Health Plan Roles in Addressing Health Equity with Quality Measures

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Summary

Quality regulators are implementing new requirements and performance measures to expand health equity expectations for health plans. Avalere describes common approaches and identifies data-driven strategies to respond.

The Centers for Medicare & Medicaid Services (CMS) deepened their public commitment to advance health equity at the 2022 CMS Quality Conference, reiterating that true quality does not exist without equity. While health equity is an originating pillar of health care quality, CMS programs have traditionally focused on clinical effectiveness, efficiency, and patient safety. However, health equity priorities are gaining presence in program policies, accreditation requirements, and performance measures. Health plans need to respond to these changes and coordinate across business units to meet the expectations of regulators and consumers.

Forefront of Regulator’s Quality Agendas

The inclusion of heath equity in policy proposals continues to gain momentum. While changes are often specific to individual programs, common approaches are evident throughout.

Expanded Requirements

Quality regulators are incorporating health equity into health plan structure and operational requirements. For example, state Medicaid programs are already including equity in their requests for proposals for procurements and re-procurements. Health plans need to describe how internal structures ensure diversity, equity, and inclusion of their staff, as well as how health equity is accounted for in care delivery to members. California’s Medicaid program, Medi-Cal, is another example. It requires all plans to risk stratify their enrolled populations and offer a menu of care management interventions at varied levels of intensity.

Similar updates are also echoed in the Notice of Benefit and Payment Parameters for 2023 proposed rule for the individual and small group markets. The CMS is proposing to require that Qualified Health Plan (QHP) issuers implement a quality improvement strategy focused on reducing health care disparities and, also requested input on expanding QHP accreditation requirements to include the National Committee for Quality Assurance (NCQA) Health Equity Accreditation.

The NCQA finalized changes to their 2022 Health Plan Accreditation program to include diversity, equity, and inclusion standards. They also updated their Multicultural Health Care Distinction program to serve as a standalone Health Equity Accreditation program. Accreditation updates address data collection, quality improvement initiatives, and evaluation of member needs. Seven state Medicaid agencies and 2 exchange authorities require NCQA Health Equity Accreditation for participating health plans.

Emerging Performance Measures

Quality regulators are utilizing several measurement approaches to evaluate health disparities and inequities. For example, stratification is traditionally used to control for variation between health plan contracts; however, regulators are now stratifying quality measures to highlight preventable differences within a health plan. Stratification of quality measures by race and ethnicity is an ongoing initiative for the Healthcare Effectiveness Data and Information Set (HEDIS) and was recently proposed for 5 quality measures in the Quality Rating System for QHP issuers (i.e., colorectal cancer screening, controlling high blood pressure, hemoglobin A1c (HbA1c) control for patients with diabetes: HbA1c control (<8.0%), child and adolescent well-care visits, and prenatal and postpartum care). The 2023 Rate Notice also finalized stratification of additional Star Ratings measures by disability, low-income subsidy, and dual-eligible status for Medicare Advantage plans. While information will be confidential to Medicare Advantage plans initially, the CMS signaled their intent to make the data accessible to beneficiaries in the future.

There is also interest in developing measures that evaluate health-related social needs. In the 2023 Advance Notice for Part C and D, the CMS solicited feedback on development of a measure assessing screening for food, housing, and transportation needs. The NCQA has already started development of a similar measure (i.e., social need screening and intervention) that would be applicable to health plans offering all lines of business and includes nearly all members. The new HEDIS measure could be introduced as early as the 2023 measurement year. Social risk-factor screening measures are not new to Medicaid, with several states investing in measure development to evaluate entities contracted to deliver Medicaid services.

Coordinating a Forward-Looking Strategy

Staying ahead of health equity quality expectations requires data-driven approaches. Operationally, plans should ensure that their data engines and platforms are prepared to collect data elements currently in focus (e.g., race, ethnicity, food insecurity) as well as elements of future interest (e.g., social isolation, violence, elder abuse). Initiatives such as the introduction of ICD-10 Z-Codes, development of electronic social determinants of health (SDOH) terminologies by The Gravity Project, and alignment of member surveys to the 2011 Department of Health and Human Services Race and Ethnicity Data Standards represent efforts to standardize how these elements are defined, collected, and exchanged.

Operational, quality, and clinical business units should develop a coordinated approach to ongoing data analysis to proactively assess member composition, adjust network and benefit design, and address disparities across individuals, providers, and sites of care. While operational transformation to collect, exchange, and evaluate data will take time, health plans can fill data analytic gaps with external sources in the near term. Health plans can perform inward-looking baseline evaluations using administrative and clinical data to identify disparities in disease burden, care delivery, and outcomes within their member populations. External data partners can enhance these analyses through inclusion of public and private SDOH data and national and market-specific benchmark comparisons. Initial disparities to explore include those targeted in quality reporting programs, such as geography, dual-eligible status, race, and ethnicity. However, interest in identifying preventable differences will continue,  and additional consideration can be given to members with rare diseases, advanced illnesses, or social risk factors.

Health equity-informed data analytics can guide strategies to improve measure and operational performance, including:

  • Care Management Program Refinement: Quality measure stratification can highlight potential adjustments to improve member access to and engagement with clinical and care management programs.
  • Member Satisfaction Approaches: Collection and evaluation of language data can help a plan communicate with members in their preferred language and connect members with culturally competent providers and care coordinators who speak that language. This can improve member experience while also ensuring appropriate care is delivered.
  • Alignment of Assessments: Plans can incorporate health equity measurement in provider value-based contracts to promote alignment of health equity goals. For example, Blue Cross Blue Shield of Massachusetts includes equity measures in its payment model contracts to evaluate differences in quality of care across racial and ethnic groups. Penn Medicine incorporated health equity measures into executive annual goals, tying compensation to reduced racial disparities in maternal morbidity and mortality.

Health equity requirements and measures will continue to increase. Avalere has experience in utilizing public and private enrollment files, claims, clinical, and survey data to perform analyses of outcomes, service utilization, and provider performance. Further, Avalere supports health plans in operational gap assessments and strategic planning to guide business decisions. Connect with Avalere experts to evaluate your current approach to succeeding in the new quality environment and design a data-driven strategy that accounts for future regulator and consumer expectations.

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