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Using Data to Improve Health Equity

Thinking carefully about how data are collected is the first step improving health outcomes.

Social determinants of health are an important cornerstone of public health and should be considered when working on a program meant to improve health outcomes in a community. At the American Public Health Association 2022 Annual Meeting & Expo, held November 6 to 9, 2022, in Boston, Massachusetts, presenters discussed the equitable allocation of the COVID-19 vaccine in the state of Minnesota and what is overlooked by using the term “other” when collecting demographic characteristics.1

During the early days of vaccine rollout when only patients aged 65 years and older were eligible for the primary series of the COVID-19, disparities in vaccine coverage were noted—which were also seen in testing and disease outcomes in Minnesota, according to Dylan Galos, PhD, research scientist for the Minnesota Department of Health. To address the disparities, the department hired a Vaccine Equity Director and prioritized making data on race and ethnicity more available. Two months after the rollout began, 13.8% of eligible non-Hispanic White Minnesotans had received at least 1 vaccine dose. By comparison, only 7.7% of Black, 4.8% Hispanic, and 8.0% Asian/Pacific Islander eligible Minnesotans had received a dose.

As a result of this, 40% of vaccines were allocated to zip codes with a high social vulnerability index (SVI) score. Demographics linked to a high SVI score included limited English proficiency, living with disabilities, and being indigenous, Black, or Hispanic. As a result of the efforts, the vaccine rate came close to parity. Galos’s colleague Mateo Frumholtz, MPH urged the audience to remember, “vulnerability is not just in urban settings, especially when it comes to health care access and utilization.”

When asking about demographic characteristics, the word “other” is often used to describe race or ethnicity, but this term is not all-encompassing, according to Rachel Eckenreiter, a Community Health Program Coordinator for New Bedford Health Department in Massachusetts. In New Bedford, the race breakdown of residents has shifted between the 2010 and 2020 census, with White, non-Hispanic residents decreasing from 67.9% to 56.9% of the population and other, non-Hispanic residents increased from 8.8% to 12.8%; Hispanic of any race increased sharply from 16.7% to 24.3% during that same time. However, many groups of immigrants fall into the “other” group such as Cape Verdean or Portuguese/Azorean and are often considered Hispanic. Either designation is too broad to encompass the group and variations in vocabulary, neighborhood, frequented public places exist across these many groups.

The lack of specificity also impacts understanding the effects of disease. In New Bedford, 6% of all COVID-19 cases were missing any race/ethnicity data and 12% were categorized as “Other, non-Hispanic.” Understanding leading causes of death is also impacted by placing so many groups under the heading of “other”; for example, heart disease is the number 1 cause of death for Cape Verdean and Portuguese/Azorean New Bedfordians, but cancer is first for Hispanic/Caribbean residents.

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Addressing this lack of data can include offering more ethnicity and race options, as well as allowing for multiple options to be selected along with explaining why the data are being collected. Additionally, people looking at the data can consider using other variables like spoken languages and country of birth to analyze data. Eckenreiter encouraged creativity saying that those wanting to in-depth analysis “must find innovative methods to end alternative data sources to do so.”

Reference

1. Galos D, Eckenreiter R, Watson S. Exploring the measurement of social determinants of health and health equity. Presented at: American Public Health Association 2022 Annual Meeting & Expo; November 6-9, 2022; Boston, MA.


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