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Over the past 40 years, numerous national organizations have called for health data disaggregation — breaking down data into smaller, more precise demographic categories — to be able to understand differences in population outcomes and optimize care. There have been disaggregated data initiatives in Asian and Pacific-Islander communities and for sexual gender minority individuals, among others. Likewise, the need to consistently collect granular health data at the point of care remains a pressing priority for Latino populations.
The federal Office of Budget and Management has proposed updating its race and ethnicity statistical guidelines, but if the categories are still too broad to detect meaningful differences in health outcomes, these standards may not adequately serve racial and ethnic minority populations. State government bodies and health authorities, and specifically state Medicaid programs, may be able to play a strategic role in helping health care systems understand which disaggregated data is most important to collect in Latino communities, as well as how this data should be collected.
While we use “Latino” or “Latina” to describe populations and individuals with Latin American ancestry, there are similar terms used to describe the same population: Hispanic, Latinx, and others. However, most individuals in this demographic prefer to be referred to by their specific country of ancestry, underscoring the need for better collection of disaggregated data.
Common categories of disaggregation in Latino patients include nativity (place/county of birth), generation (immigrant, first or second generation), ancestry or ethnic subgroup (e.g., Mexican ancestry regardless of place of birth), language (Spanish, English, other), or immigration status (undocumented, citizen, legal resident, other immigrant status). While the latter two areas may be relevant to health, for millions of community health center patients, language data are already collected, and immigration status has legal ramifications necessitating consideration outside the scope of this writing. Therefore, we recommend states focus on nativity and ancestry, as these have been associated with variations in health care utilization and health outcomes.
There is a nascent body of health services literature that suggests that nativity or ancestry may be associated with health services utilization and health outcomes. Nativity has been associated with the prevalence of cardiovascular risk factors and markers of high-quality asthma care in children’s electronic health records, and that clinical variation is sometimes not observed without that level of data disaggregation. Other studies have long demonstrated that the prevalence of asthma differs in children of Puerto Rican ancestry as compared to children of Mexican ancestry.
States may have advantages over the federal government in understanding and implementing data disaggregation and demographic data collection, especially on a regional or local scale. First, state governments and officials have relationships with communities, systems, and advocacy organizations that can improve the chances of successfully collecting disaggregated data. Secondly, state Medicaid agencies can leverage 1115 demonstration projects, or initiatives designed to improve the care of Medicaid populations, to incentivize the collection of disaggregated data. California legislators even tried to pass (without success so far) legislation requiring disaggregated data collection in Latinos.
Partnerships with community health centers (CHCs) would greatly benefit these state efforts. For years, evidence has shown that Latino communities view CHCs as safe places to disclose personal information. In addition, CHCs routinely utilize promotores, or community health workers trained in Latino communities who are associated with high levels of patient satisfaction and can assist with the collection of data.
We recommend that state health authorities and state Medicaid agencies initiate data disaggregation demonstration projects that financially incentivize clinics to collect ancestry and nativity information to understand how it intersects with health care utilization and outcomes. We suggest that these projects use existing medical record systems and workflows and prioritize the following:
The ability to gather more specific, disaggregated demographic along with health care data uniformly across multiple heterogeneous Latino communities in multiple settings is necessary to fully understand how these factors impact health. While the collection of this data requires time, effort, and trust, it is needed to ensure we can target prevention and care appropriately.