“If social risk factors are taken into account by Medicare, it should be done in all aspects of the payment and quality assessment and reporting system,” according to co-authors Melinda Buntin, Ph.D., professor and chair of Health Policy in the Vanderbilt University School of Medicine, and John Ayanian, M.D., M.P.P., director of the University of Michigan Institute for Healthcare Policy and Innovation. “It should also be done in a way that rewards high-quality, high-value care for these patients but does not ‘excuse’ suboptimal care.”
Their piece highlights a recent National Academies of Sciences, Engineering, and Medicine report that they helped author. This report reviewed a wide range of studies about social risk factors and health, and considered whether they were ready to be used by Medicare in its payments and quality reporting. It appears alongside another NEJM piece by a federal government team that came to similar conclusions after reviewing the issue.
“As our nation works to make health care more patient-centered and value-based, Medicare can support these goals by making sure we reward those who do a good job taking care of disadvantaged patients,” Ayanian said.
The authors noted that Medicare could use social risk factor data it already tracks – such as information on low-income patients who are “dually eligible” for both Medicare and Medicaid - to adjust Medicare payments and quality measurements. Dual-eligible status is the most consistent of all social risk factors in predicting which patients will have the worst outcomes.
The National Academies’ report also recommends that Medicare ask new and existing enrollees for racial and ethnic background, education, marital status and preferred language - all factors that research has shown to affect health outcomes.
“These findings are important because they lay out how to account for social risk factors and strengthen incentives to deliver high-quality care to disadvantaged groups,” Buntin said. “Previously, some argued you could only do one or the other.”
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