ONC Defines EHR Certification For SDOH Data To Pursue Health Equity

ONC announced its health IT demographic EHR certification requirements to standardize race and ethnicity data collection in the pursuit of health equity.

ONC outlined that the agency’s “demographics” certification criterion requires health IT to record race and ethnicity at the same level of detail as the CDC’s Race & Ethnicity code technology. This system encompasses over 900 concepts for race and ethnicity, giving patients precise options for self-identifying their demographic information.

“Race and ethnicity data are important for many uses, such as informing effective treatment and patient care, improving healthcare outcomes, research, and, identifying and eliminating health disparities to improve health equity,” said ONC. “Race and ethnicity data are also critical to informing national priorities, including efforts to advance racial equity and to support underserved communities.”

The CDC’s 900 race and ethnicity concepts are organized to “roll up” to meet the Office of Management and Budget’s (OMB) minimum categories for race and ethnicity. This allows for data aggregation when the OMB standard is necessary, ONC explained.

Similarly, health IT certified to ONC’s “demographics” criterion must be able to “perform the roll up from races and ethnicities to the OMB categories,” ONC wrote.

The technology must also be capable of coding multiple races and ethnicities for a patient in the EHR. This allows individuals to report their race and ethnicity in a manner that most closely aligns to how they self-identify, ONC noted (i.e. Japanese-Indian as opposed to Asian American).

ONC called for healthcare providers to work with their health IT developer to implement a strategy for recording race and ethnicity that best supports the populations they serve.

“Certification criteria do not specify how many of these CDC Race and Ethnicity Code Sets must be displayed,” ONC explained. “This is left to the developers in concert with the end users in specific care settings to determine how the user interface is designed.”

Additionally, an ONC-certified health IT module must be able to record whether a patient chose not to provide information for race and/or ethnicity.

ONC acknowledged that while data can be helpful in the pursuit of health equity, it understands that datasets can perpetuate inequity as well.

“ONC recognizes the potential for data-driven technologies, including certified health IT, to impact health equity,” the agency wrote. “Further, ONC recognizes that ‘structural inequalities, biases, and racism in society are easily encoded in datasets,’ and that data science practices using race and ethnicity data ‘can reinforce existing social injustices, and health inequalities.’”

ONC also noted that the Agency for Healthcare Research and Quality issued a request for information entitled: The Use of Clinical Algorithms That Have the Potential To Introduce Racial/Ethnic Bias Into Healthcare Delivery.

“We anticipate public comments will help inform future health IT work in this area,” ONC wrote.

The collection of race and ethnicity data is critical in identifying health disparities. Data-driven public health initiatives can help mitigate these disparities as the industry strives for health equity.