Who would be bold enough to declare that the bruising recession has been a good thing? Cyndy Nayer, that's who.

Never one to pull punches as she's worked to educate and promote the importance of value-based benefit designs, the president of the Center for Health Value Innovation says bluntly, "The recession was the best thing that happened to value-based design, because employers realized they were out of options. They knew they weren't going to get any more benefits dollars, so they had to work with what they had."

As such, Nayer cites research results that show 50% of employers now have a value-based design in place, which she defines as "a suite of insurance and standalone incentives to change behavior around prevention and wellness, chronic care management and care delivery."

Obviously, not all of that 50% hopped onto the VBD bandwagon since the start of the recession, but according to CHVI, 17% of employers have had a value-based design in place just for the last two years - perhaps more than a few of them recession-rattled converts.

No matter how employers became part of the VBD movement, Nayer believes the concept will continue to take hold in employer-based health plans "even as the economy recovers, because employers are seeing results" in terms of improved health outcomes, greater patient compliance to treatment regimens and of course, reduced costs.

Comparative effectiveness research offers 'greatest hope'

One of the initiatives that can help drive even greater results from VBD plans is comparative effectiveness research, believes Helen Darling, president of the National Business Group on Health.

"The purpose of comparative effectiveness research is to assess, determine and document the effectiveness of health interventions," both in terms of safety and cost-effectiveness, Darling says. "Not just, 'Does it work?' but, 'Does it work better than something else?'"

Since VBD is all about finding what works in terms of health management and improvement and attaching an incentive to it, comparative effectiveness research seems a perfect match.

Indeed, Darling says. "Everyone wants to know what works. Even without value-based designs, as patients and consumers we want to know what's effective and sometimes there are huge differences between the costs [of certain therapies] when the effectiveness is about the same. Those are things everybody wants to know."

The problem, though, is that "the [Food and Drug Administration] is not required by law to do anything other than determine whether something is effective and safe," Darling explains. In other words, a host of drugs are FDA-approved and deemed safe and useful to combat high cholesterol, for example. But, without more comprehensive and independent comparative effectiveness research, there's no way of knowing if one drug works better for a greater number of individuals than the others.

And not just medications. Darling emphasizes: "I've worked on health care costs my entire career, and I'm convinced that our greatest hope for improved health and health care in terms of reducing waste and improving outcomes is comparing the effectiveness of health coaching, drugs, devices, physician visits and screenings. It's not easy to do, but the concept is really very simple."

So what makes comparative effectiveness research so hard to do?

"The biggest thing hindering comparative effectiveness research is a lack of money," Darling says. However, the funding drought has been relieved by the American Recovery and Reinvestment Act (aka, stimulus package), which set aside $1 billion for such research projects.

"Having the money to do this is going to be the breakthrough," says Darling. "Now, the smartest people in the country are working on this and we're going to find instances where the most effective intervention is the least expensive."

Communicating effectively

But what happens when comparative effectiveness research results fly in the face of firmly established prevention or treatment guidelines? The uproar from last November's rollout of revised mammography frequency guidelines from the U.S. Preventive Services Task Force certainly could be considered a cautionary tale for communicating new data results.

Darling says the USPSTF announcement - that women in their 40s not get routine annual mammograms, but rather only get a mammogram every other year, beginning at age 50 - marked an example of what not to do when rolling out new health guidelines.

"They did a really lousy job rolling it out. It was garbled [messaging] about data that was complex, and there were no representatives from the women's health and oncology profession at the forefront explaining it."

She instead points to data regarding the harmful effects to women on hormone replacement therapy - specifically, how health professionals explained the data in terms the average patient could understand - as a better example of showing consumers how changing an entrenched health regimen could benefit them. "The American people, when evidence is presented to them in the right way by reliable sources, can be persuaded," she stresses.

Moving toward personalization

One group that doesn't need persuading about the importance of comparative effectiveness research is CHVI, led by Nayer and members like Brian Sweet, the chief pharmacy officer at WellPoint.

Sweet says WellPoint "has done a lot with comparative effectiveness, because with more than 35 million members we have the ability to build integrated databases to study what works, and we realize that claims data itself is limited."

He notes that the company's work in comparative effectiveness allows researchers to pinpoint "real outcomes that aren't discovered in randomized clinical trials. It's being more precise and reducing waste around the science that changing people's lives."

Nayer adds: "When you [only] look at claims data, there are some screenings or [other interventions] that don't have claims against them - how do you translate that? Comparative effectiveness allows benefit managers to construct subtle changes for people who could do better under a certain plan design than another."

Along those lines, Darling offers this example: "Say, for example, you have two drugs - one that is highly effective, and one that is effective but very expensive yet works better for diabetics. An employers could tier their plan based on the evidence, and reduce or waive the copay diabetics pay for that drug. It gets us much closer to what we want, [which is] personalized medicine."

Adds Nayer: "Not just personalized medicine, but personalized benefits. What you need is different from what I need from a benefits plan. Money does not drive outcomes. That personalization is important so that what we offer is more meaningful and people will change their behavior."

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