An algorithm helps choose health insurance plans

Researchers at the Stanford School of Medicine and the University of California, San Diego developed a web-based tool with an algorithm that matches the medical records of Medicare part D with the best health insurance options for prescription drugs, to help consumers choose the best health insurance plan for them

“Tons of evidence suggests that people have a hard time making choices when it comes to health insurance,” says Kate Bundorf, associate professor at Stanford School of Medicine with a courtesy appointment at Stanford Graduate School of Business. “The complexity can be overwhelming and, as a result, people often choose suboptimal plans that punish them with higher costs and create inefficient markets. So we wanted to figure out what types of tools would help people make decisions”.

Study participants were assigned to either a control group or one of two treatments. The control group was directed to existing online Medicare resources for choosing one of the 22 prescription plans available to them. Treatment groups, meanwhile, received support from the algorithm, which automatically drew information from their medical records and matched it with prescription drug plans. When reviewing their options, both treatment groups were able to view a table online that showed individualized analysis of likely costs for each of the plans. In addition to this, one of the treatment groups was shown an “expert score” for every plan: a number, from zero to 100, that the algorithm produced to rank the plans. The three best options were highlighted at the top of the table. Both treatments encouraged people to change to more favourable insurance plans, but the treatment that included the “expert” suggestions alongside cost estimates proved more effective. Participants in this treatment opted to switch plans 36 percent more often than those in the control group. “We found clear evidence that the intervention changed people’s behaviour, particularly in the case when we offered expert advice,” says Bundorf.

In the context of the experiment, these changes generated $270,000 in savings for consumers. However, there is still something to improve: first, only a small portion of those eligible to join the study chose to enroll. Only 1,185 people took part in the study, out of nearly 30,000 who were invited; and those who joined were more tech savvy than those who didn’t. On top of this, the researchers worry that those who would benefit the most might not have elected to take part.

“The people who chose to interact with the algorithm were sophisticated consumers; they were active shoppers who were seeking out information,” says Maria Polyakova, of Stanford School of Medicine. “This suggests that if we want to improve the choices of people who currently have the worst plans, then simply offering the tool online won’t solve the problem.” A more proactive approach is necessary.

Second, the study’s demographics are not representative of the broader Medicare population. Bundorf and her colleagues collaborated with the Palo Alto Medical Foundation to run the experiment, which means those who took part lived in one of the wealthiest and most technologically attuned parts of the country. “It’s conceivable that people in other places, who have lower incomes and less exposure to tools like this, may behave in a completely different way,” says Polyakova. Further research is still needed.


Source: Stanford University

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