CMS Focus on Health Equity

Equity is a pillar of CMS's Strategic Vision with the goal to incorporate health equity and address health disparities across all programs and in the community. "CMS is working to advance health equity by designing, implementing, and operationalizing policies and programs that support health for all." CMS believes achieving health equity via improving data collection to better measure and analyze disparities across programs and policies will positively impact quality. CMS recently recommitted to ensuring equity in CMS programs with the publication of the CMS Framework for Health Equity 2022-2032.

Executive Order No. 13995, 2021, Ensuring an Equitable Pandemic Response and Recovery, provided for the creation of the Biden-Harris COVID-19 Health Equity Task Force. The Task Force’s goal is to mitigate the health inequities caused or exacerbated by the COVID-19 pandemic but also to prevent such inequities in the future. Executive Orders 13985 and 14091 address advancing racial equity and other underserved communities. Executive Order  13985 also defined equity. The CMS Framework for Health Equity aligns with these Executive Orders and other Department of Health and Human Services equity programs.

CMS defines health equity as the attainment of the highest level of health for all people, where everyone has a fair and just opportunity to attain their optimal health regardless of race, ethnicity, sexual orientation, gender identity, socioeconomic status, geography, preferred language, or other factor that affect access to care and health outcomes. 

Health Equity Terminology and Data Standardization

Measure developers need to use clear terminology when describing what and how their measures are addressing equity, social drivers/determinants of health (SDOH), and social risk factors. They also need to use data standards as much as possible.

The data critical for measuring health equity, SDOH, and social risk factors requires numerous categories of information. Measured entities have not traditionally collected many of these categories (e.g., sexual orientation and housing status), and others have not been collected consistently (e.g., race and ethnicity). Standardization of health data, equity data included, is essential for interoperability, which is a CMS priority. Learn more about this priority in the CMS Office of Minority Health’s white paper, The Path Forward: Improving Data to Advance Health Equity Solutions

Examples of data standardization work include

  • the Gravity Project, a Health Level Seven International® (HL7®) Fast Healthcare Interoperability Resources® accelerator project, which brings together interested parties across the U.S. to develop and test consensus-based standards to facilitate SDOH data capture and exchange across systems, care settings, and social services.
  • HL7's Gender Harmony Project (GHP) developed a gender-inclusive logical model. To classify individuals, the Model identifies sex as male, female, or specified and can be based on anatomy, other biological characteristics, or physical and physiological features. 

Z Codes

CMS and others, e.g., Blue Cross Blue Shield of Illinois recommend collecting SDOH issues and coding them in the patient's record with International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Z codes. This aligns with USCDI v2 data element SDOH Problems/Health Concerns.

While Z Codes have been available for some time, measured entities have not been using them regularly or consistently, as insurers do not require their use. To address the gaps in standardized collection of Z codes, CMS developed an infographic for health care administrators and other team members to understand the best practices and importance of both gathering and tracking SDOH data.

Equity-Related Screening Tools 

There are several screening tools available to assist with collecting SDOH and/or social risk factor information. For example,*

As more screening tools and standards become available for collecting SDOH/social risk factor data, the feasibility of including those data in quality measures increases. Measure developers should look for sources of SDOH information and include within quality measure specifications to assist with measuring equity.

*This a non-exhaustive list and is not an endorsement of specific tools.

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