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How to Overcome Challenges in Gathering Racial, Ethnicity Data
Payers can boost their race and ethnicity data by recognizing members’ legitimate concerns, communicating clearly, and leveraging indirect data more accurately.
Collecting accurate race and ethnicity data is a critical step in moving the healthcare industry towards greater health equity.
Having accurate race and ethnicity data enhances payers’ ability to prevent inequities in upcoming initiatives and assess their current programs’ downstream impacts and successes.
However, gathering this type of data can be more complicated than the collection processes fo other kinds of personal information.
Before even approaching the procedural difficulties, payers face the question of what race and ethnicity data actually encompass.
The United States Census Bureau adheres to five categories for race, derived from the 1997 Office of Management and Budget’s (OMB’s) guidance: Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or other Pacific Islander, and White.
However, healthcare leaders including DD Johnice, vice president of the Health Transformation Lab at Blue Shield of California (Blue Shield), recognize that race and ethnicity are not so simply classified in reality. These five racial categories alone may not offer feedback on cultures, language proficiencies, and other aspects of a members’ racial and ethnic identities.
“As an innovator, I'm also thinking about the fact that it's not a black and white answer, my race, my ethnicity. People are allowed to self-identify and, in fact, that's our gold standard: we want them to self-identify,” Johnice told HealthPayerIntelligence.
Kevin McAvey, director at Manatt Health, concurred with Johnice’s conclusion. McAvey recently co-authored a Manatt Health report, conducted in partnership with Blue Shield, that addressed using race and ethnicity data to improve California’s health equity.
“We have a lot of work to do to really collect new data elements, to reflect the diversity of our population and the diverse needs that those populations have. That extends well beyond what we are approaching in this paper to include language, sexual orientation, and gender identity,” McAvey told HealthPayerIntelligence.
However, many payers are far from that level of sophistication in gathering race and ethnicity data.
Two out of every three commercial health plans had race data missing for over 50 percent of their member populations, according to a Health Affairs report. Public payers fared a little better, with half of Medicaid health plans and over one in four Medicare plans facing the same data gaps, although 80 percent of Medicare Advantage plans have complete or partial data.
Payers are not solely responsible for these blind spots in health equity data, but they can—and, according to the Manatt Health report, should—take action to improve these outcomes.
Understand members’ reluctance to share race, ethnicity data
For payers to acquire more race and ethnicity data, they need to understand the reasons why certain communities are hesitant to share that information.
“You have to own that there is reluctance and that there is a good set of reasons across different populations for not wanting to give that information,” said Johnice.
Reluctance may be related to the healthcare industry’s history of discrimination. When a health plan requests race and ethnicity data, members may be concerned that they will be treated differently based on their answers. These fears are echoed both by recent data and by the long, deleterious record of racial discrimination in America’s healthcare system.
Discrimination is not the only reason that members might refuse to give health plans their race and ethnicity data.
“The reluctance might not be about the historical pieces,” Johnice pointed out.
“It might be about some very current day consumer things like ‘I don't want you to send my information out and get a million marketing things in the mail’ or ‘I'm unclear how this—which could be related to my medical information—eventually will be shared, amongst what groups it will be shared.’”
Payer leaders must be able to balance an urgency to acquire more race and ethnicity data with compassion for members’ resistance to sharing race and ethnicity data.
As health plan executives and healthcare leaders heed members’ hesitancy around sharing race and ethnicity information, they can create a company culture that empathizes with that hesitancy.
Enrollment staff in particular should be trained to recognize the legitimate reasons that may cause members to resist disclosing their race or ethnicity.
Communicate the end goals of data collection
Members will fill in the blanks about why health plans are requesting race and ethnicity data. They may assume that if they identify their race the health plan will narrow down their options.
“People always think we're going to route them into something, but no, understanding who they are opens up more choices,” Johnice noted. “We actually want to be able to use that information to offer them better benefits, more culturally responsive care management programs, talk to them in a language that they prefer.”
Payers do not have a strong record of communicating with members. In 2020, a JD Power Survey revealed that members’ satisfaction with payers had settled at a score of 719 out of 1,000 points, partially due to a failure to communicate well with members.
Members need to receive clear indications from their health plans regarding how self-identifying their race and ethnicity could improve their care.
In addition to being transparent about how the payer intends to use the race and ethnicity data, payers can switch from making this question optional to allowing members to actively opt-out of responding, the Manatt Health report suggested.
“It’s just making sure that everyone is taking a pause, understanding why data is being collected, and then actively saying, ‘I prefer not to submit this,’ and that's okay,” McAvey explained.
Collect, leverage indirect race, ethnicity data accurately
Because many members choose not to provide race and ethnicity data, payers often lean on indirect or imputed data as supplementary information.
Indirect data can encompass patient experience surveys, administrative and clinical data, and sometimes advanced data analytics, the Manatt Health report outlined.
This source of data is often lacking and there are wide gaps between the projected and actual differences in patient outcomes based on race and ethnicity.
“If we are working with imputed data—meaning we don't know if it's completely and utterly representative of the folks that we're trying to serve—we may not be lobbying for the right level of resources, our attention for a challenge that we're trying to solve,” Johnice explained.
Although it is deficient, indirect data is better than no data.
“Imputed data helps us to make the case today with the data we have,” said Johnice. “But again, I would love to push for people to share their real data. It is important to do both: to work on that real data, but also to keep getting better and better with the imputations and then bumping it up against the reality as that starts to fill in more.”
For health plans looking to reduce the gaps that may result from using indirect race and ethnicity data, McAvey recommended evaluating the standards that their healthcare partners use in regards to race and ethnicity data in order to ensure alignment.
“I would think about making sure that we are using this more for population health purposes and knowing that, at the individual level, there is going to be a margin of error and we do not necessarily want to be tying individuals into that estimation,” McAvey explained.
Payers also may leverage health information exchanges as a way to access reliable data.
Since stakeholders across the healthcare industry contribute to these health information exchanges, they offer a more informed and more reliable overview of race and ethnicity data than one health plan’s data collection channels.
“For such a societal issue, we need to work as a healthcare community to address it,” McAvey advised. “So if individuals aren't fully comfortable supplying this information to their health plan and are more comfortable providing it to their provider, we need to have systems in place to allow that information to be well-used by others in the ecosystem who are trusted partners."
If payers can successfully reduce concerns around sharing race and ethnicity data and boost self-identification, it could result in significant progress towards the ultimate goal: health equity.
“You can't fix what you can't see,” McAvey said. “And too often, our data right now is blind to key community characteristics that we need, patient characteristics that we can use to better health.”
The conversation about race and ethnicity data has far-reaching implications.
“What's so compelling about what might seem like a dry conversation of race, ethnicity, and language data is the unprecedented opportunity for communities of color, for disabled, poor, so many people who are not being heard and are not being able to actively shape how we treat, how we serve, where we go, where that care exists,” Johnice shared.