Three Hurdles EmployersAre Overcoming to GetActionable Benefits Insights

Think about the big things on your to-do list. Maybe it’s remodeling your kitchen, organizing your endless email inbox, or finally starting that long-planned workout routine. These are daunting tasks that you know you need to do. These, and many others, involve lifestyle changes, giving up some of your time, and learning new skills. And that’s why it takes us so long to get started.

At Artemis Health, we hear a similar story when it comes to adding a data solution to your benefits strategy. It’s a big task. You’re not sure you’ll get the data quality you need, and data is competing with other initiatives. But you know it would be great for you and your business.

In a recent joint survey with Employee Benefit News, we found a whopping 86% of you would like to add benefits data and insights to your toolbelt in the next 12-18 months.

Learn more about theArtemis Platform at:

artemishealth.com

Likeliness to Use Benefits Data Analytics in 12-18 Months

3%9%

26%

60%

Somewhat likely Very likely Don’t knowNot at all likely Not very likely

3%

Just knowing that something is a good idea isn’t the magic bullet you need to actually do it. But we’re here to help. In this guide, we’ll walk you through some of the hurdles commonly faced by benefits professionals who want to use their benefits data but don’t feel like they can take the next step. We’ll show you how to face these challenges, re-think your objections, and find the will to move forward with a benefits data solution.

Benefits teams are busy. They’re often just 4 or 5 people meeting the needs of thousands of employees and members. They’re spending an outsized amount of time dealing with benefit program vendors, conducting Open Enrollment, implementing new programs, or communicating with employees, and they’d like to be able to devote more energy to interventions that matter to employees.

For some benefits leaders, data analytics is just another thing that gets pushed to the backburner. But we know that it can work to reduce the time spent on programs that don’t work and maximize the resources available.

Let’s look at an example from a real employer. We asked a benefit leader how long it would take for them to analyze the following info:

The Artemis team has a lot of conversations with benefits professionals about the challenges they face in their roles. When we ask you why you aren’t using a data solution currently, you usually point to the time it takes to learn a new system, implement a new partner, or find answers in your data. Here’s a real quote from a Benefits Director:

Hurdle #1: Time and Resources

“We just don’t have the sta� or time to devote to learninga whole new system. We would have to go through a longlearning curve to use a data solution.”

Here’s another from a Senior Manager of Healthcare Strategy:

“The biggest barrier to doing data analysis is the time ittakes to conduct the analysis itself.”

How many high cost claimants are on your benefits plan?

What are the top five conditions a�ecting those high cost claimants?

They estimated it would be about three months for them to receive a report on this data from their consultant. While some benefits teams would have this information on regular reports or be able to pull it together in a few days or weeks, others will be waiting for months before they can take action. With a great data partner, employers and their consultants could have this info at their fingertips within minutes. Artemis’ solution presents this particular analysis as a “Standard Story,” a pre-built report that’s always available to customers.

So when you consider the overall time spent waiting for access to data, adding a data partner could actually save a benefits team time and resources. With just a few clicks, they can access data quickly, learn key insights, and plan actions to help them save costs, evaluate the e�ectiveness of their programs, or help members access needed care.

While learning any new system is certainly an obstacle to overcome, a good data partner will also prioritize ease of use and appropriate training. Employers should look for a data solution that can be used by novices and seasoned analysts alike, and one that provides analytic support throughout the year to account for changing priorities and strategies.

Data quality is on the mind of any HR professional who wants to make data-driven decisions. We asked HR and benefits leaders, “What is the biggest barrier you face in benefits analytics?” While the top answer was the time it takes to do analysis, data quality was a close second at 16.6%.

Hurdle #2: Data Quality & Security

Employers should look for a data solution that can be used by novices and seasoned analysts alike, and one that provides analytic support throughout the year to account for changing priorities and strategies.

