Spirit Aerospace Used Employee Health Records And Age Information To Lay Off Employees Union States And Filed Federal Discrimination Law Suit

CORRECTION:    This is Spirit Aerospace and not Spirit Airlines as I originally stated if you have already read this post.  Anything related to Spirit Airlines has been removed, my error. 

The Union and the Employees filed suit with the EEOC Commission, 360 employees were let loose in July.  It just so happened that this all occurred a few weeks after the company had changed to a funded insurance program.  If you watch the video you can listen to one man talk about how he applied for the exact same job that was open after he was laid off.   He never heard a word back. 

The company of course says they never used medical records but again time to dig in and see where maybe some wellness data was collected and so forth.  The company is not supposed to see those records and maybe they didn’t.  Maybe it was a 3rd party consultant who saw the records and made their recommendations?  We don’t know as we have no clue on who get to see what data, where it is shared and possibly sold as well. 

The company did call back 22 employees in November.  We live in the world where stats rule and ethics seem to be second place and you would have to living under a rock not to be aware of this.  We have what are called “risk assessments’ that are done with health insurance and even a mortality assessment can be bought from the MIB in some cases. We all know “age” is a factor with a risk assessment that can’t be changed and it is not supposed to be used to discriminate but without being there, how do we know?  We don’t.   

Now with data mining and matching that could have been done easy enough too.  A very high percentage of the layoffs were people who were older and had health conditions.  I have covered that here before and a few weeks ago 60 Minutes did a good dive in there on the re-query and rematch.  You talk to most proficient Quants and Data Scientists that have been around for a while and re-match, they just consider it part of the job as they all do it all kinds of data. 

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Here’s another example with insurance companies buying your Visa and MasterCard records, how hard would it be to identify someone with diabetes for example if they are filling prescriptions for insulin…so I think what we have here is perhaps a case where “official” medical records may not have been mined but there was plenty of other kinds of data to mine that would give them the information they may have wanted. 

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Here’s a visual and how that can be matched on the web which was done a few months back.  With so much on the web it can be matched with a good Query Monster on board to do the work.

 

 

 

 

 

 

 

 

 

 

 

http://www.kwch.com/news/local-news/union-spirit-used-employee-health-records-to-make-cuts/25175158