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How Health IT Design, Data Standards Can Help Boost Health Equity

Ensuring health IT developers design systems with a particular focus on health equity is critical, ONC officials noted.

While health IT cannot address all of the factors that drive health disparities, ensuring technology is designed with health equity in mind is crucial, ONC officials noted in a HealthITBuzz blog post.

More importantly, stakeholders must ensure that health IT does not worsen health disparities. With this in mind, ONC is focusing on the concept of “health equity by design” for its health IT endeavors.

“This means that policies, projects, and technologies, among many other efforts, are looked at early on through the lens of equitable healthcare access, treatment, and outcomes,” ONC officials Ryan Argentieri, Thomas A. Mason, Jordan Hefcart, and Jawanna Henry wrote.

Ensuring health IT supports health equity includes certifying that the technology can collect comprehensive demographic and social determinants of health (SDOH) data.

As part of ONC’s 2015 Edition Final Rule and its 2015 Edition certification criteria, health IT developers seeking certification to the “patient demographics” criterion must demonstrate that the platform can record sexual orientation and gender identity (SOGI) data, the officials noted.

Since ONC did not include these SOGI data in the Common Clinical Data Set in 2015, health IT developers were not required to demonstrate the capability to record such data.

However, the release of the United States Core Data for Interoperability (USCDI) v2 in July 2021 made these two data elements and four additional SDOH data elements a requirement for certified health IT systems.

The four additional elements enable the identification of specific needs related to food, housing, and transportation insecurity to help coordinate care and assistance for at-risk patients.

ONC is working alongside industry stakeholders, federal partners, and the HL7 community to rapidly mature standards for these data elements and incorporate them into workflows.

The officials also noted that as the digital health transformation progresses, it is critical that clinical decision support algorithms do not perpetuate disparities.

“EHRs are increasingly being used as the data sources for building and training algorithms, the development platforms for creating algorithms, and the user applications for incorporating algorithms in clinical decision-making,” the officials wrote.

“All algorithms have bias, and as use of such tools proliferates, it will be critical to ensure that users have awareness of what types of biases may exist to better inform applicability in their particular circumstances,” they explained.

The officials noted that the agency is examining several approaches to ensure that end-users know how to apply algorithms correctly, at the right time, and in the right situations.

“These are small, initial steps on a longer journey,” they wrote. “Improving health equity requires all healthcare and public health professionals to commit to rowing in the same direction toward better health outcomes. All people deserve proper healthcare, regardless of race, gender, gender expression, sexual orientation, economic status, or location.”

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