November 22, 2022
The health insurance and benefits industry has a data problem
In today’s world, data quality drives results—for good or bad. And for all the progress that’s been achieved harnessing data in the health insurance and benefits ecosystem, data problems are rampant.
We speak to you from the trenches, which is to say that Ideon is in the business of not only data connectivity, but also data accuracy. And in our experience, about 10% of employee enrollments have existing data problems—from incorrect social security numbers to inaccurate effective dates—that can and often does cause significant issues for members, employers, and carriers.
The fallout of poor data throughout the ecosystem includes:
- Members are arriving in doctors’ waiting rooms, only to be told their coverage is not in place. Scenarios like these are all too common. And while these problems are solvable retroactively, they cause undue frustration and time-wasting for members.
- Employers are paying for coverage for employees who have long ago jumped ship, when termination is not done properly. And new employees may resent their employer when their benefits experience is rife with coverage issues.
- Brokers and consultants are often responsible for ensuring coverage is intact. They also may be the ones charged with entering enrollment data into a broker portal or enrollment platform. So when there’s a data issue, they often bear the brunt of the blame. Aside from fielding calls from irate HR managers, brokers often take home lower commissions when enrollments are incomplete owing to data issues.
- Carriers have been forced to set up costly systems and processes—such as large customer service operations—to deal with the consequences of poor data quality. Bad data can also mean significant premium leakage. And importantly, while many look to insurers to solve all data problems, it’s impossible for them to do so without the help of all the other entities involved.
Bottom line: The industry’s “dirty data” problem is pervasive, with detrimental ripple effects at scale. Consider: In our estimation, nearly 9 million employees in the U.S. could have a coverage issue.
What’s being done? Not enough. Many constituencies in the industry see data issues as unavoidable and insurmountable, resigning themselves to addressing the symptoms, not the disease.
We get it: These issues are daunting. They’ve been institutionalized to a startling degree. But with industry-wide collaboration, they’re also eminently solvable.
At Ideon, we have some thoughts on how this can be done. You can learn more about them here.