This video was initially published by Health IT Today.

Last month Audacious Inquiry President Scott Afzal spoke with Health IT Today Founder and Chief Editor, John Lynn, about health equity, health disparities, and data standards as part of an ongoing series of interviews with top leaders in health IT. The discussion centered on Audacious Inquiry’s publication of an eBook about health equity earlier this year titled, “Health Equity and Health Disparities: The Role of Health IT and the Need to Standardize Data Collection.”

The interview, transcribed below, highlighted key themes surrounding how we define health equity and the role of health IT in addressing health disparities. Afzal shared that health equity is essentially about ensuring all people have an equal opportunity to be as healthy as possible despite social circumstances that may present as barriers to achieving optimal health. For example, struggling to find providers who speak your primary language, being unable to afford medications, living in an area with high pollution, or lacking access to nutritious foods are all socially determined factors that can adversely affect health outcomes.

To address these health disparities, the health information technology sector has been focused on ensuring that patients’ demographic data related to social determinants of health (SDOH) is being collected and standardized for interoperability. Collecting and standardizing SDOH data is critical to developing a solution for health equity because it will allow healthcare professionals to understand what health disparities patients face to know how to address them.

The foundational work to standardize SDOH data collection began back in 2015 when the Office of the National Coordinator for Health Information Technology (ONC) created a certification edition that required SDOH data elements. While it may seem like collecting and standardizing data is a small piece of the larger solution to achieve health equity, Afzal explained that now in the health IT sector, health equity is being built into solutions by design as a direct result of these data standards.

Without this foundation, the SDOH data that healthcare providers, health plans, and care teams need to help address disparities patients face may be missing from patient health records, could be overlooked in a data feed, or may be inaccurate. Afzal recommends that organizations in the health IT space examine their own systems to see what they can do now to support enhanced health equity data exchange for the future.

You can read an edited transcription of the Health IT Today interview below.


John Lynn: What is health equity and why does it matter?

Scott Afzal: It helps to make sure we have a common vocabulary when talking about health equity. The Robert Wood Johnson Foundation definition is really good, defining health equity that everyone has a fair and just opportunity to be as healthy as possible. The Centers for Disease Control and Prevention’s definition has a also includes that no one is disadvantaged from achieving that opportunity for health because of a social position or other socially determined circumstances. Health equity is fundamentally important to create that type of opportunity for each individual where health disparities, the health differences linked to those social differences, aren’t as prevalent.

JL: What are some examples of health disparities that are maybe highlighted in the eBook?

SA: At the highest level, think about things like disproportionate disease burden with diseases like asthma or diabetes, overall mortality rates, and life expectancy, alongside basic access to care. If you were to look at these health disparities closely, what you would see is different health outcomes tied to things like race, ethnicity, sexual orientation, gender identity, and language. Then there are major macro-level inputs to health disparity like poverty, access to healthy foods, access and ability to afford medications, and environmental hazards like poor air quality. The healthcare system has an important role in achieving health equity, but it’s a much larger societal challenge that requires policy action beyond what Health and Human Services can do independently.

JL: It is a larger societal problem. The healthcare system is not going to solve many of those challenges, so how can health IT, an even smaller subset of healthcare, help address these health disparities?

SA: Great question. We need to look at how to apply those areas where do have skillsets and expertise against this large challenge. A couple points to highlight include ONC’s work on interoperability standards to support social determinants of health (SDOH). Going all the way back to 2015, ONC’s been working on standardizing collection of SDOH with the certification edition, and currently ONC requires the implementation of USCDI version 1 data collection standards for race, ethnicity, and language. Last year, they released USCDI version 2, which included SDOH data elements on sexual orientation and gender identity and four other data elements related to food, housing, transportation, and security.

The second, is the Gravity Project, which is an HL7 accelerator focused on work to develop standards for sharing data related to SDOH. And Gravity’s work will support how providers and community-based organizations and technology solution providers consistently share data by having uniform standards and implementation guides.

JL: How close are we to really making an impact on SDOH?

SA: Even though as you look at these big macro issues in the system like, take how social services are reimbursed, the solutions to network organizations managing these issues and to put a payment infrastructure under them is new and nascent but it is happening. We’re not just a couple years in, we’re seven years in. The foundational work on things like FHIR and the standards in general, when combined with normalized data sets to insert into those transactions, we’re actually further along than most people think. Companies across the ecosystem are designing with health equity first rather than trying to retroactively solve for this challenge in some sort of point solution. Health equity is being built by design, and that starts with standards.

JL: Is that how health data and interoperability are playing into this? By providing that standardized way for any healthcare organization to get access to this data?

SA: Getting the data foundation set is a really worthy focus area, particularly in our domain of the world. First, consistently collecting health equity data—it sounds simple, but ensuring that you get outbound data that is accurate and usable and actually captures data on race and ethnicity and gender, that doesn’t happen broadly. Some of our early expertise was in getting basic HL7 V2 data, ADTs, and the primary purpose of receiving those outbound V2 messages may not place value on those SDOH fields in the message. So you might just overlook it and before you know it, you’ve got a thousand inbound ADT feeds with unusable race, ethnicity, and gender data. Then you’d have to go back and work through all that data. That’s why having that broader picture and establishing that baseline of connectivity and ability to exchange standardized data really makes a big difference.

JL: Now that we have the data to understand the inequities and the disparities, we can start to address the problems, whereas before, we were maybe ignorant to the problem.

SA: Yeah, and going back to what is possible quickly, including what infrastructure do we have in place today both in terms of the core systems the data is being entered into and consumed from. Is it being captured in the first place, is it being captured in a standardized way and can it be exchanged in a standardized way? That’s where so much of the work that the Gravity Project is doing really matters, and the work ONC is doing through USCDI really matters.

In the beginning of the pandemic in 2020, only 20 states could report race and ethnicity data about who died from COVID-19. In those early days it was really unclear what the impact was when you wanted to look at data through that lens.

JL: How is Audacious Inquiry looking at working on this problem?

SA: Well first is putting resources into trying to understand it and engage in a meaningful way. Our Health Equity eBook is part of that. It’s us educating ourselves and then sharing what we learned with the community we work in, so actually putting the work and effort into looking at our own technology and solutions. For example, how do we make sure we’re starting to require that SDOH data fields are shared in ADT data feeds, and as USCDI version 2 data normalization goes into effect, that we’re adopting what the standards require through certification.

I encourage any company to look at their own systems because ultimately the early steps you can take around the types of data that are transacted regularly today, may not be as heavy of a lift but can have important impacts down the line for both foreseen use cases and also can offer the ability to react when that data becomes far more relevant as we saw during the pandemic.