In 2021, the National Committee for Quality Assurance (NCQA) announced it was launching a Health Equity Accreditation (HEA) program. HEA provides a framework for health care organizations to use to measure and improve the equity of the health care they deliver and to identify and close care gaps. With evaluations for health plans, health systems and care delivery organizations having begun in July 2022, many organizations are still wondering how to start down the path toward achieving HEA. Key to their success is learning how to collect the right data, analyze it and leverage those insights to reduce inequities.
Katie McKillen, regional president of Evolent Health Services, recently spoke with Catherine Ahearn, managing director of quality and accreditation at Evolent Health, about how to meet the data requirements for this accreditation.
This isn't NCQA's first attempt at addressing equity issues. How did the Health Equity Accreditation program evolve?
For the last decade, NCQA's Distinction in Multicultural Health Care (MHC) has focused on gathering data on members' cultural and linguistic needs, more effectively communicating with members, and setting goals to improve on those elements. MHC was narrowly focused, but it was a beginning.
As NCQA recognized the need to drive a more holistic and inclusive way to deliver care, in 2021 it announced it was replacing MHC with Health Equity Accreditation, which is a full three-year accreditation. This shift is similar to the one NCQA made moving from Disease Management Accreditation to the more holistic Population Health Program Accreditation. HEA expands on MHC's goals and is focused on advancing equitable care. It is going to challenge all of us to focus on identifying and resolving the inequities and disparities in health care. To do that, you need to look at a whole host of data in a number of areas.
NCQA is continuing to expand the standards over time as well. The next set of standards will be called Health Equity Accreditation Plus and will be even more rigorous. Health Equity Accreditation Plus will help organizations that are already performing at the HEA level to move further on the path to full equity. Where HEA focuses on foundational aspects of health equity within an organization, HEA Plus focuses more on external aspects, like social risk factors and social and community needs and working with community-based organizations to support members.
What are the issues Health Equity Accreditation is trying to solve?
As we all know, in the United States, there are long-standing, deep-rooted problems of racism, and structural and institutional discrimination.
HEA is designed to help organizations focus and further a much-needed discussion about health inequities and disparities. To have the impact we want—to be able to provide high-quality, truly equitable care to members—we must begin to dismantle the existing institutional biases and injustices.
Where can health care organizations start? I believe we have to start at the very beginning, with our recruiting and hiring processes, and then move to our staff training, by providing focused, genuine education. Then you have to take it one step further, to the provider network, to work hand-in-hand with the providers who see patients every day, and in many cases, really know the members and what hurdles they face. We can gather data, we can align it, we can coordinate care, but at the end of the day, we cannot do our job as effectively if we're not tied closely to the clinician interacting with the member.
How do you see the Health Equity Accreditation helping at the community level in addition to the member level?
By gathering the right data, understanding what that data means and then applying it appropriately to the community and into those areas where the community is struggling, we can effectively impact the most vulnerable community members. HEA will help us better understand the structural barriers that exist, using social determinants of health data related to food, shelter, safety, transportation and access to care.
The accreditation standards will push us to gather the "right" information and help address biases so that when we step into the community, we really know the member, and we can target our interventions to the specific community, whether they be related to food insecurity, housing instability, access to care, etc.
How should we define what the right information is and how do we collect the right data without perpetuating existing biases?
I think that's going to be the big question for everybody. We need to start with social determinants. From there, we can determine whether members have access to care, or to the information they need. For example, do they have access to a pharmacy that isn't 25 miles away, or access to transportation? Social determinants data, combined with geographic information, will help derive and understand some of the other dynamics of our member population, like culture, language and ethnicity.
We also need to consider how we label the data. In some cases, labels can be inadequate and fail to capture important cultural nuances that can help us serve members better. For instance, the standard categories for race on U.S. federal surveys—such as American Indian, Alaskan Native and Asian—are very broad. This is being looked at on a national level to see if we need to be more granular, but currently, if we are following the federal standard, we're lacking detail. We're not really determining and discovering what the true inequities are. The same goes for gender and ethnicity.
How do you recommend Medicaid plans and their administrative partners get started on the path to HEA?
At Evolent, we've identified a few building blocks for getting started with health equity.
The very first thing is to address bias. It's like Maslow's hierarchy, where you have to start with the basics of food and shelter before addressing other needs. Bias is at the very bottom. If you address that—in your staff and in the data you collect—it builds on itself to take you to the next level. To address the bias, you have to understand the member who you're talking to. You have to listen and pay attention to what they say and how they say it. At the start, we'll only be gathering data, but if you gather inclusive data, the next steps will happen organically.
Then you can move to another portion of the standards and focus on what is the right data and how we collect it and share it efficiently and appropriately. We know it's very difficult for Medicaid plans to get accurate member data. States don't always have accurate data on members to help plans follow them or speak to them appropriately so they stay engaged. One source of potential data is providers. NCQA has added a huge set of standards to HEA that is focused on providers, because NCQA realizes that the provider network is an essential part of the equation. It's an area that we (managed care) have not historically tapped into very well. For example, providers already take member language into account so that they can communicate with the member at the provider office or facility. But often, providers are not sharing this information with health plans. Or maybe the plan does know that a member speaks three or four languages—but which is their primary language? What is the member's ethnicity and how does that play into making sure that the member gets equitable and quality care? Historically we haven't tapped into the providers and the data they hold.
So how do we use that data to better support the community?
There are so many options. Maybe we use aggregated community data to more effectively evaluate existing member incentive programs or create more tailored value-added benefit programs. Our understanding of what the member needs should be informed by this community data. That's how we begin to focus on the health of a community in a more positive way.
We can't take these first steps until we do three things right: we have a strong relationship with the provider network; we've got the same information they have on members and the barriers they face; and we understand what that data means. It's like three legs of a stool: you've got the administrative partner, the plan and the network. The data collected among all three of those can be very rich. With that data, you can better align activities, help address biases and be in real alignment to deliver equitable care. It's incredibly challenging to do those three things successfully. HEA provides the structure for the data, approach and infrastructure to help plans achieve positive outcomes.