By Dan Openshaw

The successful optimization of employee benefits plans so workers and employers come out ahead is a shared goal among every organization, but one that’s a challenge to achieve.

Major barriers have always been the complications of accessing and aggregating the necessary benefits data given security concerns over protected employee information and limits on what can be safely shared. Getting your hands on the data at all is next to impossible if you’re not self-insured. But pressure from self-funded employers and consultants have surmounted such barriers and changed the game for benefits planning for self-insured, middle-market employers.

And not a moment too soon. As satisfaction with their benefits decline, three in ten employees would trade a higher salary for improved benefits packages. Better employee benefits analytics could help by bringing more rigor to how benefits programs are typically structured now:

  • HR departments often conduct employee surveys or undertake historical cost analyses without integrating workforce population data.
  • Not all employers explore what’s behind a workforce push for a new benefit.
  • Utilization reports are helpful, but don’t usually consider why benefits are being used.

Using data to dig deeper into benefits usage patterns provides a more comprehensive understanding of current usage disconnects, longer-term fixes and, importantly, enables you to move away from a one-size-fits all strategy that really doesn’t fit all and may keep costs unnecessarily high.

One area that’s ripe for analytics is the utilization of emergency rooms, as they are often overused for non-critical treatment. Analytics advance your understanding of age or cultural influences behind usage trends among your plan members. Better understanding may suggest benefit design changes or improved communication strategies to alter the trends and divert plan members to more convenient and cost-effective solutions like telemedicine or urgent care.

There’s a tremendous amount of low-hanging fruit to be picked, and not just on the medical side. Rising pharmaceutical costs make it critical to mine prescription claims data for insights that can lead to savings. In one case study, analytics on one employer’s claims revealed that over a one-year period, $173,019 was for an NSAID-antacid combination for 18 plan members. But through formulary adjustments, the coverage could be changed so the members could take the generic drugs separately for an annual savings of $75,000.

A strategic, data-driven employee benefits program should draw on data that’s aggregated from all your benefits, and goes deeper than merely basic demographics to uncover meaningful trends and insights. There is potential to integrate multiple data sets, from medical and pharmacy to biometric screenings and worker’s compensation. And, importantly, the data should be both current and historical in order to most effectively inform better benefit design and predict future needs.

The ability to make use of the vast amounts of data associated with their benefits programs doesn’t just give self-insured employers more control over a major cost center, but it also gives them a big opportunity to sharpen their competitive advantage with benefits that count in attracting and retaining employees.

HUB International’s employee benefit specialists consult with employers of all sizes and in all industries on every aspect of employee benefits program planning and management.