The Wellness Data That Matters Most

The Wellness Data That Matters Most

Data, data, data. There’s a lot floating out there. And sometimes it’s hard to separate the good from the bad. When it comes down to it, health and wellness data should allow you to gain valuable insights, make decisions, and take actions that lead to your desired outcomes. It should help you do at least one of these three things:

  1. Plan
  2. Communicate
  3. Measure impact

If your data does none of these, chances are it will sit on the shelf or in your inbox. So then, what are the types of data you should be gathering and analyzing?

Best data

The best wellness data provides information about what is actually happening with your employees. It eliminates guessing games and highlights areas where you might choose to intervene.

Top medical conditions and prescription

This data shows what conditions are affecting employees and how they use prescriptions, as well as what the biggest costs are to the plan. It’s meaningful to slice this data by highest cost and highest prevalence, as both are important. Several actions you may take with this data include:

  • Tailor well-being programs for the top conditions of employees (i.e., a campaign on diabetes maintenance and prevention).
  • Evaluate carrier products and other partners who assist members with chronic conditions.
  • Make changes in prescription plan design that decrease financial barriers to refilling maintenance and preventive medications.
  • Route members to less expensive providers and services based on top conditions and associated care.
  • Provide targeted benefit communications for certain segments of your population (i.e., by location or business unit).
  • Develop consumer-driven education that connects to members’ financial well-being, which, as a side effect, has a positive impact on the plan.

Compliance and adherence to care

When a member has been formally diagnosed with a chronic condition, such as diabetes, high cholesterol, or coronary artery disease, a care plan is assigned to the patient. This care plan includes recommended actions they should take throughout the year to remain compliant with the care of the condition. Depending on your organization’s size, funding, and data analytics tools, you can see the top gaps in care for certain diseases and conditions.

The actions you take here might be similar to some of those above. Knowing the top gaps in care can also pave the way for communication around disease management. For example, you might choose to highlight resources available through the health plan that would assist with diabetic care, including A1c screenings in the doctor’s office, affordable testing supplies, and vision exams. Most often, a communication of this nature would go out as a blanket notice to all employees.

Better data

Better data is especially helpful to supplement “best”data, because it starts to look at employee behavior, rather than hard statistics and dollar amounts.

Cohort biometric screening data

Having access to multi-year biometric data for the same group of individuals can lend insight into annual trends in your population, such as a rise in high blood pressure or seeing positive impacts from weight loss campaigns. Cohort data works best when employee turnover is low, contributing to a larger cohort group. While this data doesn’t tell you if members have been diagnosed with or treated for certain conditions, it helps you measure the overall, long-term impact of well-being programs.

Wellness survey feedback

If you look at well-being from the angle of employee engagement and culture, why not ask employees what they want? Surveying on what areas of well-being are of most interest to them individually (physical, financial, career, etc.) and how they envision their employer supporting them gives you firsthand insight and gathers buy-in. It also lets employees know that you hear them and value their opinion, which gives you a couple culture bonus points in itself. Often, when employers struggle with participation and engagement in wellness, it’s because programs target the wrong needs or interests. Be careful not to ask survey questions unless you intend to take action around the feedback you receive. For example, don’t ask employees if they would like an on-site fitness center if leadership isn’t willing to make that investment. Also, it’s important to refresh this data every few years as your population changes.

Good data

Although there are worthwhile things you can do with good data, it is often less informative and has a more myopic view of your overall program.

Aggregate biometric data

Since biometric data for a single year’s screening event is simply a snapshot in time, it’s only as important as how you use it. We often recommend employers relay this information back to their employees in an appropriate manner. The goal is not to place blame on individuals, but rather, rally employees behind health initiatives. Aggregate data also provides a quick benchmark to help you see top risks and how your population compares to the rest of the nation.

Participation data

Employers who make the best use of wellness data put little weight on sheer participation numbers. Participation data can be collected for the purpose of rewarding incentives or measuring the success of an initiative. Too often, though, employers rely on participation data to reflect engagement in wellness, when these are two distinct things. Employees can participate–or not–for many different reasons, not all of which are tied to how engaged they are and whether or not they’re improving health outcomes.

Perhaps now is a good time to take inventory of the health and wellness data you currently receive—be it monthly, quarterly, or annually—and decide what insights you’ll be able to gain. If there is valuable data you think you should already be getting that you aren’t, ask for it! Finally, consider which team member you should share this information with to make better decisions collectively. Here’s to transforming your data into more than just numbers on a page!


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