During work with different health insurers, one thing I became curious about was the structure of information about employer based or Group insurance. Specifically the origin of the Group, Sub-Group construct (also known by many other names). The group number usually corresponded to an employer. The Sub-Group would usually be a sub-set within a Group such as Managers versus Unionized employees. Usually is key, as when it didn’t there were complications. For reasons to long to blog about, the Group construct was limiting some options.
I would ask Clients why Group insurance was organized in such a way. For most, it was like asking why water was wet. It simply was always this way and how could it be any other way?
Any other way was the root of my question. In practice, the use of this construct was inconsistent within health plans. Some employers had multiple Group numbers. The Sub-Group had many meanings. One group used it to designate geographic locations. Some used it to separate retirees and active workers. Most Groups had a mix of uses that only subject matter experts on a particular group would understand, which hampered analysis.
In response to my question I was eventually brought to a woman who one could certainly describe as seasoned. I was fairly sure she handled any Wright Brothers’ claims. The answer to my question was simple. A Group Number corresponded to a filing cabinet. It was why larger Groups sometimes had more than one number. The Sub-Group was a particular drawer. The Contract number would be a file. For smaller companies the Group was often a drawer and the Sub-Group a particular slot in a drawer.
So as Health Insurance transferred from paper to electronic processing, the paper based construct of Group and Sub-Group remained. Entire IT infrastructures were built around a structure that was no longer required. There are probably better ways to organize this information in an electronic based environment.
My next line of questioning to all is, what other assumptions exist that are not really necessary anymore? Will Data Analytics help in identifying these self imposed restrictions and offer ideas for change? Or will the promise of Data Analytics be blinded to some opportunities by constructs that no longer apply?