Using data to improve health equity

Careful consideration of how data is collected is the first step to improving health outcomes.

The social determinants of health are an important cornerstone of public health and must be considered when developing a program designed to improve health outcomes in a community. At the 2022 American Public Health Association Annual Meeting and Exposition, held November 6-9, 2022 in Boston, Massachusetts, presenters discussed the equitable distribution of the COVID-19 vaccine in the state of Minnesota and what is being overlooked in the use of the term “other” when collecting demographic characteristics.1

During the early days of vaccine rollout, when only patients age 65 and older were eligible for the primary series of COVID-19, inconsistencies in vaccine coverage were noted—which was also seen in testing and disease outcomes in Minnesota, according to Dylan Gallows, PhD, a researcher at 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 accessible. Two months after the start of vaccine rollout, 13.8% of eligible non-Hispanic white Minnesotans had received at least 1 dose of vaccine. In comparison, only 7.7% of black, 4.8% Hispanic, and 8.0% eligible Asian/Pacific Islander Minnesotans received a dose.

As a result, 40% of vaccines were allocated to postcodes with a high Social Vulnerability Index (SVI). Demographics associated with a high SVI score include limited English proficiency, living with a disability, and being indigenous, black, or Hispanic. As a result of the effort, vaccine rates have approached parity. Gallos’ colleague, Matteo Frumholz, MPH, urged the audience to remember that “vulnerability is not just in urban settings, especially when it comes to accessing and using health care.”

When asked about demographic characteristics, the word “other” is often used to describe race or ethnicity, but that term is not all-inclusive, according to Rachel Eckenreiter, community health program coordinator for the New Bedford, Massachusetts, health department. In New Bedford, the racial breakdown of residents changed between the 2010 and 2020 censuses, with non-Hispanic white residents decreasing from 67.9% to 56.9% of the population, and remaining residents who non-Hispanic increased from 8.8% to 12.8%; Hispanics of any race increased sharply from 16.7% to 24.3% during the same time. However, many immigrant groups fall into the “other” group, such as Cape Verdean or Portuguese/Azorean, and are often considered Spanish. Both designations are too broad to encompass the group, and within these many groups there are variations in vocabulary, neighborhood, public places frequented.

The lack of specificity also affects the understanding of the effects of the disease. In New Bedford, 6% of all COVID-19 cases were missing data on race/ethnicity, and 12% were categorized as “Other, non-Hispanic.” Understanding the leading causes of death is also affected by placing so many groups under the heading of ‘other’; for example, heart disease is the #1 cause of death for Cape Verdeans and Portuguese/Azoreans in New Bedford, but cancer is number one for Hispanics/Caribbeans.

Addressing this lack of data could include offering more options for ethnicity and race, as well as the ability to select multiple options along with an explanation of why the data is being collected. Additionally, data viewers may consider using other variables, such as languages ​​spoken and country of birth, to analyze the data. Eckenreiter encouraged creativity, saying that those who want to do deep analysis “have to find innovative methods to cut through alternative data sources to do that.”

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 Annual Meeting and Exposition 2022; November 6-9, 2022; Boston, Massachusetts.

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