As of Measurement Year 2019 (the most recent publicly available data), 76% of racial data and 94% of ethnicity data was incomplete for commercial health plans. This isn't just a data quality issue—it's a barrier to achieving health equity. Health plans cannot address health equity gaps they cannot measure. With 22 HEDIS measures now stratified by race and ethnicity as of Measurement Year 2026, the stakes for collecting complete, accurate diversity data have never been higher.

The solution? Modern Health Appraisals (HAs) that make it easy for members to self-identify in ways that are private, comfortable, and culturally sensitive.

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The Missing Data Problem

In 2010, the National Committee for Quality Assurance (NCQA) introduced two measures to track member diversity: Race/Ethnicity Diversity of Membership (RDM) and Language Diversity of Membership (LDM). These measures were designed to help health plans understand who they serve and identify where data gaps exist.

More than a decade later, the data reveals a troubling picture of incompleteness across all product lines:

• Commercial plans: 76% of racial data missing, 94% of ethnicity data missing
• Medicaid plans: 50% of racial data missing, 70% of ethnicity data missing
• Medicare plans: 26% of racial data missing, 60% of ethnicity data missing

For context, NCQA considers data "complete" when greater than 95% is known, and "incomplete" when less than 50% is known or missing. By this standard, most health plans fall far short.

What's changing for MY 2026: NCQA now requires reporting on the Middle Eastern or North African (MENA) category in alignment with updated federal Office of Management and Budget guidelines. This means health plans must update their data collection processes to capture this new category.

Why does this matter? Because you cannot address disparities you cannot see. Complete diversity data is required for NCQA's Distinction in Multicultural Health Care and is the foundation for any meaningful health equity strategy.

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Why Traditional Methods Fail

If the data has been incomplete for over a decade, what's been going wrong? Several barriers have prevented health plans from collecting complete diversity data:

Reliance on administrative records alone: Many plans depend solely on enrollment data or claims information, which often lacks race and ethnicity details or contains outdated information.

Uncomfortable in-person questions: Asking sensitive demographic questions face-to-face during enrollment or appointments can make members uncomfortable, leading to declined responses or skipped questions.

Limited response options: Traditional forms often force members into binary choices or limited categories that don't reflect how they actually identify themselves.

No opportunity for self-identification: Without privacy and control over how they identify, members may provide incomplete or inaccurate information—or none at all.

The result? Missed opportunities to tailor services, provide language-appropriate materials, and identify disparities in care delivery across different populations.

Good news for MY 2025: NCQA has simplified data source reporting requirements, removing this burden from stratified measures and requiring it only for the RDM measure itself. This change reduces reportable data elements by 58%, making compliance more manageable while still advancing equity goals.

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How Modern HAs Work Better

Digital Health Risk Assessments offer a solution to these longstanding barriers. Here's how PDHI's HRA approach improves data collection:

Private, comfortable self-identification: Members complete the assessment in their own environment, on their own time, with the privacy to thoughtfully consider how they identify. This removes the pressure and discomfort of face-to-face demographic questions.

Multiple selections allowed: Rather than forcing members to "choose one" race or ethnicity, modern HRAs acknowledge the complexity of identity by allowing multiple selections. This is especially important for individuals who identify with more than one racial or ethnic group.

Comprehensive language assessment: The HRA captures both spoken language preference for healthcare AND written materials preference—recognizing that these may differ for some members.

Integrated with health data: Diversity data is collected alongside health risk information, providing a holistic view of each member and their needs.

For MY 2026, these HRAs align with updated OMB federal standards including the new MENA category, ensuring compliance with the latest requirements.

Additionally, MY 2025 introduced optional CAHPS sample frame variables for language preference, helping plans understand survey representativeness and compare plan-provided data with self-reported information.

The digital format naturally leads to higher completion rates—members can access assessments on any device, pause and return as needed, and feel in control of their information.

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Using Complete Data to Drive Health Equity

Once health plans have complete diversity data, what can they actually do with it? The possibilities expand significantly when you know who you serve:

Identify care gaps by population: With 22 HEDIS measures now stratified by race and ethnicity, health plans can pinpoint which populations are experiencing disparities in specific areas of care—from cancer screenings to diabetes management to behavioral health follow-up.

Create culturally appropriate programs: Understanding the racial, ethnic, and cultural composition of your membership allows you to design interventions that resonate with specific communities, incorporating cultural values and addressing community-specific barriers.

Provide interpretation services where needed: Language diversity data identifies exactly which members need interpretation services and in which languages, ensuring resources go where they're needed most.

Develop materials in preferred languages: Rather than guessing which translated materials to produce, plans can target their efforts based on actual member language preferences for written materials.

Track progress over time: Complete baseline data allows plans to measure whether their equity initiatives are actually reducing disparities or if gaps persist despite interventions.

A promising development: NCQA is now comparing plan-provided race and ethnicity data with self-reported CAHPS survey data to assess data quality and concordance. Plans meeting minimum criteria (100+ respondents per item) receive beta reports showing how well their diversity data aligns with member self-reports. This feedback loop helps plans continuously improve data accuracy.

The real-world impact extends beyond HEDIS reporting: better communication with members, improved engagement in care, reduced medical errors due to language barriers, and genuinely culturally competent care delivery.

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Taking Action Now

The MY 2025-2026 requirements represent both challenges and opportunities for health plans:

New requirements to address:

• 22 measures now require stratification by race and ethnicity
• MENA category must be captured starting MY 2026
• Data source reporting has been simplified
• Race and ethnicity must be reported as separate categories

Steps to take now:

1. Implement HRA tools that support new categories and formats: Ensure your assessment platform can capture the MENA category and allows for multiple selections across all race and ethnicity categories.
2. Prioritize direct data collection: Self-reported member data is considered the gold standard. Focus on methods that encourage members to self-identify rather than relying solely on administrative records or imputation.
3. Prepare for the HEDIS format update: MY 2026 brings the largest format update in over 20 years, aligning with FHIR standards. Ensure your systems can handle these changes.
4. Use data to drive real change, not just compliance: Complete diversity data isn't valuable unless it informs action. Build processes to regularly review stratified performance data and adjust programs accordingly.

The path forward is clear: technology makes comprehensive diversity data collection scalable and sustainable. With NCQA's goal of fully digital quality measurement by 2030, now is the time to modernize your approach.

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In Summary

Health equity begins with knowing your members—truly knowing them, in the identities they claim for themselves. Complete diversity data isn't just about HEDIS reporting or accreditation requirements. It's about delivering care that meets each member's unique needs, in their preferred language, with cultural sensitivity and competence.

With 22 stratified measures, new MENA category requirements, and NCQA's continued push toward health equity, the importance of complete, accurate diversity data has never been greater. Health plans that update their HRA tools for MY 2026 requirements, prioritize member self-identification, and use the data to drive meaningful change will be positioned to lead in health equity.

The question isn't whether to improve diversity data collection—it's how quickly you can implement the tools and processes to do so.

Learn more by stopping by the PDHI booth #520 at NCQA Summit next week!

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