How to Achieve Health Equity? Leaders Say Start Unlocking Race and Ethnicity Data

June 2, 2021
Manatt Health and Blue Shield of California have partnered on a paper detailing why states need payer data to identify inequities and address disparities

One of the many unfortunate realities of the COVID-19 pandemic is that it has underscored historical inequities throughout the U.S. healthcare system. In that realm, the crisis has also uncovered there simply isn’t reliable enough race and ethnicity (R/E) data available that allows healthcare stakeholders to understand key contributors to disparities. According to a recently launched Health Equity Tracker, for instance, 38 percent of COVID-19 cases reported unknown race and ethnicity.

In a recent paper written by two leaders at consulting and professional services firm Manatt Health—Alisha Reginal, manager and Kevin McAvey, director—in partnership with Blue Shield of California, entitled “Unlocking Race and Ethnicity Data to Promote Health Equity in California: Proposals for State Action,”  the authors note that “Health plans are well-positioned to collect R/E data and use this information to promote health equity. However, plans face several data collection challenges that result in significant reporting gaps,” they write.

Some specific challenges in race and ethnicity data collection, the authors contend, include: individuals’ reluctance to self-identify—which could be the biggest barrier of all since we are our own source of truth regarding R/E information, yet many choose to not voluntarily share it with their health plans; health plans often not being required by federal or state authorities to collect R/E data for significant portions of their members; and inconsistent use of standards. Variation in the collection and reporting of R/E data prevents accurate comparisons of the quality of care being delivered to different population groups across multiple entities, the authors assert.

These impediments, the paper’s authors believe, are significant because “states, plans, consumer organizations and providers can use R/E data to identify barriers to healthcare access and monitor the impact program reforms have on health inequities.” Fortunately, “some state Medicaid managed care programs and state-based health insurance marketplaces have pioneered such requirements, requiring plans to collect and use R/E data to identify and address disparities,” they add. One example they offer is California’s Department of Health Care Services (DHCS), which analyzes Medi-Cal Managed Care Plan (MCP) quality data received through its External Quality Review Organization (EQRO) process to assess potential differences in health outcomes between population groups, and then share those analyses with plans to guide interventions.

Nonetheless, the key challenge of individuals not providing R/E data is a major foundational obstacle and in a recent interview with Healthcare Innovation, D.D. Johnice, vice president, health transformation lab at the Oakland-based Blue Shield of California, opines that people aren’t willing to give this information because the “healthcare system hasn't always been kind to everyone. And it’s not easy to forget, because [an inequitable healthcare system] is not just a thing of the past. It still exists today, and systemic racism still exists today, too. So that makes it very difficult, even when you are trying to do something to create equity and minimize disparate outcomes. It isn't always easy to disabuse people of the reasons that they won't provide this information, and therefore, it's really hard to get this done,” Johnice acknowledges.

What can be done to fill some of these R/E data gaps? Johnice offers that being very transparent with people about the reasons why health plans want the information, how they will use the information, and in which ways they will share back with members what they have done with the information will go a long way. “There's no accountability [currently]; there's just a [system] that sucks in all of your information, and you have no idea what happens with it. This means that anyone who would seek to hold us accountable for addressing inequities and racism in the system won’t be able to see if we are accomplishing it or if we are moving the needle at all.”

There are several layers to the impact of healthcare organizations not being to collect this data for their members, notes Johnice. For one, there could be missed opportunities to intervene before lives are lost or severely impacted by not receiving the quality standard of care, and in some cases, just a basic standard of care, she says. “But in other cases, you're talking about not receiving care [at all]. Right now, we're all focused on COVID, but before COVID, there were disparate outcomes for [other health conditions], such as whether or not black women survived breast cancer,” she adds. Indeed, Black women have the highest breast cancer death rates of all racial and ethnic groups and a 41 percent higher rate of breast cancer death than White women, according to the American Cancer Society. “The stats on COVID mortality [and racial disparities] look a lot like the stats on cancer,” Johnice asserts.

How tech can help

According to the paper, in response to R/E self-identification challenges, many health plans are increasingly relying on indirect or proxy methodologies to collect R/E data for their membership. They note that indirect data sources may include patient experience surveys such as the Consumer Assessment of Healthcare Providers and Systems (CAHPS), clinical data from providers or health information exchanges (HIEs), or other external administrative data resources.

To this end, Manatt Health’s McAvey notes in an interview that HIEs “are uniquely positioned and functionally equipped to securely collect, link and share race and ethnicity among health plans, providers and payers.”

When thinking about who is collecting what information about patients and members in the healthcare system, McAvey offers the example of Medi-Cal, California’s Medicaid program, which solicits race and ethnicity information from the member at enrollment, which then flows downstream to the plan. From there, the plan may try to enhance that understanding, and then it goes down to the provider, at which point the provider hopefully further enhances that understanding on their end, he explains. “But they are often lacking technological and data flow mechanisms to make sure that everyone in the ecosystem knows as much about this population as possible. So everyone can serve their respective roles in supporting better health. And that's where HIEs serve as historical and natural brokers to share this information with organizations that can use it.” says McAvey.

Related to HIEs, the paper also notes, “Building on their existing connections and processes, HIEs can use the data they receive from participants to create centralized R/E records for all members, improving data acquisition; apply centralized, standardized methods of R/E estimation, or use external data sources, to fill R/E data gaps while minimizing the impact on overall data integrity; and facilitate R/E data standardization among participants.”

McAvey also points to the need to develop consensus around a common standard for collecting this information. He says one of the core challenges right now is that even with those who dutifully and responsibly try to assess their patient and member population, they're often assessing them by different classifications, “which makes it incredibly difficult and oftentimes impossible to look across populations of providers and of plans to really understand where we are and where the problems lie.”

As such, in the paper, McAvey and Reginal write, “A cross-agency workgroup should be convened to establish R/E data collection standards and acquisition targets for contracted and regulated health plans. Requirements should be embedded in regulations and state-administered contracts. Acquisition requirements should elevate R/E data collection as a plan priority, ensuring the data is available to guide interventions. The state should also facilitate sharing of industry best practices for maximizing member self-identification and optimal use of indirect data.”

In the end, Johnice believes that progress will be measured simply by how much data health plans can get from their members. “We can’t escape it and we have to get a little more creative in terms of how we go about getting the data,” she says, offering the example of asking about race and ethnicity when members select their health plans every year.

“We also want to make it so that whatever door [patients] open in terms of the healthcare system, or in seeking services to remove barriers to healthcare, we need to be there, and be prepared to share how we will use the information, how they can understand better the outcomes of sharing that information, and then how they can get follow up,” she says.

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