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Linking new COVID-19 race, ethnicity data to APCDs will provide more complete picture of virus’ toll

Principal Consultant, Freedman HealthCare, LLC

Mary Jo Condon, MPPA, sees information and collaboration as the foundation for improving our nation’s healthcare system. While at Freedman HealthCare, Ms. Condon has led consulting engagements on complex, data driven health care policy projects requiring extensive stakeholder engagement, communications strategies, analytic methodologies and clear, concise presentation of cost and quality outputs.

The Department of Health and Human Services said Thursday that beginning on August 1 it will require laboratories to report race, ethnicity and other information about each person tested for the novel coronavirus. The goal is to better understand differences in how the virus impacts populations, particularly communities of color. The new requirements include 18 pieces of information in all.

While some counties and states are already reporting race and ethnicity data for confirmed COVID-19 cases, hospitalizations, and/or deaths, few if any are reporting race and ethnicity of those tested. Moreover, for the states that do report race and ethnicity data for confirmed cases, hospitalizations, and/or deaths, the data is not standardized.

While additional, standardized,  data on race and ethnicity will help inform states’ emergency responses, it would be more meaningful if this data (including the newly mandated data on race and ethnicity) was linked to more complete information on healthcare utilization, such as whether patients sought care in an emergency room, were hospitalized, or required the assistance of a ventilator. All payer claims databases (APCDs) are typically best positioned to support public health authorities with these types of analytics.

States with APCDs should move quickly to develop interagency data sharing agreements that can support linking testing data, including the new required data elements, with their APCD data. Further, states may want to fund this work by applying for new federal dollars dedicated to support analytics related to COVID-19 response.

Combining information sources can occur at multiple levels. Ideally, from an analytics perspective, this linking would occur at the patient level using a combination of shared identifiers, such as a patient’s name, date of birth and address. Linking at the patient level allows researchers to analyze detailed care trends among specific populations. For example, in this case, it would allow researchers to measure the rates at which individuals were tested by race, the percent positive by race, the percent of those individuals who needed more care and how that varied by race, and the health histories of positive patients with the aim of better understanding the dual impact of pre-existing conditions and race on COVID-19 severity.

Of course, combining data at the patient level also brings heightened privacy concerns. While these privacy concerns can be addressed by state agencies working together to develop appropriate data use agreements, state policies do not always allow this level of identifiable data sharing and linking. In those cases, states may choose to look at these data sources side-by-side. This type of analysis could highlight areas where rates of testing and/or positive cases were comparatively lower, yet COVID-19 related utilization was higher. This would suggest individuals in these areas were more likely to have more severe cases of the condition.

For more information on developing interagency data sharing agreements or tapping into federal dollars to support COVID-19 impact analysis, contact Mary Jo Condon at [email protected].

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