NHSN and Social Determinants of Health
Division of Healthcare Quality and Promotion
Mission
To protect patients, healthcare personnel and to promote safety, quality, and value in both national and international healthcare delivery systems.
Surveillance Branch
Vision
To protect lives by leading the nation’s trusted surveillance system for healthcare.
Mission
- To use rigorous science for real-time data and surveillance to protect patients, protect healthcare personnel and to promote safety, quality, and value in healthcare.
- To lead the nation’s efforts to identify and respond to emerging and persisting threats across healthcare with best-in-class data automation and user interfaces.
NHSN Focus on Race, Ethnicity, Language, and Interpreter Use Data to Address Health Disparities
Underlying racial and ethnic inequities and system barriers for other language speakers significantly affect health outcomes. However, few studies have systematically addressed these factors and their impact on hospital and long-term care facility (LTCF) acquired infections. Similarly, few studies have addressed these factors and their impact on COVID-19, influenza, and respiratory syncytial virus (RSV) vaccination uptake by healthcare workers and LTCF residents.
Race, ethnicity, language, and interpreter (REaLI) data fields already exist in most electronic medical record systems. There are rapidly evolving requirements on the horizon to collect these essential data elements. By looking at traditional race and ethnicity categories, and diving deeper into population sub-groups who speak languages other than English, more specific and actionable differences in infection risk and vaccine uptake may be identified.
In order to better understand the impacts and interactions of REaLI data on hospital and LTCF associated infections, as well as COVID-19, influenza, and RSV vaccination uptake by healthcare workers and LTCF residents, we are taking steps to require the submission of REaLI data in a systematic and standardized way in NHSN, with guidelines to support this effort.
We intend to analyze the data to identify disparities in infection burden and vaccine uptake, which can be used to inform action for hospital, LTCF, state, and local public health systems. The goal is to mitigate infection risks and vaccine uptake barriers associated with REaLI data identifiers. Recommendations may include specific sub-population outreach, including other language speakers within communities, collaboration with ethnic community-based organizations to better understand how culture, language, and structural barriers impact these risks, and specific actions to directly address health systems barriers.
