Consultant at Group Alternatives
May 17, 2018
I like lists. Work lists, home improvement lists, shopping lists. My beautiful and loving wife will make lists, but sometimes those lists are based on what she thinks we need. Has your spouse ever asked you to go to the grocery store with their list of “needed” items? I’ll bring home the grocery items from the list and start putting them away in the refrigerator or pantry, only to realize that we’ve duplicated some items while we “forgot” to purchase others. My frustration lies within the crucial missed step of taking inventory, which leads to both “forgetting” items and duplicating items. A good list begins with knowing, “What do we have in the fridge?” Only then can you assess what you need.
In the world of healthcare benefits, similar to grocery shopping, you need to understand your starting point. If you don’t identify cost-drivers for the health plan and member gaps in care, how can you accurately and efficiently predict future spend? How can an employer develop effective strategies for getting employees to focus on managing their health and well-being? Data analytics applied to medical and pharmacy claims, and biometric screening results can be used to identify gaps in recommended care, initiate outreach and predict future spend.
Healthcare data is complex. Identifying members across multiple data sets to create a picture of an individual’s health journey requires a level of analytic sophistication that was not historically available to most employers. The goal is to make the information actionable for both employers and employees. The challenge lies in presenting solutions to individuals at a time and in a manner that will make them more likely to take action.
Employers have historically attempted to address these issues by offering multiple programs designed to target individuals with particular needs. However, without sophisticated data and a comprehensive engagement strategy, these efforts are needlessly expensive and ineffective. The programs tend to duplicate each other’s features, and the layering of multiple vendors and touch-points adds to the complexity of the health benefits program. This lack of focus often ends up discouraging the very program participation they were intended to promote.
The sad truth is that it is difficult to get people focused on their health. Using a “Big Data” approach, we can aggregate data from multiple sources from medical claims, prescriptions and biometric screening results. We can identify an individual’s health status, and using this information, determine steps that can be taken to reduce future medical risks. We then can determine if gaps in recommended care exist to improve someone’s health, and if they do, initiate steps to get the employee to attend to these needs.
The additional benefit of applying a data-driven strategy to managing workforce health is the speed with which information can be made available, as the data is updated and reviewed on a monthly basis. This allows the employer to evaluate results and implement new strategies and programs to address continuing challenges. A good benefits advisor should be consultative in this review, providing not only insights from the trends reflected in the data, but also applying predictive modeling that shows where costs are likely to go in the future. Then, the right data analytics vendor provides an ability to track the results of any given implemented strategy and builds in accountability for all stakeholders: Is our strategy working to improve employee health and reduce plan spend? If results or engagement aren’t meeting expectations, let’s not waste time and money, but let’s find a different solution!
Employee populations can be ever-changing. Our goal at Group Alternatives is to improve employee health while reducing plan costs. Building strategies based on continuous data analytics and predictive modeling can have a significant impact on engagement, outcomes and medical costs. Wouldn’t you rather know your population’s cost drivers and gaps in care (what’s in your fridge?) before you go shopping for solutions that you may or may not need?