Health plan choices: less is more

Whether through an employer, Medicare, or an Affordable Care Act marketplace, many Americans have choices of health care plans — sometimes from among dozens of possibilities. I’ve written a lot on the AcademyHealth blog and The Upshot about how hard it is for people to make good plan choices from such a bounty of options. They often end up paying more than they should, either because they actively choose a suboptimal product or because they passively remain in a product that drifts away from optimality over time.

Some studies indicate that with reminders and assistance — provision of calculating tools, better ways of comparing and viewing options, and other guidance — people can be encouraged to make active choices and, moreover, make better ones. Availability of such things is not widespread, but it is growing.

But is encouraging annual plan shopping, providing selection aids, and improving choice architecture just treating the symptom of the real problem? Maybe more choices isn’t better? What if helping consumers navigate them is merely second best to reducing the number of choices in the first place?

It sounds a bit crazy, because a premise of an ideal market is that there are so many choices, everybody can find a product to perfectly match his or her preferences. No market achieves that ideal, but clearly fewer choices moves in the wrong directly, theoretically.

Theory is useless if it is wrong. It must be tested.

In a study published as an NBER working paper, Jason Abaluck, Jonathan Gruber did so. They compared people’s choices of health plans under various interventions: (1) promotion of active choices, (2) assistance with choice support software, and (3) reduction in plan choices. According to their analysis, across these intervention types, consumers achieved the best outcomes when choices were restricted. Less is more!

These interventions were implemented across school districts in Oregon between 2008 and 2013 where, according to the analysis, only 36% of covered employees had made the cost-minimizing choice. On average, employees spent about $1,000 more on coverage per year than they could have. The number of plan choices varied across district and time. Through 2011, the vast majority of employees had four choices. After 2011, some had as many as ten. Choices ranged in plan style — closed panel HMOs (e.g., Kaiser) and broader network PPOs — as did employer contributions to premiums and cost sharing, all of which was controlled for in analysis.

The authors analyzed nearly 400,000 employee-year observations in several ways. One analysis exploited the fact that 12% of employee-year observations were forced to switch plans when their current plan was dropped in their district. Did forcing people to switch cause them to choose better plans, compared to people who did not switch? Nope. Forced switchers actually spent even more than they could have, compared to non-switchers.

Another analysis exploited the randomization of enrollees to access to a tool that used each individual’s claims history to provided the total cost of each available plan. Based on this information, it also displayed plans in order of total cost and stared the lowest cost plan. In other words, it relieved consumers of most of the cognitive effort of comparing plan costs — just look for the star and done!

The authors estimated that users that received the tool’s recommendations were only 8% more likely to choose the best plan, relative to those that did not have access to the tool. Unfortunately, the tool’s recommendations were not always in alignment with true plan costs, because the tool had to make some assumptions and also due to user input error. The authors estimated that a perfect tool fed perfect information — which is essentially impossible to achieve — would induce 17% of users to choose the lowest cost plan, reducing foregone savings, coincidentally, by only 17% as well.

Finally, the authors examined forgone savings as a function of choice sets. Foregone savings are almost twice as large when employees face a choice of eight plans versus only four plans. Now, this result could occur if what’s going on is that as additional choices include better ones, but that enrollees don’t pick better ones. That is, they could do better with more choices, but they don’t know how to make the right ones.

That’s not what’s going on. The authors wrote,

[S]maller choice sets lead to beneficiaries being enrolled in lower cost plans because larger choice sets have more plans which are higher cost on average – and individual choices do little to offset this “more dangerous” choice environment.

In other words, when choice sets are small, plan administrators have made relatively good selections already. But as administrators expand the choice set, they add worse (more expensive) plans. Because consumers have a hard time picking the best plan, they are more likely to end up in a more expensive one as choices grow.

The conclusion is that consumers may save far more if they are presented with fewer choices than they save by either being induced to shop or by provision of output from a plan cost estimator. Yes, we can help some people make modestly better choices with cost calculators and better choice architecture — and we should provide such things. However, according to this study, people are so bad at choosing plans that they are even better served by simplifying their choices.


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