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The more we look at the data Enkata produces, the more it becomes clear that claims payers need Enkata if they want to make substantial quality and productivity gains in their manual claims paying operations. There are many ways claims payers can improve their processes, but all of the largest potential improvements come specifically from understanding how people work.
When we look at this work, we see several areas where simple changes can lead to dramatic improvements. There are skill gaps, especially where remote employees don’t understand that they are doings something the wrong way. There are poor processes, where certain steps and tools slow workers down and lead to reduced productivity. And, unfortunately, there are always a small number of processors who game the system, producing fewer finalized claims and more errors than they should. When they address these behaviors a company can easily boost productivity by 10% or more.
It turns out that some of the problems that lower productivity also lead to significant accuracy problems. We see behavior patterns that are highly predictive of errors. For example, some people switch between email, instant messaging and complex claim types at a high rate. This kind of multitasking on complex tasks has a serious impact on accuracy. Likewise, people working in a hurry will skip important quality control steps, and some people simply don’t know what to do. Enkata provides a uniquely powerful tool for identifying and correcting these causes of errors. Although Enkata greatly improves productivity metrics like claims per hour, the accuracy improvements are perhaps more valuable.
Companies are always looking for ways to improve efficiency. For claims payers, there are projects to be done around tweaking auto-adjudication, identifying fraud, improving macros, etc. While these projects are important, and can have a strong ROI, companies that fail to look closely at how their workers perform will always be overlooking the most significant potential improvement they can have.