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Transforming health equity analysis

Expanding race and ethnicity data collection in Maven®

Health equity remains a significant challenge for epidemiologists and public health officials, primarily due to deficiencies in data collection and reporting. Accurate, comprehensive data is crucial for understanding the diverse health needs of different communities. Existing methods of data analysis, however, often fail to capture the full spectrum of race and ethnicity, resulting in substantial challenges for public health agencies, epidemiologists and practitioners. 

These data deficiencies may impede our ability to accurately identify health disparities and develop targeted interventions. Without detailed and disaggregated data, resources cannot be allocated efficiently, and policies cannot be effectively shaped. 

The Importance of data disaggregation

For public health organizations, disaggregated data holds transformative potential in advancing health equity. It is a catalyst for systemic reform, amplifying the voices of historically marginalized groups.

The miscategorization of data has profound impacts. During the height of the COVID-19 pandemic, for example, public health efforts were impeded by race and ethnicity data that was less than 30 percent complete (pdf), according to the Council of State and Territorial Epidemiologists.

In response to these deficiencies, our teams at Conduent sought to effect change in our systems and platforms. 

Advancing health equity

Last year, experts at Conduent completed the meticulous, multi-year process of updating how data is collected and parsed to better aid communities and industry experts, many of whom rely heavily on Maven®, our disease surveillance and outbreak management solution that tracks, manages and reports on the health status of individuals and communities.

The project was complicated and required us to balance three important criteria — the need to keep existing reporting requirements, the preservation of historical data and the ability to capture race and ethnicity. 

The impact of social determinants of health, including factors such as income, education and zip code, which influence health outcomes, was also necessary to consider. Disparities in health outcomes across various racial and ethnic demographics, such as rates of chronic diseases, life expectancy and infant mortality further emphasize the need for improved data collection.

In the pursuit of health equity, we examined where resources are allocated for advocacy initiatives and targeted interventions. We also discussed how the role of monitoring and accountability mechanisms are used to assess the efficacy of health policies, programs and interventions, needing ongoing refinement and adjustment. 

We focused on aligning with pertinent federal initiatives, such as Healthy People 2030 and the Office of Management and Budget (OMB), aimed at bridging the current landscape with a more equitable future. 

Key considerations for improving race and ethnicity data in public health

To enhance health equity, Conduent experts used eight strategic points to improve data used by agencies and scientists:

  • Data disaggregation for systemic reform and amplifying marginalized voices
  • Historical context to address racism and bias in healthcare, highlighted by COVID-19
  • Social determinants income, education, and zip code factors
  • Health disparities to highlight chronic diseases, life expectancy, and infant mortality
  • Resource allocation to support advocacy and targeted interventions
  • Monitoring and accountability to assess and refine health policies and programs
  • Safeguarding information to ensure protection of sensitive health data
  • Federal alignment to conform to Healthy People 2030 and OMB directives

We examined OMB Statistical Policy Directive No. 15, which outlines the Standards for Maintaining, Collecting, and Presenting Federal Data on Race and Ethnicity. These categories for Race and Ethnicity have remained unchanged since 1997, when the OMB last revised its standards for the classification of federal data in this domain. Our working group prioritized three key proposals:

  1. Consolidate the collection of race and ethnicity into a single combined question. This was motivated by findings from the 2020 Census, which revealed that 43.5 percent of individuals who identified as Hispanic or Latino either did not specify a race or were classified as 'Some Other Race' (SOR) alone, comprising over 23 million people.
  2. Introduce a new category for Middle Eastern or North African (MENA) race, considering its status as the 6th-largest population group in the United States.
  3. Mandate the detailed collection of race and ethnicity data for the purpose of disaggregation.

Conduent's Maven System

As a result of these efforts, state and local health departments that use Maven can now better capture data that is vital for understanding populations and targeting interventions that promote health equity. By adding key data elements, we’ve empowered public health officials to better address health disparities and improve outcomes for diverse populations.

Updating Maven’s race and ethnicity data was a crucial step in addressing the disparities health equity among diverse communities, and is pivotal to our mission to enact lasting change and create a healthcare system that truly serves everyone.

Ready to discover why Maven is a trusted health platform by public health agencies around the world? Visit us online to learn more and reach out to an expert.  

About the Author

Alycia McNutt is an epidemiologist with Conduent’s Public Health Solutions. She channels her passion for data and analytics to provide enhancements to Conduent’s Maven Disease Surveillance and Outbreak Management System. With a background in bacterial genomics and several publications including outbreak detection using WGS in multi-state outbreaks, Alycia sheds light on the intricate web of microbial life and its impact on human health.

Profile Photo of Alycia McNutt