuable information about individual behavior and, consequently, improve decisions over those obtained from experimental studies alone.