Sure, post-menopausal women and single men don't need maternity coverage but have to pay for it it anyway. But, the US government can now argue, half of all people are paying for coverage they don't need already.

There's just one problem, argues a new report; while currently only a relative handful of the population has been able to sign up for the mandatory program, when lots of people do sign up for healthcare via the new health insurance exchanges set up by the federal and state governments, the fact that more than 80% of consumers may be unable to make a real estimate of their needs means they will choose a higher cost plan than they need.

That means that the insurance companies the government has demonized and said are the problem will make lots of profits and won't be under any competitive pressure to squeeze hospitals and doctors into taking less money - and competitive pressure claims were the big selling point in the government's cost analysis. Result: taxpayers will pay more directly, in the way of premiums, and indirectly, in the way of more taxes to pay for everyone else buying more coverage than they need and getting subsidized for it. 

The team conducted six experiments asking people of varying education levels to choose the most cost–effective policy using websites modeled on the current exchanges. The results led to some startling conclusions, including:

• The average consumer stands to lose on average $611 — roughly half a week's salary for a family making $42,000 per year — by failing to choose the most cost-effective option for their needs.
• Because the federal government will subsidize many policies, American taxpayers could pay an additional $9 billion for consumer's mistakes in choosing more costly plans.
• Surprisingly, providing monetary incentives alone did not improve outcomes. Participants were offered $1 for every correct answer and entrance into a lottery that pays one winner $200, yet 79% of participants still chose the wrong plan, inadvertently adding $419 to the cost of their health insurance.

The percentage of choices of the most cost effective option and respondents' average error. The top half of each bar, in blue, represents the proportion of correct choices, and the bottom half, below the zero line in red, plots the average dollar error, across respondents. A dashed line for each condition represents the performance of a random chooser, and the error bars represent 95% confidence intervals. Darker shades denote the provision of calculators. Panel (A) represents the results of Experiments 1–4 collapsing across other manipulations (see SM). Panel (B) represents the results of a sample of highly educated MBA students (Experiment 5), and of individuals from the target population, when given different choice architecture interventions. For (b) the random response threshold ($1264) exceeds the lower limit of the graph. Credit and link: doi:10.1371/journal.pone.0081521

Professor Eric Johnson, lead author of the report and co–director of Columbia Business School's Center for Decision Sciences, cautioned against misuse of the research: "Amid the political heat around the healthcare law, there's going to be a great propensity for some politicians to jump on this study and misinterpret these results. This research presents no empirical evidence that in any way is an argument for or against the Affordable Care Act itself. Instead, this is research about the difficulties and complexities in creating the actual delivery systems, which is being done in both blue and red states." 

Prescriptions to Improve Outcomes

Through the research, Johnson and his colleagues identified several mechanisms that significantly improved outcomes for the consumer. These include:

• Estimate First; Peruse the Plans Second: Estimating your medical services before choosing a plan increases your chances of choosing the best plan.
• Educate: Including the use of 'just-in-time' education: tutorial links and pop-ups that explain basic terms like "deductibles" that might not be known to new buyers, increase your chances of choosing the best plan.
• Implement smart tools: Adding a calculator to the process improves your chances of choosing the right plan and reduces the size of errors by over $216.
• Implement other "smart defaults": Including a tool that defaults to the most cost-effective plan drastically improves a participant's chances at selecting the most cost-effective plan by 20%. Together, calculators and defaults reduce the average mistake saving consumers and the government $453.
• Limit the number of choices: Exchanges that limit their amount of choices in healthcare plans will help to avoid confusion among consumers (Utah offers 99 healthcare options for participants).

"Designers of the exchanges should take heart and know that they can significantly improve consumer performance by implementing some easy, straightforward tools such as just–in–time education, smart defaults, and cost calculators."