Predictive Prevention: How might consumer data be used for and against you?

Under the Affordable Care Act, we are now supposed to be living in an era where insurance companies can no longer prevent you from getting insurance just because you have a pre-existing condition.

But health care companies are clever. And one can imagine any number of ways that the use of consumer data in health care could yield results that would create strata of care that would leave some folks well served and others less so.

This was underscored for me recently by coverage of how some health care companies are starting to use consumer data such as credit card transactions to make decisions on how to prevent disease. It’s promising but, as I have noted before, a little scary, too. 

Already some providers only offer their services to the wealthy. If, for example, a health care provider or insurer could predict which patients were going to cost them more in time and resources than they wanted to spend, they could look in the consumer data for ways to carve out only those people they knew would bring in the right amount of payments at the right times. Robotic prostate surgery and post-surgical checkups? Great. Complicated pregnancies with a high risk of bad outcomes and potential lawsuits? No, thank you.

The truth is that health care companies already know a ton about us. Jane Sarasohn-Kahn at the California HealthCare Foundation did all of us a service this month by writing a tidy little report called “Here's Looking at You: How Personal Health Information Is Being Tracked and Used.”

Then the foundation took some of this great research and turned it into a clever pair of infographic stories that show how our everyday decisions enter into our digital health profiles.

There are words of caution and visions of an incredibly innovative future in Sarasohn-Kahn’s report. Here are two I thought particularly compelling.

1) Risk management may force companies to avoid certain clients or even employees. Sarasohn-Kahn wrote:

Consumers’ health scores could be useful for providers and payers as they move to value-based payment. … In the risk-based era for health care, those who bear the financial risk must manage that risk at a ‘much more granular level,’ [said Basel Kayyali, partner at McKinsey & Company].

So what would prevent a company from using this data to screen a potential employee and choose not to hire them based on their digital profile? Insurance companies may be barred from preventing someone with a pre-existing condition from joining a plan, but might they find other ways to steer people toward higher-premium, lower-benefit options because of other pieces of their profile?

2) And yet, wouldn’t it be great if your health data could make you healthier?

The possibilities of a future where predictive analytics takes your health data and makes you healthier as a result seem more tangible than a lot of the other ethereal ideas being discussed by the technorati. She quotes Paul Wicks, the vice president of innovation at PatientsLikeMe and a research neuropsychologist. PatientsLikeMe is a for-profit company that encourages people to sign up and share their patient information. Here’s Wicks’ vision, using the example of a grandmother with Parkinson’s disease:

A connected system of sensors, algorithms, and scientists could develop software that realizes it’s Friday, which is when we need more medication on board to get her safely to her weekly game of bingo, so the command center suggests to grandma that she ups her dose of medication, and sensors in her smartphone can monitor her journey and alert caregivers if something goes wrong, like a fall.

If you think the grandmothers in your life don’t have smartphones, ask them. Same with social media. Rare is the person these days who is not living digitally in some fashion and allowing the information collected to be used for a lot of things that really don’t directly benefit them.

The exciting part of the future foretold by Wicks, though, needs to be brought to life, while mitigating the risks noted in the rest of Sarasohn-Kahn’s report. In my next post, I’ll write about how gathering and analyzing the data are just the first part of the equation. Possibly the most important part is in the conversation that happens after a health care provider looks at the data profile and sits down — one hopes — to talk with the patient.

Cropped photo by Quinn Dombrowski via Flickr.