- Data Intelligence For Sales
- Data Intelligence For Claims Operations
Although a reported 79% of healthcare claims are processed by an auto adjudication system, significant investments (including both technology and people) are still needed in healthcare payer organizations to handle the manual processing of claims. However, manual claims processing operations face a lack of into work done at the individual processor level, which is where the real changes for improvement will happen. Healthcare organizations are likely to have high-level insights into the total number of claims processed by each processor, as well as the organization as a whole, average processing time, and accuracy information pulled from auditing efforts.
While this information is still very useful, it provides very limited opportunities to determine in what areas individual processors could focus on improving. What behavior really separates good processor from a great one?
For instance, knowing that Jake processes twice as many claims per day than Kathy is important. And on the surface it may make Jake look like a much more valuable employee. After all, he is doing double the work in the same amount of time as Kathy. However, when you start digging deeper into the real story the why behind Jake’s speed becomes very important to understanding who the better processor is.
It may be that Jake is the worst employee on the team. If he is skipping key process steps, then he’ll be faster, but with a lower accuracy rate. Overpayments in claims are hard to catch, so if Jake is overpaying on claims, he’ll be getting high performance scores despite really damaging the business. Or Jake may be cherry picking easier claims, and passing on claims that look like they’ll take more time.
On the other hand, if Kathy really doesn’t know how to do her job, or has poor work habits, then her manager needs to help her get her productivity up to snuff. It’s important to note that remote workers have a different set of challenges. Home based claims processors may not know the best practices or understand what is expected of them. They can’t simply lean over to the cube next to them to ask for help.
Managers of home based workers have challenges as well. They generally don’t have tools that help them gain visibility and insight into how their team is performing. Stuck with high level productivity metrics, they can identify the outliers. That doesn’t help them provide the right kind of coaching to those who need it, or identify the destructive behaviors that some employees may have.
There are many reasons why one agent might be processing more claims than another or why one processor’s average handling time is longer than another. On the surface these metrics tell one story but if you dive a little deeper you might find a completely different situation. Determining the real why behind a processor’s performance is critical to creating a more productive back office.