Are You Confident in Your Ability to Analyze Healthcare Benefit Data? If Not, You’re Not Alone

March 3rd, 2020

By James Vertino, Chief Executive Officer

The rewards for leveraging health data analytics can be significant in many ways – improved customer experience, more control over health plan design and increased profitability. No wonder that advanced data analytics is gaining favor as a strategic tool in the insurance industry.

Are you making the most of your data?

Don’t be intimidated by all the data already at your fingertips. It is merely information that, when analyzed closely, can provide you with valuable knowledge that will guide your decision-making. Data, when used strategically, gives health plan leaders more control over care management and disease management programs – and the bottom line.

The data analytics trend has gathered increasing momentum in recent years, and for good reason. At my company, self-funded plan sponsors who have embraced the analytics movement have seen huge benefits. They have reported:

  • Healthier, more satisfied plan members
  • Higher value care delivery
  • More informed decision-making
  • More insight into how well their plan is performing

These things are priceless to a plan sponsor. Tech-forward TPAs like EBMS provide the data analytics that give clients the information to develop strategies and gain control over plan performance.

Isn’t that where you want to be?

Three years ago, Deloitte found that two-thirds of health plan executives it surveyed said that using health data analytics was a top priority. In 2017, Capgemini, a technology consulting firm, identified 10 emerging trends in the insurance industry and highlighted the use of analytics as one of them.

What is driving these trends? New reimbursement models, such as value-based purchasing and pay-for-performance, have focused attention on containing costs by keeping patients healthier in disease- and care-management programs.

When health plans put data analytics and predictive modeling to work, it is easier to identify patient populations that would benefit from special care-management programs before their health deteriorated or an expensive medical claim occurred.

Data can also help plans reduce spending and improve the patient experience by identifying and closing care gaps. For example, analyzing data on patients with chronic conditions may prompt a change in how utilization patterns are managed and care benchmarks are met.

When you use data analytics to gain more understanding and more control over your plan, you can see how fast costs are rising compared to the national average. You can drill deep into your data to learn more about claims, prescriptions, lab, and biometric evaluations.

Even though our experience and industry trends clearly show the value of data analytics, there are many brokers who still haven’t embraced this tool. Recently, my company interviewed 15 brokers to understand how much they used data, how well they knew how to analyze and interpret it, and how often they were using it with clients. Here is what we found:

Most brokers don’t feel comfortable translating the data to useable knowledge. They admitted to not knowing how to use data to change course on healthcare plans.

Most brokers interviewed didn’t use data or analytics, with the exception of maybe once a year. They told us that reviewing reports more often than at annual renewal is a burden for their overtaxed schedule.

Some brokers didn’t feel confident they could use the analytics to impact plan designs. In fact, most said they didn’t think the clients would appreciate the insights that data brings.

Though the data analytics movement is accelerating, there are many brokers who are not on board. Even for those who are, there are challenges to using information to strategically make care decisions. The Deloitte survey highlighted these challenges:

Lack of expertise: It is difficult to recruit and train analysts who can compile reports and extract meaning from the data. Turning raw data into business intelligence is not easy. Making care-management decisions based on a flawed analysis could have unintended outcomes.

Quality of data: In the Deloitte study, 60 percent of those surveyed worried about data accuracy, completeness, relevance, accessibility, and real-time status. Do you really know how your plan is performing? Is your staff capable of interpreting the data from biometric evaluations, prescriptions and claims?

To trust the data and the analysis that comes from it, we must become comfortable with data governance – the overall management of data assets. Data must be available, accessible, accurate and secure. Only then will you have meaningful – and rewarding – data analytics like those provided through EBMS.