If you can’t trust your data, you can’t trust your decisions. And you have a lot of decisions to make:

Data quality is a major concern for employers, so it’s naturally a major concern for benefits data platforms as well. Artemis is addressing this concern with employers through tech-enabled services. We use an innovative, next-generation data management tool that was built specifically for benefits data. It automatically flags data quality issues for early identification and quicker resolution. It also creates consistency from one data refresh to another, and automates many processes unless human intervention is required.

Self-insured employers concerned about data quality should look for a data partner with a strong data implementation and quality assurance process. While fast, automated data integration is desirable, a great data solution should also include a collaborative QA that involves both the customer and the vendor’s team.

Security is also a barrier for many who would like to use benefits data but haven’t yet made the leap. Some benefits leaders tell us they know that a benefits partner evaluation will draw a lot of scrutiny from their security and IT teams.

This is a tough one, though not a surprise. HR teams, Risk Management Teams, and IT teams are the least likely to take on projects or services that pose a risk. Our best advice in these circumstances is to get your IT security team involved early in the evaluation process.

Whether to add, keep, or remove a wellness program

Expanding or narrowing your network

Where your onsite clinics will have the biggest impact

Forecasting next year’s healthcare spend

Planning formulary changes

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Self-insured employers concerned about data quality should look for a data partner with a strong data implementation and quality assurance process.

Data platforms like Artemis will have a robust security plan in place, including a data architecture strategy, end-to-end encryption, HIPAA compliance, and independent security audits. We find that if we can reassure security teams early in the process and explain our procedures and policies, it helps benefits leaders make the case for a data solution.

The cost of a data platform is one of the most common hurdles benefits teams face. They understand the value of benefits data analytics. They recognize the advantages of having access to all their data in one place. And they know they’ll be more e�ective benefit managers with real-time analyses and insights. But it’s not always in the budget to take the next step.

Here’s what employers are telling us:

We don’t take this concern lightly, and we understand that not every good idea can be implemented every year. However, we’ve worked with many determined benefit professionals who have successfully justified the cost of a data solution. They’ve had success with two strategies:

Hurdle #3: The Cost of A Data Platform

They have other programs they’re investing in, and data analyticsis just one in a long list.

They know data analytics is important, but the cost of a benefitsplatform is hard to justify.

01 Showcasing the cost savings you can find in your benefits spend

02 Highlighting the need to make future benefits decisions with data

Let’s look more closely at each of these:

info@artemishealth.comartemishealth.com

If these hurdles or others are preventing you from making the most of yourbenefits strategy, get in touch. We’d love to show you how to unlock the powerof your benefits data.

© Artemis Health Inc.

When you’re evaluating a wellness vendor, making changes to your network, or looking to add an onsite clinic, can you really make those investments without data?

An estimated 30% of healthcare spending in the U.S. goes to waste, and employer healthcare dollars are no exception. If you’d like to make the case for investing in a data solution, start with the benefits spending you’ve left on the table. Artemis’ Actionable Overspending App is a good example; it gives an instant, impactful view of benefits overspending in five categories: in-network variance, out-of-network spend, avoidable ER, inappropriate Rx quantity, and ine�cient Rx.

As you can see in the illustration from the Artemis Platform, for some organizations this can be in the millions of dollars. If cost is a hurdle, you may be able to pay for a data platform with the savings you find using the platform.

The second strategy to justify the cost of a data partner is to think about the future. When you’re evaluating a wellness vendor, making changes to your network, or looking to add an onsite clinic, can you really make those investments without data? What if they don’t work? What if you spend all the time, energy, and money implementing a chronic condition management program only to find out it doesn’t make an impact on employee health?

That’s where data is critical to benefits decision-making. Before you add one more program or make one more adjustment, you need access to actionable benefits data. It’s a crucial step in the day-to-day of providing great benefits to employees and their families. A great data solution will help you stop and see if the programs you’re using are working, and if new vendors and programs will actually provide ROI. Don’t try a new program, do the heavy lifting of rolling it out, and watch it fail. Use your own benefits data to avoid the pitfalls and get better results from your benefit programs.