There’s a major headache going on in the world of hospital systems and healthcare insurance providers. With recent regulations requiring more transparency in healthcare coverage online, the healthcare industry has been rushing to get their files in a row. There’s just one problem: it’s a lot of information to sort through. In one discussion with a health provider executive, we even found that some files could contain petabytes of data—a million gigabytes.
But imagine not just petabytes of data. Imagine entire petabytes of bad, inconsistent data, and you see what these major healthcare providers have to deal with.
Files may be in the wrong format, include bad data, or may not even be machine-readable, rendering automation a formidable challenge. Here is what some executives are looking at:
- Creating consistent files. A lot of data isn’t necessarily a lot to handle. As long as the data is high-quality and consistently readable, it’s easy to export, move around, and get to its proper function. The problem is when data isn’t machine-readable or provides inconsistent information that requires digging through files with greater scrutiny. That’s why so many executives find it challenging to deal with these overwhelming amounts of data. It’s not because they don’t have the resources for the space, it’s due to their overwhelming complexity.
- “Fidelity quality assurance.” One executive we spoke to said consistency was the key. They’ve been able to go through the files and ensure that the vendors’ work retains fidelity with what the hospital did. The problem? Extremely large data sets to sort through. Making sure the data is high-quality was the first priority for the executive we spoke to, who is going through existing vendor contracts to find out how to fix the data issues.
- Outsourcing data automation. When a company works with M Corp, our ambition is to make the headaches like those described above go away. And while we do employ software in these solutions to help make sense of all of that data, we don’t view ourselves as a software vendor. This means that large organizations are paying for the amount of data they’re off-loading to us rather than purchasing software and hoping for the best possible results.
- RPA-as-a-Service. Robotic Process Automation as a Service (RPAaaS) employs software technology to execute the reading of all of this data without the intense headaches that they cause along the way. For large healthcare providers, there may be no other way to minimize the headaches—not when you’re dealing with entire petabytes of bad or inconsistent data.
Large organizations are finding that the data they have to deal with is not only overwhelming, but not worth the headaches to solve entirely on their own. Moving to an RPAaaS solution promises to add simplicity and data fidelity to the process. Think of it as a way to turn data from a problem—into an asset.