Big
data can help with a lot of things: Netflix suggestions, saving money at the
grocery store, monitoring your sleep cycle. Should it be considered in the
workplace too?
Headlines last
week started
swirling about how many companies, including prominent names like Wal-Mart or
J.P. Morgan Chase, were using #big_data firms to mine data about the health of
their employees.
Everything from monitoring which workers are at risk for
spinal surgery to monitoring which employees have stopped filing their birth
control, these firms closely monitor aggregated data and pass along tips. And
for now, they’re painting within the lines. But that doesn’t mean it’s
popular—or permanent.
It’s yet another example of just how much data
consumers can leave in their wake that they don’t even know about. Healthcare analytics firms can mine workers’ medical
claims, pharmacy claims, credit scores, and search queries to get a read on
exactly how an employee is doing, and what they might do for the future.
“I bet
I could better predict your risk of a heart attack by where you shop and where
you eat than by your genome,” said Harry Greenspun, director of Deloitte LLP’s
Center for Health Solutions, a research arm of the consulting firm’s
health-care practice, in the Dow Jones
Business News.
And it’s all legal: Currently there’s no
legislation out there to keep employees’ data out of the hands of companies
like this. It’s all on the employer to navigate any legal fault lines (like
HIPAA, which prevents accessing a worker’s medical information but not data
mining), which is what has many worried.
Data is only collected on employees who
have explicitly opted in, and although these firms will share data with the
employer, they’ll do so without any personal data. Employers may know that there’s
200 workers considering surgery according to the firm’s data collection, but
they won’t be able to drill down who those 200 are.
In this case, however, the stakes are much
higher because the parties involved are in an employer-employee relationship,
points out James Hodge, a professor of public health law and ethics at the
Arizona State University Sandra Day O’Connor College of Law.
“If [an employer] originally thought that
15% of the women in its employee base may become pregnant, but data shows it’s
closer to 30%, that could lead an employer to say we cannot hire as many female
employees this year because we can’t afford them being out for family leave,”
Hodge explains. And while this example is purely hypothetical, it shows the
kinds of discriminatory arguments that this data could be used to
make—regardless of whether an employer has access to individual employee names
or not.
…Hodge argues
that the data gathered by the company could still be used to penalize employees
who did not opt in. “You only need a random sampling and you can then
extrapolate meaningful and actionable data” based on a significant sample, he
says. In other words, Walmart doesn’t need every one of its 1.4 million U.S.
employees to opt in to Castlight—it can make do with a few thousand.
Meanwhile the statistics behind employment
discrimination remain daunting, with the number of pregnancy discrimination
charges are increasing. And while the EEOC has tried
to stem the tide of employers using wellness programs and wearables to
monitor employees’ health they’ve had some
setbacks as of late.
Which some would say isn’t so bad. After
all, so long as the program isn’t mandatory there is good that can come from
these programs. The same app that collects the data on whether you’ve stopped
filling your birth control could give them
nudges to find an OB/GYN to help with prenatal care. When Wal-Mart was informed that 30 percent of
their employees who got second opinions opted not to get back surgery, the corporation made concentrated efforts to
communicate with those same employees about alternative options.
But as technology gets more inventive, and is able to
help people live longer, healthier lives, you can trust that some—including the
EEOC—makes sure that information doesn’t fall into the wrong hands.
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