Lessons for Health Care from Behavioral Economics
The emerging field of behavioral economics has yielded important insights into how individuals make choices. Standard economic theory assumes that individuals are rational, forward-looking consumers who make choices so as to maximize their utility (or happiness). However, numerous laboratory and field studies now show that individuals often have difficulty making wise choices. Difficulties are particularly likely when individuals are faced with decisions that involve uncertainty, tradeoffs between current and future costs and benefits, or significant complexity.
Decisions relating to health care, such as whether to purchase health insurance, what plan to choose, and whether and when to consume health care, unfortunately exhibit all of these attributes. Yet the insights from behavioral economics generally have not been applied to the study of health care. A new working paper by researchers Jeffrey Liebman and Richard Zeckhauser, "Simple Humans, Complex Insurance, Subtle Subsidies," (NBER Working Paper 14330) seeks to apply such insights.
The authors discuss the three areas where decision-making has been shown to be particularly poor, starting with the issue of uncertainty. The standard economic model suggests that individuals in effect calculate the expected utility associated with each health insurance plan, as well as that associated with not buying insurance, and then select the option that maximizes expected utility. Yet making this calculation requires assessing the probabilities, financial costs, and levels of happiness associated with possible future outcomes such as developing cancer or having a heart attack. In practice, each of these components is problematic.
The behavioral economics literature has shown that individuals make systematic mistakes in assessing probabilities. They give too much weight to salient low probability events, such as dying in a plane crash, and do not distinguishing sufficiently between a 5 percent and a 20 percent chance. It is virtually impossible for consumers to assess the financial costs associated with various health conditions, as there is no place to look up the prices charged for health services. Predicting one's level of happiness under different health conditions presents another challenge. The standard way to assess health-related utility is in quality-adjusted life years (QALYs), where the value of a year of life is reduced by a certain amount if the individual has a particular medical condition. Research has shown that individuals overestimate the amount by which their happiness will decline if they become sick (that is, assign disability states too low a QALY value).
Decision-making over time presents a second challenge. Health care choices often require incurring costs today to produce future benefits. This is true for routine preventative care as well as for more costly and invasive procedures such as the removal of certain organs or tissue to reduce cancer risk among high-risk patients. Behavioral economics has shown that given their own values, people tend to invest too little in activities like these because they put too much weight on costs today and too little weight on future benefits.
The complexity of health care decisions creates a third area of difficulty. The standard health insurance plan incorporates many attributes, including financial provisions like deductibles and copayments, as well as other factors such as different levels of coverage for different providers. Health insurance is also rife with complex cross-subsidies. For example, employees may not understand that they are sacrificing cash wages in exchange for employer premium payments, and may not know whether they are giving up an amount equal to the average premium or their own personal premium, which will depend on age, family size, and health status. Evidence from psychology indicates that people who face complex choices make poor decisions. A salient example is status quo bias (SQB), people's tendency to stick with choices made previously regardless of whether they are optimal. Given SQB, the behavioral economics literature has recently focused on the importance of default options in decision-making and the potential using them to get individuals to make better choices.
Having analyzed the pheonomenon, the authors turn next to the implications of behavioral economics for health care policy. The first is that behavioral economics provides an additional justification for subsidizing health care. A key tenet of economic theory is that insurance leads individuals to over-consume health care by reducing the price of care to less than its marginal cost. But if individuals tend to under-consume care for reasons related to behavioral economics - for example, because they underweight the future health benefits it will provide - we are thrust into a second-best world. Under-consumption stemming from behavioral tendencies offsets the traditional distortionary effect of insurance. It is no longer certain that insurance leads to over-consumption of care.
Behavioral economics also has the potential to inform thinking about how subsidies to health care should be structured. For example, standard economic theory suggests that the point of insurance is to protect people against low-frequency, high-cost events like heart attacks, not high-frequency, low-cost events like annual flu shots. But if these low-cost events are precisely those where under-consumption is greatest because the benefits primarily occur in the future, subsidizing them, including possibly paying people to get them, is warranted.
What are the lessons of behavioral economics for current policy debates? The major proposals from both the left and the right seem likely to produce at least a modest shift away from employer-provided insurance and towards a system where individuals are more responsible for making complex choices about health insurance and health care. Based on their analysis, the authors suggest four main lessons for health care reform.
First, consumers need to have their health insurance plans mediated by some entity that can screen and restrict health insurance choices down to a very limited number. The authors argue that employers are better suited for this role than is the government or private insurance agents. Second, rather than structuring insurance co-payments to make consumers face the marginal cost of care or something close to it (at least over some range of expenditures), the authors suggest that co-payments be designed using cost-effectiveness analysis. This would maximize QALYs gained relative to dollars spent. Third, efforts to cover the uninsured should reflect behavioral obstacles to coverage - for example, automatic enrollment may hold more promise than financial penalties as a way to increase coverage. Finally, information gathering on the effects of behavioral interventions should be increased in order to promote the more sensible design of health policy.
As the authors conclude, behavioral economics "enables us to predict the biases that afflict individuals' poor decisions, to know what measures can counteract them, and thereby to produce better choices for insurance and care by individuals. QALYs are waiting to be reaped."