‘Big Data’ Can Improve Value of Health and Savings Plans

Data analytics can target communications to those most in need of aid

By SHRM Online staff April 29, 2015

Several national experts described how employers are making a major commitment to capturing and analyzing the vast amount of health and retirement data in their benefits plans in a report published in the April 2015 issue of EBRI Notes. “Measured Matters: The Use of ‘Big Data’ in Employee Benefits” draws on presentations made at a December 2014 policy forum in Washington, D.C., sponsored by the nonprofit Employee Benefit Research Institute (EBRI).

The summary below is edited from the report with EBRI’s permission.

Health Data Can Foster Engagement

Mike Manocchia, director of consumer health engagement analytics at Cigna, described the health insurer’s use of databases to create a “Health Matters score” that provides physicians with information that can help improve patients’ health behaviors.

“We’re trying to confirm certain amounts of behavior and behavior change, associate that with a value, and provide that in terms of our Health Matters score for physicians to set priorities with their patients,” Manocchia said.

How health care providers use the list of individual health-improvement opportunities with patients “is influencing our contractual relationships” with provider groups,” he added.

Along similar lines, Alex Baldenko, a data scientist at Aetna, said a challenge was to “crunch” siloed data regarding enrollment, demographics, medical and prescription claims, and patient-provided information via the website or phone.

Connecting these sources into a single record gives a holistic picture that is particularly useful in modeling the likelihood of hospital re-admissions, for instance, and provides “an opportunity to personalize messages that increase engagement.”

Shari Davidson, vice president at the National Business Group on Health, said about two-thirds of their member firms are currently using a third-party data warehouse to help them analyze their health and wellness information, while others rely on their health insurance carriers to provide the data. Most commonly used are medical claims and enrollment, pharmacy, and mental health data. By law, this data is de-identified for the employer to protect the privacy of employees.

Davidson said employers are also looking to segment and target workers so vendor partners can implement “just-in-time outreach” and send specific messages that better address workers’ health needs.

Expanding the use of preventive care is an example. “Based on market data, we know that women are more likely to take care of themselves when they see how it could impact their family, while men do it more if they know they can save money,” Davidson said. “So we created postcards and e-mails and text messages based on the statistics we identified to encourage employees and family members to utilize this important benefit.”

-----------------------------------  -------------
Data analyzed by third parties can
be used to urge employees to
take advantage of health benefits
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Mark Englizian, Walgreen Co.’s group vice president for HR business strategy and solutions, described how the drugstore chain segments its covered employees into low-, medium- and high-risk groups. After doing this, the company realized that just 10 percent of its plan members generated 65 percent of its total health care expenditures.

For those who are healthy, preventative programs make obvious sense, while for those who are ill, intervention programs are seen as the way to improve health and control costs. But for both, Walgreens’ goal was “to make sure that we were engaging as many of our team members as possible to make sure that they were beginning to take responsibility and accountability for their own health care,” he said.

Retirement Data Can Improve Savings

Using behavioral economics can improve retirement plan participants’ decision-making, such as by not offering too many choices for those who are likely to be overwhelmed by complexity, suggested Christopher Goldsmith, vice president, client relationship manager and behavioral economics initiative leader at Sibson Consulting.

“There's a clue-seeking bias when people face complexity, and they look for clues and often make suboptimal choices because of that bias,” he said. “Organizations should become better at this in terms of communication campaigns” with positive goal-directed messages, and “influence choice-making with nudges based on behavioral economic techniques.”

Goldsmith cited one study that showed workers photos of themselves at their current age and, using age-progression software, what they are likely to look like at retirement age. Those who had seen their age-progression photo contributed significantly more to their retirement accounts.

Showing age-progression photos
upped participants’ contributions to
their retirement accounts

“It's about making it real for the individual by creating a consumption frame of reference in addition to a financial focus,” Goldsmith said. “You say to that 35-year-old: ‘Save 9 percent of pay and you may eat steak and lobster, live the good life, and travel to exotic locations around the world when you retire—or contribute 2 percent of pay and eat processed baloney and vacation at your local rec center.’”

Plan Design Can Optimize Labor Management

Employers need to be aware of unintended consequences when they change their retirement plan, especially if people tend to stay in the workforce beyond normal retirement age, said Arthur Noonan, senior partner and actuary at Mercer. While there has been considerable press coverage about older workers delaying their retirement and blocking the advancement of younger workers, Noonan said there are some urban myths about how that actually plays out.

For instance, big data can help determine whether older, longer-tenured workers are more cost-effective than younger ones because of their higher productivity and value-creating efforts, or more expensive due to higher pay rates, health and disability costs. Also, do older workers actually account for higher health care costs when it’s the younger workers that are having children?

Data analytics also would be particularly useful in identifying which groups account for the most absenteeism, Noonan added.

Employers trying to structure their benefits plans to obtain the optimal workforce “need to understand what the real cost is of either delayed retirement or premature retirement on their organization. And if they need to move the needle one way or the other, they need to understand what that cost is,” he said.

The ideal situation is “having the right things in place so that that on-time exit can occur and the proper velocity in advancement of the rest of the workforce is in place.”​

Related SHRM Article:

'Big Data' Is Shaping Employers' Benefits Strategies, HR Magazine, September 2015

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