Let's be honest: terms like “data analytics” tend to make many people's eyes glaze over. The idea of number-crunching health care data sounds like a good way to improve benefit plans, but it also sounds like a complex subject—and it is.

Brokers who have been dealing with data analytics say this is why a good, reliable partner is so important when delving into this area of technology. Consumer education and communication are important, but like retirement investing, most laypeople aren't going to want to get into the weeds of data analytics and how it affects health benefits. Having an expert who can explain the concepts and strategies will do a lot to make data analytics truly useful to companies and their employees.

When people talk about Big Data in health care, they aren't kidding: A 2016 report by the National Institutes of Health estimated that electronic health records in the U.S. will gather 25,000 petabytes of data annually by 2020. A petabyte is a million gigabytes.

“The decrease in the cost of storage has enabled an exponential distribution of data collection, but the ability to analyze this quantity of data is the center of gravity for 'big data' in health care,” the NIH report said. “Other industries such as astronomy, retail, search engines and politics have developed advanced data-handling capabilities to convert data into knowledge. Health care needs to follow their lead so that decisions regarding organizational objectives and goals can be met.”

Wrangling Big Data is a big job

“From our recent experience, I can tell you it's a daunting task to evaluate this space,” says Rex Wilcox, a specialty health and analytics consultant with IMA Financial Group. “Most employers don't have the bandwidth to take this on in terms of implementing it, managing it, and knowing how to use it. That's why they should hire a broker or consultant.”

Rob Piazza agrees. “You have to partner with an expert,” he says. “It gets really complex; if you're going to work with a PBM, for example, your broker can help you find the right one.”

Piazza, product manager of analytics at Charleston, South Carolina.-based Benefitfocus, says firms like his are helping companies take a holistic view of health benefits by combining eligibility, enrollment and claims data into a single source.

For those who do find the right fit, he says data analytics can improve benefit plan design and save money. Piazza's company works with a self-funded employer of more than 4,000 employees to offer more competitive benefits. By identifying cost drivers and instituting disease management, combining high deductible health plans (HDHPs) with voluntary benefits, and creating a program to provide free diabetic medications and supplies, the employer was able to save almost $5 million in claims costs.

“You have to know your numbers,” Piazza says. “The good brokers are good at that.”

Hitting your targets

Several analysts stress that companies should see data as a tool to achieve certain outcomes.

“Brokers, consultants and employers should identify goals prior to investigating health care analytics,” says Dan Ross, president of Med-Vision, a consulting firm based in Tampa, Florida. “For example, many consultants and brokers utilize analytics to create simplified dashboards highlighting and benchmarking plan performance.”

Ross notes that for those trying to control health benefits costs, there are few better places to start than with the data. “What other critical expenses do employers handle in the same manner they do health care?” he asks. “An employer will hammer a sales employee for overspending $50 on a client lunch; however, he will not notice their health plan is purchasing MRIs at prices varying from $300 to $5,000.”

Chris Davis, director of health management and claims informatics, Regions Insurance, says when data is used to see where the cost drivers of a health plan are, it's much easier to address those costs. “It's not uncommon for up to 70 percent of your claims to be driven by less than 10 percent of your population,” he says. “So, when you're making large plan design changes, it should be less focused on that other 90 percent and more focused on the 10 percent driving the disproportionate amount of cost.”

Davis says by identifying the areas of spending, employers can work on finding the right facilities and disease management programs to address specific issues. “The data allows us to create steerage opportunities, communication opportunities and employer education tactics,” he adds.

For years, health care researchers have known that there are wide disparities in the cost of services from state to state. Analysts are now talking about significant variance in quality and cost from facility to facility. In the past, employers had little information on these variances. But that is changing, says Keith McNeil, partner at Arrow Benefits Group, based in Petaluma, California. (Ross, Wilcox and McNeil are members of Health Rosetta, a health industry consulting consortium.)

“While the data analytics can be great for potentially finding next year's large claim—the so-called 'ticking time bomb'—they can also show the huge disparity in costs charged for the same procedure,” he says. “The variance can be over 2,000 percent! If the plan knows that, it can set up ways to reward members who use low-cost providers; as has been shown many times before, high cost does not translate into better quality.”

Pushback from employers

It may seem that data analytics are most appropriate for large employers, but brokers also see benefits for self-funded companies with relatively small workforces.

“Smaller companies may think there could be a HIPAA violation; they think that their data isn't relevant, they've never really used these tools before,” Davis says. “They've only been given reports from their carriers, but those carrier reports often withhold a lot of relevant information to make an informed decision.” This data could be key to addressing cost and quality issues, he adds.

Ross agrees. “Insurance company plan reports typically exclude any meaningful data considered actionable,” he notes. “Added to this hidden data is the unfortunate fact that employer plan sponsors sign contracts typically forbidding auditing.”

Analytics lead to creative health plan design

Piazza notes that better data leads to health plan designs that can better fit the population of an employer. High-deductible health plans, while seen as a way to save money by shifting some costs to employees, can also discourage utilization, which can lead to more serious health costs down the road.

“HDHPs really do save money, but when I look at groups that contain costs well, they inevitably say they've increased other options for plan members,” he says. “They invest in a hospital indemnity plan for every HDHP member, or get a communication budget for a marketing campaign so people understand their benefit plan better.”

That creativity—going the extra mile—can make a real difference in a complex field like health insurance, Piazza says. He notes that many people on HDHPs don't understand that their preventive care is covered at 100 percent, and that if members think only of the high deductibles with their plan, they will use the health care delivery system very differently. Better education leads to better outcomes, he adds.

“Communication is one thing that really ties back to our space,” he says. “We want to get to the point where we're making good recommendations, based on the data that are right for you and your company.”

Instant Insights /

Using Big Data to design better health care plans

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