Errors in manual claims processing are a big problem. While underpayments lead to complaints and rework, overpayments may go unnoticed and cost far more.
In either event, healthcare claims payers bear an increase in cost with every mistake made.
In studying what leads to claim processing errors, Enkata has found two things of note. One, not surprisingly, is that errors are not at all evenly distributed. The worst processors in a group will have an error rate that is more than twice that of the average. Those with high error rates will consistently have high error rates across measurement periods.
The more interesting discovery is that there are actually clusters of behaviors that lead to these high error rates. Low accuracy processors tend to be one of two types: those who work too fast, and those who work too slowly. Managers who want to help their processors reduce their error rates need to start by understanding which behaviors the processor has.
Processors who work too fast skip key quality control steps and don't invest the time needed to make sure the payment is correct. If there are supporting materials they're supposed to review, they may not even be opening the documents.
The impact on accuracy of working too fast is clear. However, the behavior itself can be hard to spot. Often times, these processors are well aware of the productivity target, and they race to hit it, and then slack off, or even stop working all together. This behavior can be most extreme among remote employees, as they might organize their day to have hours off once they've reached their goal.
Traditional metrics, like average claims per hour or claims per day, tend to be useless for finding these
"target shooters," because they know how to work towards metrics. Additionally, employees who switch between claim types might be expected to have high variation in work rates. The better way to identify them is to review how long they actually spend in a claim. Complex claims finalized in seconds is a clear indication of a real problem.
The first step in coaching these employees is to actually identify the undesirable behavior, and confront them with it. If they aren't clear on the steps they need to take, they can be coached. But more often than not, the issue is not a lack of knowledge, but a lack of willingness to put forth the effort required.
In this way, target shooters are completely different from their slower, error-prone counterparts. The challenge slow workers have is that they simply don't know how to do the job. This becomes painfully clear when you watch them work. While "good" workers follow a very consistent process, slow employees click around, wander through the knowledge base, and eventually start sending emails, instant messages, and phone calls looking for help. Ironically, the longer someone takes and the more time they spend in the knowledge base, the more likely they are to have an error.
The good news is that these types of employees are at least trying to do a good job, and may be as frustrated as their manager with their results. The solution is also pretty straightforward. They just need more training, perhaps on the specific claim types that are the most challenging for them.
For managers, the conclusion to draw is that while that managing with dashboards and scorecards may be a good starting point, the key to improvement comes from really understanding how employees work, and how their personal work habits shape the quality of their work.
Dan Enthoven is vice president of marketing at Enkata.