A Mistake in the Making: How to Eliminate Claims Processing Errors

People at all levels of organizations want quality improvements, but they often don’t understand how to make them happen. Processing errors are far from random events. Some processors consistently have higher error rates than others. There are even persistent differences in error rates among managers. This is because many errors are caused by patterns of behavior and work habits that last over time. Managers who can identify and change these patterns can substantially lower the error rate on their team.

Unfortunately, managers generally don’t have the time or the ability to understand what processors are doing, or how to help them improve. With teams as large as twenty or twenty five processors, it’s unrealistic to expect that managers could take the time to identify the subtle differences in work patterns that lead to errors.

When we analyze employee performance data, we consistently see a gap between actual employee performance and their potential performance. Some of the most interesting data comes from looking for the work patterns that appear in conjunction with errors. Although the presence of a pattern doesn’t always mean that a particular claim will have an error, we have found there are clear behavior patterns that indicate a mistake may be in the making.

The role of managers is to help employees perform at or near their potential. A critical way they can do this is to be on the lookout for the specific behaviors and patterns that are most likely indicative of an error about to be made. Finding these behaviors and then implementing the small changes to correct them can have a large, immediate impact on quality.

We’ve crunched the data and discovered clear behavior patterns that indicate an employee is about to make an error. Here are a few things you can look out for:

Speed

• Too Fast: The “do it fast or do it right” tradeoff is very real. In fact, the fastest workers tend to have error rates that are three to four times that of the “best practice” workers. When employees speed up their work, they often skip steps in the process. Their quick work may result in terrific output, but also in terrible accuracy.

• Too Slow: Even worse are the slowest workers. The people who tend to struggle to complete a task, or are unsure of the process, are even more likely than the fast workers to make an error.

Application Usage

• Help Desk: In one study, more than 20 percent of payment errors involved an employee checking the knowledge base. It’s unfortunate that when they recognize that they have a problem and turn to the knowledge base, the information they find there doesn’t prevent them from making an error. Of claims without errors, employees checked the knowledge base only 7 percent of the time.

• Email: Switching to email in the middle of a claim is a strong indicator that a mistake will be made. Either the employee is looking for help, or he is just easily distracted. Claims with errors are more than twice as likely to include an employee using email while the claim is open. If someone is working on complex claims, but they drop whatever they are doing every time they get an email, they can’t possibly maintain the kind of focus they need to perform efficiently.

• Claim Research Tools: There are some people who use the research tools to check eligibility or coordination of benefits, or to dig into other information on the claim. And there are other people who simply don’t use research tools. What the people with the fewest errors have in common is that they are always researching. Those with the highest error rates rarely use any of the research tools.

Other Indicators

• Breaks: People who take a break in the middle of a claim are more than twice as likely to make a mistake when they come back to it. This is a situation where the person is having a hard time staying focused on their work and it’s clearly better to finish the task before the break.

• Managers: While they aren’t a behavior, managers have a huge impact on how people work and what their resulting error rate is. Managers can motivate and inspire employees, or do the exact opposite. Comparing team error rates shows that some managers have error rates that are four or five times that of others managing similar teams. Other employee engagement measurements, including productivity, show similar team differences.

To really lower the error rate across the entire pool of claims processors, it is crucial to have visibility into their work habits and to use the insights gained to direct specific actions that lead to improvement. One of the most important ways you can understand employee performance is to understand how people use their time and the tools available to them. Looking at patterns of behavior like idle time, outlook usage, and how often they use research tools or calculators goes a long way toward understanding performance differences and how to achieve performance optimization. The real key, though, is reinforcing new behavior over time so that the new work habits can take hold. Just pointing out the problem isn’t enough.

Daniel Enthoven, vice president of marketing at Enkata, located in Redwood City, Calif., has twenty years of technology and call center experience.