Surveillance in Barrett's Esophagus: Lessons from Behavioral Economics

Several observations in clinical practice seem to be difficult to explain on a rational basis. These include doing “too much,” such as repeated testing, parallel testing, expensive and extensive testing for unlikely rare disorders, as well as doing “too little,” such as screening for common cancers, vaccination, or counseling. Some of the practices seem baffling at first glance, especially given the presence of decision analysis models, cost-effectiveness models, and occasionally evidence-based published guidelines that delineate rational medical decision making. Conventional economics (ie, rational utility theory) assumes that decisions are arrived at through a rational process of weighing benefits against costs for the goal of maximizing one's utility. Medical decision making is modeled by similar assumptions; namely, physicians (and patients) should make decisions that maximize utility by balancing benefits/harms against costs. However, there has been a growing interest in behavioral economics, which concerns itself with describing how decisions are actually made. Behavioral economics assumes that we (people) are “predictably irrational”1 in the way we make decisions on several things, including those decisions pertaining to health, and that understanding the basis for this nonrational behavior might be used to make us “do the right thing” despite ourselves. Daniel Kahneman was awarded the Nobel Prize in Economics in 2002 for his and Amos Tversky's empiric work describing how individuals make nonrational decisions. Kahneman and Tversky (1973) demonstrated that individuals use mental short cuts (heuristics) to efficiently and reliably make decisions that are often in contrary to models that determine preferences based on weighing benefits against costs.2 Furthermore, their Prospect theory (1979) illustrated how individuals predictably overweigh losses and underweigh gains.3 They use the term “prospect” to refer to a set of outcomes with a probability distribution, and they state that even when the probability of gain is low, most people choose the prospect that offers the larger gain.