New payment models test ability to identify underserved communities


The Centers for Medicare and Medicaid Services is testing new ways to distribute Medicare funding based on need.

Last year, CMS started using the area deprivation index to adjust payment rates and quality incentives in some models to encourage participating providers to offer care to disadvantaged populations.

The area deprivation index, or ADI, is a compilation of data points the Health Resources and Services Administration created to rank neighborhoods by socioeconomic disadvantage based on factors such as income, education, employment and housing.

CMS has incorporated the tool, which is maintained by the University of Wisconsin-Madison, into ACO Realizing Equity, Access, and Community Health (REACH) and the Medicare Shared Savings Program and is considering adding it to Medicare Advantage Star Ratings.

Using the ADI and other social indicators to calculate reimbursement is an important step toward shifting more resources to structurally marginalized communities, said Oak Street Health Chief Medical Officer for Value-based Care Strategy Dr. Ali Khan. But providers participating in the alternate payment models fear the tool may inadvertently divert resources from some communities that need them.

Stakeholders are now taking a hard look at how the healthcare industry should identify underserved communities in payment arrangements to ensure providers are incentivized to care for high-needs patients. "That examination is happening now in the academic sector, the private sector and the public sector. And that innovation is going to be fostered because CMS took such a bold stance," Khan said.

Holes in the methodology

Regulators are monitoring the implementation of the benchmarking methodology and will make adjustments based on evidence that arises within each model, a CMS spokesperson wrote in an email. "CMS is aware of concerns some providers have shared with the use of the ADI and is examining other variables that might be added to the composite measure used in ACO REACH," the spokesperson wrote.

An analysis by Sacramento, California-based Sutter Health and New York-based Mount Sinai Health System found that factors incorporated into the ADI, such as average home prices, may not accurately capture health disparities in densely populated urban areas, leading to underestimation of social vulnerability in some communities.

The study published in Health Affairs in April also found instances in which the Medicare Shared Savings Program ranked low-income areas in New York City's Bronx borough with lower life expectancies, similar to communities in Manhattan's high-income Upper East Side with higher life expectancies—masking significant inequities.

The discrepancy could result in CMS distributing additional resources to wealthier rural neighborhoods instead of lower-income urban areas, said Maria Alexander, Mount Sinai Health System's vice president for population health operations and co-author of the report.

"We want to make sure that the way they structure that incentive isn't inadvertently discouraging certain provider groups from participating or moving resources to groups that actually don't need those additional resources," Alexander said.

Advocate Health perceives the same problem in the Midwest, said Don Calcagno, the Downers Grove, Illinois-based health system's chief population health officer. Some disadvantaged populations are not accurately reflected in the top ADI areas, leading to inequitable distribution of benefits, he said.

Chicago-based Oak Street Health estimated CMS's proposed use of the ADI in a Medicare Advantage payment model would transfer resources away from beneficiaries who are Black and eligible for both Medicare and Medicaid.

The CVS Health division told federal regulators in March that it would see a $240 reduction in risk-adjusted payments per dual-eligible member per year under the methodology. Black dual-eligible beneficiaries would be acutely affected, with a yearly decline of $480 in risk-adjusted payments.

The extra funding helps Oak Street Health finance providers such as behavioral health clinicians and social workers, Khan said. “The ADI drives a weight away from dense, structurally marginalized neighborhoods and cities, particularly where Black, Latino and low-income Asian patients congregate, and we see that disparity,” he said.

If integrated into the Medicare Advantage Star Ratings program, the reward provision would save Medicare $5.13 billion over 10 years, CMS said.

Evolving methods

In letters to CMS, provider organizations largely expressed support for the regulator's decision to leverage data to target resources to communities considered socially vulnerable but pushed for the methodology to evolve.

CMS pairs data from the ADI with dual-eligibility status to determine whether a patient should be considered underserved in both ACO REACH and the Medicare Shared Savings Program, which helps capture factors the ADI does not take into consideration, the CMS spokesperson wrote. Dual-eligibility status is an imperfect metric because Medicaid programs vary by state, Alexander said.

Moving forward, social risk adjustment should evaluate both community-level barriers and individual patient needs to address health disparities, said Aisha Pittman, senior vice president of government affairs at the National Association of Accountable Care Organizations. The ADI should also include regional adjustments to account for variations in income and cost of living, she said.

To improve accuracy, CMS should complement the ADI with metrics such as life expectancy, Alexander said. CMS could eventually individualize the risk adjustment process by incorporating clinical notes and social assessments but should be careful to avoid alienating safety-net providers with limited data and reporting infrastructure, she said.

CMS should also consider allowing the use of similar tools, such as the Centers for Disease Control and Prevention's social vulnerability index, Khan said. Each tool has limitations, and ongoing discussions are needed to determine the most suitable methods for identifying high-needs patients, he said.

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