How Much Should Your Health Insurer Know About Your Health?
Coordinated care, integrated care, managed care -- these are just some of the buzz words surrounding the health insurance industry these days. This is what makes modern health insurance different from the indemnity insurance of years ago, when patients went to any doctor they liked and the insurer passively paid the bills. The modern insurer wants to be involved in your health care. At a minimum they want to steer you to providers and facilities that...well, that might have higher quality care, but for sure will cost less money.
Coordinated care, integrated care, managed care – these are just some of the buzz words surrounding the health insurance industry these days. This is what makes modern health insurance different from the indemnity insurance of years ago, when patients went to any doctor they liked and the insurer passively paid the bills.
The modern insurer wants to be involved in your health care. At a minimum they want to steer you to providers and facilities that…well, that might have higher quality care, but for sure will cost less money.
What insurers don’t know. There’s just one problem. The health insurers who are enrolling folks in the newly created health insurance exchanges don’t have any more information about the health condition of their enrollees than Blue Cross had about its enrollees back in the 1950s. Why? Because of health reform. (ObamaCare.)
Until this year, insurers who sold individual and family coverage in most states asked people to answer questions about their health status, just the way sellers of life insurance and disability insurance do. The answers to those questions determined the premium, led to exclusions for certain types of care and may have precluded the applicant from getting coverage at all.
This year things are different. In the health insurance exchanges insurers are not only precluded from discriminating against applicants based on their health status, they aren’t even able to ask about health status in the first place.
That’s frustrating the health insurers in two ways. First, without knowing who is sick and who is well, they can’t do any of the coordinating, integrating and managing they think they are supposed to do to keep costs down. But even worse, now is the time of year when they are supposed to be setting their rates for re-enrollment during open season later in the fall. And they have no idea how to price their plans because they have so little information about the likely health costs of the people who they have as enrollees.
How they are finding out about you. Not to be deterred, some insurers are following the lead of some large retail stores and using the Internet to find out what they want to know. Take U.P.M.C., a Pennsylvania nonprofit that owns an insurance company as well as hospitals, including Pittsburgh Medical Center. As Natasha Singer at The New York Times explains:
… the insurer recently bolstered its forecasting models with details on members’ household incomes, education levels, marital status, race or ethnicity, number of children at home, number of cars and so on….
In a more-data-the-merrier culture, patients may ultimately be unable to choose whether their health insurers know they prefer organic foods, hunt big game or own a dog.
If health insurers mistakenly peg certain people as dog owners, patients probably won’t find that out, either. (Acxiom, one of the sources for the household information U.P.M.C. used in its prediction models, has publicly acknowledged that its details about consumers can be out of date or just plain wrong.)
So what can insurers do with all this information? Predict utilization of care. For example, a person who buys furniture using an Ikea catalogue might be a person who is homebound or lacks transportation. Such a person is more likely to seek care at a hospital emergency room than a (less expensive) doctor’s office visit.
U.P.M.C. discovered that mail order shoppers and Internet users overall are more likely to use the emergency room.
To see just how far data mining can take you, consider my previous claim that “Target Knows You Are Pregnant, Even if No One else Knows”:
As Pole’s computers crawled through the data, he was able to identify about 25 products that, when analyzed together, allowed him to assign each shopper a “pregnancy prediction” score. More important, he could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy…
Pole applied his program to every regular female shopper in Target’s national database and soon had a list of tens of thousands of women who were most likely pregnant. If they could entice those women or their husbands to visit Target and buy baby-related products, the company’s cue-routine-reward calculators could kick in and start pushing them to buy groceries, bathing suits, toys and clothing, as well. When Pole shared his list with the marketers, he said, they were ecstatic. Soon, Pole was getting invited to meetings above his paygrade. Eventually his paygrade went up.
At which point someone asked an important question: How are women going to react when they figure out how much Target knows?
Will all this snooping help control costs? That’s the goal of the insurers, of course. But the same technology that is available to the insurers is also available to hospitals and other providers – whose interest is in more spending and more revenues.
MedSeek, a software and analytics company in Birmingham, Ala., offers a “21st-century tool kit” that can refine health care marketing pitches based on sex, age, race, income, risk assessment, culture, religious beliefs and family status. One client, Trinity Health System in Michigan, used MedSeek’s services “to scientifically identify well-insured prospects,” among others, and encourage them to schedule screening tests and doctor visits, a company case study said.
And what’s wrong with that? Natasha Singer explains the down side:
The pitches might encourage the worried well to have unnecessary screening tests, for instance, potentially putting them at risk for false alarms and unneeded biopsies. And by devoting so much attention to pulling in low-risk or well-insured patients, health providers could end up overlooking – or not having timely appointments available for – ailing, poorly insured patients.
In other words, the same technology that can enable an insurer to better manage the care of the sick could also be used to induce more spending on the part of the healthy and the wealthy.