CMS aims to improve health equity data to reduce disparities

Photo: Marko Geber/Getty Images

The Centers for Medicare and Medicaid Services is looking to improve its data in ways that contribute to a fairer healthcare system, including continuing the development of equity scores and refining the Health Equity Summary Score, as well as addressing bias in various tools and methods.

The CMS Framework for Health Equity outlines this approach, and the agency said it recognizes that “increasing the collection of standardized sociodemographic and social determinants of health (SDOH) data across the healthcare industry is an important first step towards improving population health.”

To strengthen and improve the accuracy of enrollee health equity data, CMS has enhanced the collection of data elements across its programs, including limited collection of SDOH data or Health-Related Social Needs (HRSN) data. 

For example, the Center for Medicare and Medicaid Innovation’s Accountable Health Communities (AHC) Model included a mandatory HRSN screener, which includes items such as housing instability, food insecurity and transportation needs, and CMS has mandated the future collection of new health equity-related data elements in post-acute care (PAC) settings, such as skilled nursing facilities, with information including race, ethnicity, transportation, social isolation, health literacy and preferred language.

WHAT’S THE IMPACT

Although progress has been made, gaps in the availability, completeness and quality of health equity data remain across CMS programs. Historically, some data elements were collected in forms that are not aligned to current standards, such as those established by the U.S. Department of Health and Human Services in 2011. HHS standards include the 2011 HHS data standards and the HHS Office of the National Coordinator for Health Information Technology (ONC) United States Core Data for Interoperability (USCDI).

The USCDI consists of data elements and associated vocabulary standards to support computerized, interoperable use of equity data. It includes standards for race, ethnicity, preferred language, sex and disability status aligned with the 2011 HHS data standards that can be used in conjunction with the 2011 HHS data standards and guidance.

Where it’s appropriate, CMS said it will align with the USCDI standards. The collection of data elements not aligned to HHS data standards can result in inconsistent analyses when using and combining health equity data from multiple sources, the agency said. And the lack of consistent data collection at a disaggregated level, broken down into detailed sub-categories, presents barriers to understanding the needs of specific subgroups, as well as to comparing data across programs and populations as needed.

Efforts to address these health equity-related data issues are already underway and will be prioritized as CMS pursues its future vision for health equity data. 

These efforts include collecting new health equity data elements across CMS programs to fill existing gaps; aligning health equity data to acceptable standards across all elements; considering health equity measures and health equity scores (such as the Health Equity Summary Score); equipping the industry with new tools and capabilities aligned to health equity goals; and providing access to disaggregated data insights that the public can use to drive action.

THE LARGER TREND

CMS outlined a multi-pronged action plan geared toward promoting health equity in April. A number of actions are laid out in the strategy, and are meant to better identify and respond to inequities in outcomes, barriers to coverage and access.

CMS is aiming to close gaps in access, quality and outcomes for underserved populations, and to promote culturally and linguistically appropriate services that are responsive to a person’s preferred languages, as well as their level of health literacy.

The agency said it wants to build on outreach efforts to enroll eligible people across Medicare, Medicaid/CHIP and the federal marketplace. CMS also said it would expand and standardize the collection and use of data, including on race, ethnicity, preferred language, sexual orientation, gender identity, disability, income, geography and other factors across CMS programs.

CMS Administrator Chiquita Brooks-LaSure told a crowd at the HIMSS22 annual conference in Orlando in March that interoperability is key to addressing health inequities. Data exchange is needed to understand gaps in the system, she said.

Technology can help in implementing six pillars, she said, which are: addressing health disparities, building on the Affordable Care Act, engaging partners and communities served, driving innovation to tackle health system challenges and promote value-based care, protecting program sustainability, and fostering a positive workplace and workforce.
 

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