Ep. 119 Healthcare, Computers and Consumer Choice

Americans constantly make choices about products and services – from buying a new pair of running shoes to figuring out which restaurant to order dinner from. We know from marketing and consumer theory that we are influenced by many things when we make our choices. Advertising work for a reason, and being exposed to different types of information, too, can influence our choices.

This episode of Policy 360 investigates how information may influence consumer choice when it comes to public goods such as health care or schools. How might recommendations and information provided by algorithm in these complex services influence the choices that we make? What ethical questions should be considered when guiding people to make decisions about essential services like health insurance?

Professor Kate Bundorf, S. Malcolm Gillis Distinguished Professor of Public Policy at the Sanford School of Public Policy at Duke University, joins the podcast to answer some of these questions. She recently published a study examining the impact of algorithmic information and recommendations on consumer choice in health insurance plans.

Sanford School @ Duke · Healthcare, Computers, and Consumer Choice

“There is a growing and almost large literature documenting the many ways in which people kind of screw up making their health insurance choices” says Bundorf,” and I felt a little frustrated by that literature. I felt, well, here we are documenting the ways in which people’s decisions are kind of going wrong. What could we do to actually help people and make those choices easier?”

The study focused on Medicare Part D, a publicly subsidized prescription drug insurance plan for older adults. As a part of the study, researchers developed a tool for people to use which tested how the participants reacted to information provided by algorithm. The information was designed to help people better understand complicated cost sharing features of different plans.

The research showed people who used the tool were more likely to switch plans and generally were more satisfied with their plans.