5 Tips for Health Plans to Improve Race and Ethnicity Data

The Current Landscape

Race and ethnicity data are available for nearly all Medicare beneficiaries. However, while 61.2% of working adults ages 19 to 64 received health insurance through an employer in 2019, less than 25% of commercial health plans had race data for even half of their members. As expectations for stratifying quality results by race and ethnicity increase, having these data is fast becoming both a business and ethical necessity.

Among health plans, there is wide variability around how to collect and analyze race and ethnicity data from their members. Health plans also often face real and perceived barriers to collecting these data. These can include legal and privacy concerns, reluctance from individuals to self-report, hesitancy from health care professionals to gather race and ethnicity data, and a lack of financial incentives or program requirements to collect this information.

While racial and ethnic health disparities have always been present, the COVID-19 pandemic highlighted these inequities and brought them to the forefront of public health conversations. There can be no quality care without health equity, and data which lack race and ethnicity information are incomplete, making it impossible for many health plans to see the full picture.

Improving Data Quality to Advance Health Equity

What is not measured cannot be improved. Though there are many facets to addressing health disparities, improving the quality of race and ethnicity data can help close equity gaps. To do so, health plans must first identify and understand the drivers of disparities that exist by gathering and analyzing high-quality, validated data.

Quality data allows plans to uncover the underlying causes of health disparities, as opposed to only acknowledging they exist. For example, if plan members are not receiving appropriate prescription medications for their health condition or not scheduling preventative screenings, health plans cannot address these inequities. This is why having all the key information first is important.

In 2021, Blue Cross Blue Shield of Massachusetts reviewed 2019 data for more than 1.3 million commercial members and identified health inequities across a variety of different measures. For controlling high blood pressure for adult members with diabetes (ages 18 to 75), 84.3% of Asian members and 82.4% of White members had their blood pressure controlled, as opposed to 71.4% of Black members and 76.6% of Hispanic members. These differences underscore the importance of health plans analyzing and understanding race and ethnicity data.

While the motivation for health plans to improve race and ethnicity data should be focused on delivering quality care for all, there is also a business case for health plans to improve their data. Health disparities drive an estimated $93 billion in healthcare costs and $42 billion in productivity losses annually. By identifying and addressing the gaps in race and ethnicity data, health plans can more efficiently provide coverage to members in spending where it is most necessary.

Here are five best practices health plans can implement to improve race and ethnicity data:

• Take stock of current data and collection practices. Assess what unique obstacles might be preventing the organization from collecting data or using it effectively. Some health plan executives incorrectly assume that they are not allowed to collect race and ethnicity data due to potential legal concerns. However, this is often not accurate. Organizations may be prohibited from requiring this data be reported, as opposed to requesting it.
• Train staff on data collection. Whether over the phone, virtually or in-person, all staff who are collecting data should be trained on how to ask members for their personal data. The data collectors should be knowledgeable on relaying to patients how the data will and will not be used, the importance of collecting the information, and discuss the measures the organization is taking to protect their personal information.
• Be transparent with members. It is vital to explain to members why these data are being collected and how they will be used to build trust. When collecting data in a virtual or online format, consider the use of “help text” which provides an informative description that gives more context about what a user needs to input. Using this text to explain why a question is being asked can increase response rates.
• Collect and validate quality data. Ensuring the accuracy of race and ethnicity data is crucial for it to be utilized effectively in improving members’ health care.Collecting self-reported race and ethnicity data directly from members – considered the gold standard – should be a focus for all health plans moving forward.When self-reported data aren’t available, health plans should only use reliable approaches, validated for use in their populations, to impute race and ethnicity data and should make a plan to begin collecting data directly in the immediate future.
• Share outputs. Once the data have been utilized, it is important to follow up with employers and members to report success stories that demonstrate how having this information improved health outcomes. Complete, validated race and ethnicity data can be used by heath plans to improve services for members through interventions that take aim at the specific health challenges members may be managing, and helping improve patient care and outcomes by working with health care providers to address inequities in care directly.

Health equity is a fundamental component of providing quality care – and understanding whether organizations are providing equitable care requires health plans to take the important first step of obtaining and utilizing complete, accurate, high-quality race and ethnicity data. Health disparities are addressable, and there are straightforward, actionable steps health plans can take to ensure all members are receiving quality health care.

Philip Saynisch, PhD, is a Research Scientist at the National Committee for Quality Assurance (NCQA) and Sarah Shih, MPH, is Assistant Vice President of Research and Analysis at NCQA. NCQA is a private, nonprofit organization dedicated to improving health care quality.