“For public health, it is about detecting need. And aggregation hides needs.”
Ninez A. Ponce, PhD, MPP, director of the UCLA Center for Health Policy Research, shared that remark about the importance of data disaggregation during a discussion about the new federal race and ethnicity data collection standards that was convened by the Robert Wood Johnson Foundation (RWJF).
The new policy, which is called the Statistical Policy Directive No. 15, was announced on March 28, 2024, and its biggest change eliminates separate questions for selecting “race” and “ethnicity.” Instead, this will be one question that allows a person to choose the myriad ways they identify. The category of “Middle Eastern or North African” has also been added.
Federal agencies will be required to collect more than the “minimum required race and ethnicity categories for most situations, to ensure further disaggregation in the collection, tabulation, and presentation of data when useful and appropriate,” the White House Office of Management and Budget (OMB) said in its announcement of the first significant update since 1997.
“As a data producer I think I have a pragmatic view of how to make this happen,” said Ponce, who also serves as the principal investigator of the California Health Interview Survey (CHIS), during the discussion. “But, as a data advocate, I also have the aspirational view of what it should look like.”
Tina Kauh, PhD, senior program officer at RWJF, moderated the discussion, which also included Maya Berry, executive director of the Arab American Institute, and Meeta Anand, senior director for census and data equity at the Leadership Conference on Civil and Human Rights.
Below we highlight a few key ideas that Ponce shared about why the changes are important and how to encourage private companies working in health care or health care-related fields to follow these new standards, which aren’t mandatory for them. Answers have been lightly edited for clarity and brevity.
Tina Kauh: How do you think the updated minimum race and ethnicity standards will benefit data that we have about individuals in our nation, including census data, health and public health data, and beyond?
Ninez Ponce: I think the key change is minimizing the “other race” category in public health. The census data are our denominator data. When we come up with estimates on serious psychological distress, on exposure to hate crimes, not having access to healthy food, hospitalization readmissions, or other indicators of health care access and the wider social safety net, we do not have those data and, we cannot compute a rate on a specific population without the denominator.
For public health, it is about detecting need, and aggregation hides needs. You know this, Tina — we have been working on this together for almost a decade. This “model minority” of the Asian American aggregate category hides the identities under that broad category. For example, Koreans in California had one of the highest uninsured rates, but it was not seen.
Mental health needs vary across different groups. The aggregation of Asian people with Native Hawaiian and Pacific Islander people totally masks the needs of the Native Hawaiian and Pacific Islander population. Their demographics, educational attainment, opportunities to access good health care and promote well-being, are very different.
Later the panelists discussed how to get the private sector to work with these new guidelines.
Tina Kauh: Are there any opportunities to work with the private sector on this issue? Do you have thoughts on how the health care industry, for instance, could either support or help advance some of this work?
Ninez Ponce: The private sector health care industry, of course, is motivated by delivering excellent care, but also profits, right? If the accrediting bodies are saying you cannot be accredited unless you comply at the minimum with OMB’s Statistical Policy Directive 15, then that is one way to incentivize change. In the conversations I have had among health care finance and policy folks, there is more and more concern about equity because there are bonuses with equity dollars built in. The private sector responds to maximizing revenue. Payers like the Centers for Medicare and Medicaid Services also now have more of an equity agenda.
When I talk about health care delivery systems, it is hospitals, electronic health record vendors, health insurance companies, federally qualified health centers, and nursing homes. With COVID, the nursing home race and ethnicity data was terrible. So again, how do you get the private sector to adhere to more race data collection fidelity with the SPD 15? Again, I think the way to do it is through incentives.
They are losing dollars on the table. You cannot have high-quality delivery of care or effective health systems if you do not have the data equity piece.
