Program measurement is a fundamental aspect of managing employee benefits, though it’s not an easy task. The average employee benefits team is managing 10+ benefits programs, and that means 10+ large, complex data files to comb through, look for trends, and try to determine trustworthy insights. Think about your own employee benefits plan. You’re probably working with vendors and carriers for:
It adds up to a messy mountain of data, and it’s not easy to sort through the haystack to find the “needles” that help you determine whether a program is really helping your members get healthier (or helping you reduce costs).
Artemis Health recently shared best practices for measuring benefit program performance, including some tips for types of metrics to consider. In today’s blog post, we’ll share two more best practices and some examples from our work on employee healthcare analytics.
One of the most common questions Artemis’ analytics team gets from customers is, “How do we know which metrics to track?” It’s a good question, and it’s difficult to answer because the goal posts often move. Each population is unique, so the “starting line” will shift for, say, a tech company with lots of recent college graduates compared to a manufacturing company with majority union employees.
However, there are two solid ways to ensure you’re identifying the right metrics to accurately measure your programs.
The benefits industry has a number of great resources to help employers with program measurement and ROI. Employers can use industry benchmarking data, like that provided by Milliman or the Integrated Benefit Institute (IBI), to see how they are performing against other organizations like theirs. Many also tap risk score methodologies like MARA as a good way to see how their population compares to others.
Artemis uses a number of industry-recognized methodologies like these to ensure our data is useful for program measurement. One good example is our Actionable Overspending app, which uses a proprietary data model to identify wasted and inefficient benefits spending.
If an employer were to embark on an initiative to direct employees to the appropriate point of care, they might start with metrics like:
In addition to tapping industry standards, employers should be prepared to use custom metrics to better reflect their real-world needs.
Artemis worked with an employer client, their consultant, and a diabetes care management vendor to set targets for program enrollment, key engagement metrics, and compliance with best practices for patient care. Their employee population consists mostly of long-haul truck drivers, who are seated behind the wheel for long hours and eating at fast food restaurants on the road. This combo led the employer to set more modest targets for cost savings but aggressive goals for participation and Rx compliance.
If this same employer was rolling out a virtual musculoskeletal health/physical therapy program, they would have very different goals and metrics in mind due to the nature of the work environment. In working with this vendor, the employer and Artemis knew what we would be measuring ahead of time, and the vendor knew exactly which metrics to track and provide in their data feeds. We worked together on an approved file format that made data integration faster, more accurate, and easier for everyone involved. Employers who set clear goals and understand what a vendor can or can’t offer up front will set themselves up for success later.
This leads to our last program measurement best practice, which is to get your data partner(s) involved in the process. In our most successful case studies, the employer’s team, their consultant or broker, and their analytics solution were all involved in vendor evaluations, data implementation, and ongoing program monitoring.
Using a data analytics solution helps an employer pull in hundreds of data points, synthesize the information, and communicate back to carriers, disease management programs, wellness vendors, and ultimately, to the affected population. With the help of seasoned analysts, whether they’re in-house or at a consulting firm, employers can quickly find insights that enable action.
There are a few things to look for in a data partnership that will help ensure you get the most from all your other programs:
We hope these program measurement best practices help you make the most of your benefit offerings and your data.