Unveiling Health Care’s Hidden Stories: The Power of Disaggregated Data

By Oprah Cunningham

In the bustling corridors of health care, a longstanding revolution is brewing — a revolution centered not on new treatments or cutting-edge technology, but on something seemingly mundane yet undeniably powerful: data. At the heart of this revolution lies a simple yet transformative idea: the need for comprehensive and disaggregated race and ethnicity data collection within federally and state supported health programs. The quest for more comprehensive, inclusive, and informed approaches through the use of disaggregated data started decades ago and continues to gain traction. It’s a quest marked by its urgency, complexity, and — most importantly — its profound impact on the very fabric of health care delivery.

Picture a health care landscape where the experiences and health outcomes of people from different racial and ethnic backgrounds are not lumped together, but instead they are categorically understood, respected, and addressed. Measuring health outcomes in the aggregate creates a blurred picture — a picture that conceals the unique experiences of distinct communities and obscures the prevalence of health conditions that disproportionately affect certain populations.

Data enable us to pinpoint and address disparities effectively. Disaggregated racial and ethnic data illuminate variations in outcomes, access, enrollment, patient experience, and program utilization within essential health care programs like Medicaid, the Children’s Health Insurance Program (CHIP), Medicare, and Health Insurance Marketplaces. These disparities, when effectively addressed, pave the way for rectifying historical inequities and offering high-quality, culturally competent health care tailored to individual needs.

Some real-world examples illuminate the potential immediate impact of disaggregated data. The California Health Interview Survey unveiled stark health disparities within Asian subgroups. The survey revealed a greater prevalence of high blood pressure, asthma, heart disease, and delayed medication use for Filipinos compared to Asians overall. This data helped to shed light on the Filipino community’s experience of specific health conditions that might otherwise be overlooked if disaggregated data were not analyzed. Additionally, this data can help provide guidance on prevention, care, and treatment approaches specific to this community in the future.

The COVID-19 pandemic sadly provided more examples of the urgency of disaggregated data collection. In California’s Santa Clara and Alameda counties, disaggregated data showed disparities among Asian ethnic subgroups. In 2020, Santa Clara County collected disaggregated data on COVID-19 rates and found that Vietnamese and Filipino residents were being hit harder than any other Asian American groups. Around the same time, Asian Health Services, a federally qualified health center in Alameda County, started collecting disaggregated data for those receiving COVID-19 testing and found that Vietnamese residents had nearly twice the case rates as Asian Americans overall. The collection of these data led to targeted interventions that mitigated the disproportionate impact of the virus on specific disaggregated Asian communities.

Balancing the imperative for data disaggregation to achieve racial equity outcomes, while safeguarding individual privacy, is also paramount — especially for communities of color who are both underserved and vulnerable to privacy attacks. While the need for privacy cannot obviate the need for communities to have access to meaningful, actionable data, it is important to ensure that any data captured is used only for the desired purpose. Privacy and security protections must be discussed prior to the disclosure of race and ethnicity data to ensure that impacted communities can experience the positive health outcomes associated with the use of disaggregated data, without risking their privacy.

In essence, equity (not only racial, but also based on sex, disability, age, language, etc.) in health care systems can be advanced through meticulous data collection and rigorous analysis, while balancing the need for privacy and extensive stakeholder education.

The journey toward comprehensive demographic data collection in health care programs is not just one of numbers and statistics. It’s a journey of telling previously untold stories, dismantling barriers, and crafting a health care landscape that echoes the diversity and complexity of the human experience.

Much of the content in this blog was inspired by comments given by Mara Youdelman, managing director of federal advocacy at the National Health Law Program, during our press briefing. In this press briefing, The Leadership Conference Education Fund released a new report detailing current standards for collecting race and ethnicity data in all 50 states. The report — “Disaggregation Nation: A Landscape Review of State Race & Ethnicity Data Collection” — provides an unprecedented national overview of race and ethnicity data collection standards.

Oprah Cunningham is the strategic communications associate at The Leadership Conference on Civil and Human Rights.