Big data was the craze for 2014, and from our experience in the employee benefits management world we can understand why. It goes without saying that healthcare is a massive expense for American businesses, consuming upwards of 35% of company budgets annually. Too often, we have brought on new clients only to discover that they’d let hundreds of thousands, potentially millions, of dollars in misallocated healthcare dollars leak out their doors! In this blog, we’d like to share some areas where accessible healthcare data can immediately help employers uncover the errors and make decisions to reduce their annual healthcare cost.

What do we mean by accessible healthcare data?

Think about the way many organizations, perhaps your own, manages healthcare eligibility and enrollments. It usually goes as follows:

1. Hold an open enrollment period
2. Collect paper enrollment forms
3. Fax forms to the insurance carrier or type in information manually into the carrier’s enrollment portal
4. File away enrollment papers, only to return for qualifying life events or the following year’s enrollment period

Unless your HR or benefits manager is taking the time to record all of that enrollment information into a database or eligibility management system, the data is virtually lost, or at least not in any format that helps your make informed decisions about optimizing your healthcare plan.

Where accessible healthcare analytics can save!

One area where we’ve coached clients on using employee benefit management data to trim down their healthcare budget is evaluating how increasing coverage tiers can cut premium costs.

Transitioning to a multi-tiered plan may be a way of finding quick savings. Depending on the dependent status of your workforce, there may be a significant percentage of the population that is married without children. Discovering this with a quick analysis of accessible healthcare data, an employer may make the decision to move from a two-tiered single/family coverage option, to a 3-tiered single/2-person/family coverage option. Oftentimes, employers are paying for coverage that’s not being used because it doesn’t fit their current population.

Another area where accessible healthcare data can translate into immediate savings is through improved management of your Medicare eligible retirees. At Benetech, we have witnessed clients hemorrhaging hundreds of thousands in misallocated medical claims due to an employer’s failure to shift retirees to Medicare as the primary insurer once they reached age 65. Through the Tax Equity and Financial Responsibility Act of 1982 (TEFRA) and the Deficit Reduction Act of 1984 (DEFRA), the primary claims payment responsibility shifts from the employer to the government once retirees become Medicare eligible, but this is not automatic.

This oversight has an even greater impact on employers with self-insured plans and/or experience-rated contracts, where claims history serves as the basis for subsequent years’ premium levels. For example, if an employer’s claims history is $20M when it should be $18.5, that employer (and all within that experience pool) get slammed with an extra $1.5M of claims history, impacting their subsequent annual premium equivalents.

In one particular case, we uncovered an 86-year-old retiree who had never been switched over to Medicare prime. That’s 21 years of misallocated claims payments during the most expensive healthcare years of a person’s life!

For self-insured employers, tracking the ages of covered retirees through accessible data from employee benefits management services on a monthly basis allows them to monitor their retiree population for Medicare eligibility.

In short, there are a lot of life events that make an employer’s healthcare cost a moving target, and it’s not enough to revisit that data once a year. With the potential to find immediate savings with accessible data, employers cannot afford to be asleep at the wheel when it comes to managing their enrollment population. In making informed decisions when it comes to managing healthcare expenses, the first step is having the company stats at an employer’s fingertips through an accessible benefits management system. Because when the data is out of sight, so are the potential errors.