Unlike here in the UK, taxpayer-funded universal healthcare doesn't exist in the US, where healthcare is provided by private firms and not-for-profit organisations.
There are, however, some cases of government aid, and Ohio-based CareSource is one of the largest providers of Medicaid, a government programme that provides assistance with obtaining healthcare for those on lower incomes.
Like many modern healthcare providers, CareSource is beginning to use analytics in order to determine the nature and quantity of medicines that patients require.
The firm established a "Decisions and Information" department in 2004, with Bob Gladden brought in as VP of Information Management and Analysis to build it from scratch, and he describes SAS's big data solution as key to its success.
"Almost immediately we brought in SAS as a tool for a lot of reasons," he told Computing at the SAS Premier Business Leadership Series 2013 conference in Orlando, Florida.
"SAS gives us a lot of capabilities, and it has a fairly easy user interface so folks don't have to be heavy programmers to use it. We have folks who really aren't programmers using it very effectively."
Gladden praised the simplicity of SAS, commenting that the solution enables CareSource analysts to quickly and simply write and interrogate thousands of reports at once.
"If we have a process we want to put in place and we need for it to become a production process, that's fairly easy to do with SAS. So we have about a thousand reports right now that have all been written in SAS," he said, adding that SAS allows the system to be almost entirely automated.
"All those reports are written in SAS, the vast majority of them are written so that nobody's touching them, you just get them all built in the process," Gladden continued, hailing the agility of the SAS solution.
"It gives you the flexibility of having a tool that analysts like so it's very agile and very effective, but also gives you the capability of moving into a more production based IT-like environment so you can have it run on a routine basis."
When asked to identify SAS's strongest feature, Gladden responded "without a question it's been the ability to - and I'm going to create a word - 'productionalise' the work that we have within the department."
He explained how SAS enables analysts to set cycles of production, freeing them up to work on other projects instead of needing to repeatedly analyse new sets of reports or data.
"Typically we'll be asked to do analysis of something then told ‘this is great, I want to have it every month'. The last thing I want to do is take an analyst offline to run a report every month, that's just a colossal waste of time," Gladden told Computing.
"It gives you the capability of taking that code largely as it sits and then immediately moving it into a production environment and that can include some sophisticated statistical techniques that are part of that programme which if you were writing in other packages would take you an immense amount of time just to perform the statistical function," he added.
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