Making Mammograms Automatic – Unintended Consequences Of A Behavioral Economic Intervention
SEVILLE ANDALUSIA, SPAIN - OCTOBER 19: A lady with the help of a nurse gets a mammogram. (Photo By ... More Eduardo Briones/Europa Press via Getty Images)
The experiment was simple. A group of behaviorally-minded researchers tested whether patients are more likely to receive mammograms when those tests are automatically scheduled (meaning they can opt out if they want) versus when they have to opt in for the tests.
The researchers predicted that people who have to opt out of the test will be much more likely to receive it. Lots of research shows that when you turn a behavior into a default, things are more likely to happen. Automatically max people's retirement contributions and people are more likely to…maximize their retirement contributions (even though they could opt out of this option). Make the James Bond theme song the default ring tone, and lots of people will hear that theme song when their phone rings, the default option becoming their 'choice.'
Inertia is a powerful force. Add to that the importance of mammography, and automatically scheduling mammograms should significantly increase use of that test, a great outcome with no apparent downside.
Except that's not what happened. Here's why.
In the study, which was led by Leah Marcotte a physician at the University of Washington, the research team randomized over 800 women mammography into one of two groups:
To my surprise, the opt out intervention did not work as predicted. It did not increase the number of women receiving mammograms, with 15% of women receiving mammograms regardless of whether they were in the opt out or the opt in group.
You might think 'no harm, no foul.,' that the opt out intervention did not increase screening but did not reduce it either. But the intervention backfired in one meaningful way – it created lots of work for healthcare providers handling mammography appointments. In the opt in group, 5% of women scheduled mammograms and then canceled their appointments; in the opt out group, the cancellation rate was 24%.
This well conducted study is hardly a death knell for opt out interventions, which have proven to work in many healthcare and nonhealthcare settings. Instead, it is a reminder that a host of other factors – populations, organizations, finances – potentially alter the impact of behavioral interventions.
We should not assume we know how behavioral interventions will influence the people we are trying to help. Instead, we should expose those interventions to rigorous tests. Kudos to to Marcotte and her team for doing so, and for reminding us to expose behavioral interventions to the rigors of science.
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