The technology could have some, ah, implications.
On Tuesday, the Wall Street Journal published an article about how bosses might take advantage of big data in order to anticipate employee health needs. The article focused on the ways in which firms like Castlight Healthcare Inc. collect data about what prescriptions employees use, how they shop, and even, sometimes, how they vote, in order to determine who is at risk for certain illnesses in order to offer them personalized messaging. (For instance, someone at risk for diabetes might receive an email suggesting they start a fitness regimen.)
The data analysis is, at best, a dystopian, unsettling violation of privacy with the ultimate goal of cutting healthcare costs. At worst, it could be used to identify employees in the process of making life changes—life changes that legally do not have to be disclosed, like whether or not you are trying to get pregnant.
From the WSJ:
To determine which employees might soon get pregnant, Castlight recently launched a new product that scans insurance claims to find women who have stopped filling birth-control prescriptions, as well as women who have made fertility-related searches on Castlight’s health app.
That data is matched with the woman’s age, and if applicable, the ages of her children to compute the likelihood of an impending pregnancy, says Jonathan Rende, Castlight’s chief research and development officer. She would then start receiving emails or in-app messages with tips for choosing an obstetrician or other prenatal care. If the algorithm guessed wrong, she could opt out of receiving similar messages.
The software could help employees make better informed decisions about their healthcare, but the potential for corporate misuse is definitely there.
Federal health information privacy laws prevent most employers from being able to see their employees’ health information (self-insured employers have more flexibility, according to the WSJ).
Still, should employers obtain the information for any number of reasons, it could be used to discriminate against employees whose healthcare could prove costly, which is fairly terrifying.
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