Health Equity: A Data Priority
Updated February 6, 2023
Advancing health equity is a CDC priority and should be a collective data priority. Data gaps in routine and public health emergencies surveillance limit visibility into the public health needs of disproportionately affected populations, such as people experiencing homelessness, people who use drugs or have substance use disorder, and people with disabilities. When the data of diseases and conditions for different groups are incomplete or unknown, public health agencies and partners are unable to understand and address health inequities. The Center for Surveillance, Epidemiology, and Laboratory Services’ Public Health Informatics Office (PHIO) is working with partners to collect more complete data, establish data standards, and improve data exchange to better achieve health equity among various disproportionately affected populations and strengthen data-driven actions.
Expanding Data Sources
Two major challenges to addressing the public health needs of disproportionately affected populations are lack of data and lack of awareness of these populations and their needs. These challenges are closely linked; lack of awareness hinders inclusion of necessary variables in all data systems and the availability of information to strategically address challenges. As a result, quantifying the distribution and impact of inequities is a challenge. Incomplete data and low awareness compound inequities and may lead to worsening health disparities. Together with subject matter experts from across CDC, PHIO is taking on this important health equity issue through research on gaps and best practices for standardizing, exchanging, and visualizing data.
Improving surveillance data for disproportionately affected populations
PHIO identified gaps and best practices for traditional case reporting for COVID-19 for people with disabilities, people who are experiencing homelessness, and people who use drugs or have substance use disorder. This work gathered the perspectives of jurisdictions and end users on key facilitators to improve data collection. This activity was coordinated with subject matter experts from the National Center on Birth Defects and Developmental Disabilities; National Center for Injury Prevention and Control; National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention; and the Deputy Director for Infectious Diseases Special Populations team.
- Key Facilitators: Jurisdictions and end users of surveillance, including healthcare personnel, expressed the need for clear definitions of populations of focus. Communication that these data are an agency priority was identified as a strategy to increase buy-in. In addition, it was noted that increased clarity on the goals behind data collection was needed, including concrete downstream benefits to each population of focus.
- Applicability: While this study was conceptualized by gaps noted during the COVID-19 pandemic, the focus has remained broad. Findings and tools developed for jurisdictions will be applicable across public health concerns.
- Training: An interactive gamified training was developed to encourage data collection techniques for discussing sensitive topics in a way that is accessible and appropriate for those who may have experienced trauma. This training is designed to be applicable across a variety of health conditions and concerns specific to all three disproportionately affected populations of focus. The training will be launched in 10 jurisdictions in collaboration with the Council of State and Territorial Epidemiologists (CSTE) in spring 2022.
While improving case investigations and more traditional data surveillance systems is key, electronic data sources will increasingly be leveraged in public health efforts. Investigators are collaborating with data standards and health equity groups across the agency to improve future data on these populations of focus via emerging methodologies (i.e., Electronic Case Reporting, Electronic Lab Reporting).
Partnering with Community-based Organizations Serving People Experiencing Homelessness
PHIO partnered with CDC’s Office of the Deputy Director for Infectious Diseases Special Populations team to explore strategies to increase data exchange between public health and community-based organizations (CBOs) working with people experiencing homelessness.
- Information Gathering: PHIO received input from CBOs providing services to people experiencing homelessness on best practices for high-quality data collection and data sharing with local public health. Information was collected through focus group, in-depth interviews, and electronic surveys.
- Next Steps: Findings will be reviewed from April to June 2022 by a Technical Expert Panel. The panel will include public health jurisdictions, CBOs focusing on people experiencing homelessness, CBO service providers, and other federal agencies. The panel will identify potential best practices that could be piloted and adapted for use by service providers. Key findings will be published. Expansion of similar work for other disproportionately affected groups is being explored.
Call to Action
To support ongoing health surveillance and future responses, there is a need to evaluate our systems to create and maintain data streams with robust information on disproportionately affected populations. CDC programs should inventory their surveillance and data systems to see whether data on disproportionately affected populations are included and adequately captured. Heath equity, including disproportionately affected populations, should be considered in the design of new data systems. New data standards for disproportionately affected populations are needed to facilitate the process. These actions will support the long-term goal of achieving health equity.
Data collection is not just about what questions are asked, but also understanding why they are asked and how they can be asked in a trauma-informed manner. The service providers who work with disproportionately affected populations, including people with lived experience, know the needs of populations best and are trusted within communities. Partnering with these organizations and individuals to improve data collection and exchange is an important component of improving data quality and exchange.