ML helps health plans tackle SDOH, improve outcomes

With the passage of the Chronic Care Act, Medicare Advantage plans have been scrambling to figure out how to offer supplemental benefits to their members.

Passed as part of a Bipartisan Budget Act last year, the Chronic Care Act promotes the use of benefits that maintain health or keep a beneficiary’s health from deteriorating, and the benefits don’t have to be health-related. Instead, they can include help for social determinants of health that include housing, nutrition and transportation.

Michael Cantor, MD, chief medical officer at CareCentrix, a company that works with payers and providers to create programs that improve quality of care while lowering costs, says social determinants are “significant barriers” to achieving good health for some beneficiaries and the Chronic Care Act is opening doors to improve outcomes. Under the act, the supplements can also be tailored to the individual, when it comes to qualifications. The same benefits don’t have to be offered to every beneficiary, he says.

The Chronic Care Act allows for these supplements in MA plans, but without reimbursement, so the risk is on the plans, leaving some hesitant to try making these additions. “MA plans will need to believe that there is a return on investment for benefits targeting social determinants of health,” Cantor says.

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Also See: How 4 organizations are leveraging IT to address SDOH

The Centers for Medicare and Medicaid Services is allowing the supplemental services in 2020, with some aspects being launched this year. Big health plans that have already had programs in place to offer remedies to social determinants of poor health are in a better place to implement the new supplemental insurance benefits next year, Cantor says.

A recent CareCentrix analysis found that national and regional MA plans that offered supplemental benefits saw increased enrollment in the markets where they offered the new benefit designs.

“Whoever gets it right is going to differentiate themselves in an increasingly competitive market,” Cantor says of health plans that decide to jump in and pursue the supplemental benefits.

However, getting data on how to accomplish this is operationally challenging, Cantor says. Currently, the best method being used is a standardized questionnaire that asks beneficiaries questions related to needs such as transportation, care that’s available at home and nutritional risk. Some organizations are kicking it up a notch by using analytics and machine learning.

“The future of this will depend on how well the big plans do,” he says. “If they do well with this, others will follow. At the very least, it’s going to take a few years to get it right.”

Wolf Shlagman, CEO and founder of Care Angel, a company that provides a virtual nurse assistant that strategizes and coordinates care for the most expensive, highest risk and rising-risk populations, is making use of Angel’s automated and AI-assisted calls to scale healthcare, averaging 20 times less expensive than traditional methods for case management, he says. This expanded capability is enabling health plans to reach out to not just the sickest patients, but to the rising risk patients, as well.

“What’s interesting, today, is no one really touches below [the] high risk [group],” Shlagman says, yet statistics show that 20 percent of these will move up.

With the current risk model, insurance companies are being forced to become population health management companies, Shlagman says. With billing information, insurance companies currently have the most data on patients in one place, giving them an advantage on population health. When AI is added to that storehouse of information, a lot can be done toward improving outcomes and preventing patients from getting sicker.

Cathryn Donaldson, director of communications at America’s Health Insurance Plans says health plans are using socioeconomic data to tailor programs for various communities, with three key goals in mind—to improve health outcomes, lower consumer costs and increase consumer satisfaction.

“Health insurance providers and other healthcare stakeholders recognize the value in leveraging AI to more thoroughly analyze socioeconomic data and better serve their members,” Donaldson says. In addition, “data gathered by insurance providers can be used to inform public health strategies by predicting potential outcomes based on risk factors.”

According to Donaldson, predictive analytics can be used as a tool to appropriately allocate resources. “[H]ealth insurance providers can also use this form of advanced data analytics to identify and address disparities and to ensure that members have access to effective, affordable care when needed,” she says.

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