More than 14.5 million Americans signed up for health insurance through the Affordable Care Act exchanges for 2022, which was a 21% increase over the last open sign-up period and the highest number of enrollments since the law was instituted in 2010, according to the U.S. government. About 10 million of these enrollments were through health care.gov, the federal insurance marketplace that is utilized by 33 states.
Health insurance decisions have strong financial consequences and determine access to potentially life-saving health care. Choosing health insurance requires many consumers to grapple with complex terms like deductibles and copays. These attributes force consumers to make tradeoffs—since low deductibles result in higher premiums—and many make costly mistakes with their choices and end up overpaying for coverage. Offering better choices can help consumers make better decisions and thereby improve both their health and the efficiency of the health care system.
This new research investigates how the design of online marketplaces—which is termed “choice architecture”—affects which health insurance policies consumers choose. The researchers show that seemingly minor changes in choice architecture can have a large effect on health insurance product choice and consumer health care costs. For example, providing consumers with a default alternative can remove the need for extensive contemplation. In addition, rapid advances in large-scale data availability, artificial intelligence, and machine learning-based algorithms help marketers match products with a consumer’s needs. Combining these insights with choice architecture can help consumers choose health care products that work best for them.
Health care exchanges provide opportunities for digital choice architectures to support consumers, especially because these decisions are both high-impact and infrequent. These exchanges use two ubiquitous choice architecture tools:
They can order the available options—typically done from the lowest premium choice to the highest premium one.
They can partition the total choice set presented to consumers by determining if a small number of initial options are presented on the first page.
“Ordering and partitioning may not always improve choices separately, but we identify the conditions that allow the combination to improve health insurance decisions. When the best health care options appear at the beginning of the list, partitioning subtly nudges consumers to focus on them. However, if the best options are not at the top of the list, partitioning discourages search and can impair consumers’ discovery of the best options,” states Dellaert.
Consumers must not only pay attention to good options; they should also avoid paying attention to poor-quality options. Johnson explains that “High-quality ordering, based on consumers’ predicted health care expenses, ensures that consumers see the good options, but without efficient partitioning, they can search too much, revise their opinions, and settle for lower-quality options. When the best options are not presented at the beginning of a choice set, for example, with random or low-quality ordering, partitioning can be harmful by focusing consumers’ attention on options that are not truly superior.”
The results of the study suggest that wise choice architecture interventions need to consider the joint effect of choice architecture tools as well as the quality of the firm’s user model. Choice architecture can be a relatively inexpensive and efficient way to use firm-level knowledge to improve social welfare, and governments can use regulatory oversight to prevent companies from adopting choice architectures that lead to worse consumer health insurance choices—but this will first require an understanding of how choice architecture ensembles affect consumers’ outcomes and choice processes. “Health care firms can take the lead by developing new business models based on algorithm-based choice architectures to deliver longer-term value and minimize waste for customers, other stakeholders, and themselves,” says Duncan.
For managers, this research highlights the potential tension between the interests of consumers and the profit-maximizing interests of health insurance firms. Thanks to the availability of extensive data, a health insurer may have a more accurate view of the probability and financial cost of a consumer being involved in an accident or contracting a serious disease. Baker says that “Health insurers might be tempted to exploit these informational asymmetries, but there could be another path to greater consumer satisfaction and loyalty in the long run, that is, building choice architectures that help consumers make better decisions.” While the economics of this strategy depends upon the ability of health insurance firms to develop accurate user models—along with the requirement that consumers trust these recommendations—an efficient system could have a lasting effect on individual consumers’ lives as well as the health of society as a whole.