How data mining can help build a health and wellness program

Raymond Kim

It seems you can’t look at a business-oriented website or go to a conference these days without hearing people talk about big data. The evolution of the Internet has given us the ability to accumulate a tremendous depth of information about a wide variety of topics. Businesses are swimming in data about their customers.

Of course, this data is nothing without insight—that’s where the rubber meets the road. Organizations armed with a deeper understanding of audience behavior have a huge advantage over their competition. This truth applies to employers and gaining knowledge about how their employees use their group benefits. The more you know and understand about benefits utilization, the more you can tailor your program to suit participant needs.

Such insight requires data mining, defined as collecting and analyzing data to create understanding and drive informed decisions. What you’re trying to do is to identify patterns and trends to glean information about what you can proactively impact in the future. This process can be very helpful in the process of designing and measuring the success of wellness programs. Health and wellness has become a significant trend for employers over the last several years. According to an IBISWorld report on corporate wellness, U.S. businesses spend $2 billion annually on worksite wellness initiatives.

Data mining can verify suspicions or uncover issues about benefits utilization. Your findings can provide the knowledge and tools to drive a higher-level discussion as you consider whether to make the case for investing in wellness, or to change course in an ongoing initiative. Data mining is particularly useful for organizations with more than 100 covered employees on their employee health benefits program because the information becomes more meaningful as the sample size increases. Additionally, this is the threshold at which many carriers start including group claims experience into rate development.

Mining data is a matter of rolling up your sleeves and drilling down on specific information. It’s often best to begin with assumptions and verify or disprove them. This process requires an understanding of what you’re looking for and a wider contextual view of the industry and population demographics. You can speak with your employee benefits consultant about performing this task, or you can get the information from your insurance carriers and conduct an analysis yourself.

At a minimum, employers should examine certain metrics like utilization statistics and average cost per variable such as gender, claimant, and dependent status within certain key benefits like:

  • Office visits
  • Emergency room use
  • Out-patient surgery
  • Hospitalization occurrences
  • Prescription drugs

Examining data in these specific buckets will lead to an understanding of plan performance and will provide additional insight to help make more informed health and wellness program decisions. Performing deeper dives into the data may reveal specific insight into your population’s preventive care compliance, medication adherence, and most prevalent disease states and cost differentials.

Understanding these data sets can sharpen the focus on how you design your group employee benefits package and wellness programs. Data mining is the way to activate the potential of big data, and employers should consider the concept.


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