What’s Health Equity Got to Do with Quality Measures?
Population Health Alliance
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The Imperative to Measure Health Equity
According to the Centers for Disease Control and Prevention, health equity “is the state in which everyone has a fair and just opportunity to attain their highest level of health.” Factors affecting health equity, or social determinants of health (sometimes called social drivers), “are the conditions in the places where people live, learn, work, play, and worship that affect a wide range of health risks and outcomes.”
In a January 2022 JAMA Viewpoint, Dr. Victor J. Dzau, Dr. Kedar Mate , and Margaret O'Kane made the case that “what is not measured cannot be improved,” and therefore, “The health system must be able to measure and demonstrate improvements in health care disparities to show progress toward achieving health equity.” The authors point out that the US health system does not collect the necessary data to achieve these goals, citing the 2021 National Academy of Medicine report, An Equity Agenda for the Field of Health Care Quality Improvement, and “an absence of standardized data categories, insufficient institutional incentives, a lack of patient trust, reluctance of clinicians to ask for and record data, and inadequate explanations to both patients and staff regarding the importance and purpose of collecting demographic information.” They conclude with the following key point:
There is no quality without equity, and there is no equity without quality. As new quality-improvement measures and approaches are put into place, they should be planned with equity in mind and monitored to ensure they reduce disparities.
Consistent with this drive to include equity in quality measures, the first priority of the Centers for Medicare & Medicaid Services 2022 Framework for Health Equity is to “Expand the Collection, Reporting, and Analysis of Standardized Data…to improve our collection and use of comprehensive, interoperable, standardized individual-level demographic and social determinants of health (SDOH) data, including race, ethnicity, language, gender identity, sex, sexual orientation, disability status, and SDOH.”
The need to collect and use data to support health equity objectives is clear. So, how are we doing?
Race, Ethnicity, and Social Needs Screening...
NCQA 's HEDIS® measures are the foundation of federal, state, and private payer quality measurement frameworks and account for most of the measures used in value-based payment models, including Medicare Part C (Stars). For HEDIS Measurement Year 2024 (the current year), 22 measures can be stratified by race and ethnicity. Consistent with the call for alignment, NCQA uses the Office of Management and Budget standards for ethnic and racial categories. Of the 22 measures, the race and ethnicity stratifications will be publicly reported for five measures as aggregate benchmarks for Measurement Year 2023 (Colorectal Cancer Screening, Controlling High Blood Pressure, Hemoglobin A1c Control for Patients with Diabetes, Prenatal and Postpartum Care, Child and Adolescent Well-Care Visits). For Measurement Year 2023, NCQA included a first-year measure: Social Need Screening and Intervention (more details).
Additional Ongoing Health Equity Efforts…
In addition to updating measures, NCQA, URAC, and The Joint Commission all have accreditation and/or certification programs to advance health equity and promote population health. The National Quality Forum’s Aligned Innovation program – a new initiative to rapidly develop measures for implementation – includes a focused objective to develop health equity assessment methods applicable across behavioral health and maternal outcome measures, the two outcome measure concepts identified by their coalition of stakeholders.
[And there are other efforts. Feel free to add to the list in the Comments.]
Actions Depend on Timely Insights, and Insights Depend on Inputs
So…we have measures in value-based payment models that require race/ethnicity stratification, social needs assessments, and programs that provide guidance and structure to help organizations focus on these important issues and goals. Unsurprisingly, there are challenges, not the least of which is the difficulty of asking people for the information, documenting it in the clinical record, aggregating data across health systems, and submitting data to support appropriate analyses, reports, and benchmarking. In addition, nationally reported measures do not currently require the collection of other important personal attributes such as sexual orientation, gender identity, disability status, or veteran status that are often associated with additional health disparities and inequities. The measures do not account for intersectionality – “people’s lived experiences, health, and well-being, based on their multiple identities (for example, their race, gender, and sexual orientation, respectively).” Further, the focus has been on accountability measures in reporting programs such as CMS Medicare Stars, Medicaid Adult and Pediatric Core Sets, NCQA’s Health Plan Ratings, and value-based payment models – not on improvement-oriented initiatives and measures.
Accountability versus Improvement Measures
There is a difference between reporting data for accountability measures and using data to drive context-sensitive and personalized interventions at the point of care to produce meaningful and measurable benefits for people related to gaps in care and health-related social needs (e.g., housing instability, food insecurity, transportation problems, utility needs, financial issues).
Accountability measures for health plan and national reporting, including digital quality measures (i.e., HEDIS and others), will evolve slowly because change is limited by the pace at which reporting entities can access, collect, and submit the needed information. While faster development of digital measures to replace legacy, claims-based/converted-to-digital measures will help build momentum, this will need to be coupled with enhancements to data quality (i.e., usability). The information required to support better (digital) measures that leverage health equity and disparity-related factors is often captured in unstructured notes (i.e., the person’s story or narrative instead of drop-down boxes and pick lists). This makes it more difficult for health plans to find this information across their entire membership unless they leverage natural language processing and augmented intelligence – something that is nearly impossible with manual chart review and abstraction. Finally, accountability measures use data collected and reported retrospectively to assess what happened instead of what should happen during the measurement year.
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Generating Momentum at the Health System and Practice Level
Rather than use retrospectively collected data to calculate accountability measure performance and attempt to use the same measures to drive equity initiatives, health systems, practices, and clinicians can (and should) move faster than health plans to address individual health-related social needs and population-level health equity gaps prospectively. Personal relationships developed between patients and their clinical teams create trust, which, coupled with transparency of purpose, helps those who might otherwise be reluctant to share personal information. More complete and accessible data at the point of care can drive individualized interventions and population-level initiatives.
Appropriately trained, culturally competent staff should ask, collect, and use information about race, ethnicity, language, gender identity, sexual orientation, disabilities, veteran status, and health-related social needs to meet individual needs and drive targeted quality improvement efforts at the population level. Some of the initial steps should include:
What We Need…
Quality measures need an equity lens that goes beyond stratification by race and ethnicity. We also need to differentiate between retrospective accountability measures that will change slowly and measures that can drive improvement by providing prospective insights leading to meaningful action at the individual and population levels in health systems and practices.
What Do You Think?
The survey from last week's post, Boosting Medicare Star Ratings: What Would You Do? Complete the survey here (Microsoft Form).
Michael S. Barr, MD, MBA, MACP, FRCP
Sr. Director, Population Health Improvement
The Population Health Alliance (PHA) is committed to Quality and Continuity of Care. Our key priorities are advancing value-based care, improving consumer engagement, and addressing social determinants and health equity. Join us. Find out more on our membership page.
If you are interested in this topic, please join the Population Health Alliance!
If you're a current PHA member, join your peers on the Social Care and Health Equity Workgroup. Email Executive Director Thomas Stefaniak at tstefaniak@populationhealthalliance.org to get added.