When the National Committee for Quality Assurance (NCQA) launched HEDIS measures in 1991, the project was titled the “HMO Employer Data and Information Set.” At launch, HEDIS was designed to ensure that purchasers and consumers had the information to use to compare managed care plans’ performance—namely, health maintenance organizations (HMOs).
Three decades later, the HEDIS acronym stands for the “Healthcare Effectiveness Data and Information Set,” expanding beyond the original HMO cohort of health insurers. These standards are used by most Medicare, Medicaid and commercial health plans and other healthcare organizations in the U.S. to enable quality comparisons and performance. Each year, NCQA updates the HEDIS data elements. For 2023, the big additions to the data set address health equity.
A Growing Focus on Social Needs and Health Equity
NCQA is looking to this new wave of data to address health equity by bringing transparency to inequities in healthcare quality, promoting inclusivity, addressing social needs to improve outcomes gaps, and to incentivize equity through measuring performance and benchmarks.
In August 2022, NCQA announced five new HEDIS measures including pediatric dental care, safety and appropriateness, diabetic care, and social needs screenings and interventions.
This newly introduced social needs data set encompasses some of the key factors traditionally considered the social determinants of health (SDOH): namely food, housing and transportation. Specifically, HEDIS 2023 will incorporate the following for commercial plans, Medicaid and Medicare:
- Food insecurity screening and intervention
- Housing screening and intervention
- Transportation insecurity screening and intervention.
For each of these factors, the health plan would measure the percentage of members who were screened or prescribed an intervention if screened positive.
Including Race and Ethnicity Stratification in HEDIS
In addition to adding the social needs factors to the data set, HEDIS 2023 will also add race and ethnicity stratification to HEDIS metrics.
First, let’s define “stratification” to make sure we’re all on the same page on this more technical part of the HEDIS 2023 plan.
According to the American Society for Quality (ASQ), stratification is “the act of sorting data, people, and objects into distinct groups or layers,” used with other data analytics tools. In applying stratification to the HEDIS data, it can support better transparency into health plan performance vis-à-vis race and ethnicity to identify where health disparities are and to address the care gaps. On the other hand, stratification can also reveal where disparities do not exist so that best practices and performers can be identified and learned from.
NCQA explained “why” stratification would be a growing aspect of HEDIS measurement:
“Race is a social construct, not biological; stratifying HEDIS measures by race and ethnicity is intended to further understanding of racial and ethnic disparities in care and to hold health plans accountable to address such disparities, with the goal of achieving equitable health care and outcomes.”
The health equity journey begins with stratification, Franzi Rokoske, the head of Population Health & Equity at RTI International, wrote in a March 2022 blog post. Stratification is the “slicing” of patient data by age, race, gender, ethnicity, language, sexual orientation, and other factors—including social determinants of health, such as those being added into HEDIS 2023’s data set.
“The ability to stratify your population—understand all the dimensions of their social determinants of health—impacts your ability to target, in a smart way, where payers and providers spend their time and their resources,” according to research published by RTI International. “This improves focus for the maximum impact on outcomes and achieving health equity. It’s really hard to do that without understanding the underlying population’s characteristics.”
How the Right Data Underpins Accountability and Quality
“Equity requires effort. It’s that simple. And effective effort requires good data plus persistence,” Michael L. Millenson told me in our discussion on the HEDIS 2023 data update.
In 1997, Michael wrote the landmark book, Demanding Medical Excellence, which features the tagline: “Doctors and Accountability in the Information Age.” The book was among the first to gauge safety and quality in the U.S. healthcare system, and Michael is a go-to source of knowledge on the topic.
I asked Michael about the role of data and accountability back when he wrote the book, looking to learn from healthcare history. In 1997, there were few electronic health record systems deployed in U.S. hospitals: Before the HITECH Act, just a handful of hospitals used any sort of electronic medical record—although, of course, all of them billed patients electronically, Michael recalled.
“The information age allows us to measure and manage in ways that were never previously dreamed of in healthcare,” he said. “As a society, moreover, we are far more sensitive to equity, quality of care and outcomes than we were 25 years ago. But the progress we’ve made technologically in healthcare, compared to what we have been capable of doing, is deeply disappointing.”
“EHR data is not as good for ethnicity as might be hoped. Hospitals need to be accountable for active outreach to the community,” he said. That is where data comes back into the health equity challenge—and the mindful intentions and hopes for the HEDIS 2023 data update.
Time for ‘Techquity’
The concept of “techquity” is emerging in American healthcare circles. Techquity will be a featured theme at the VIVE 2023 conference this upcoming March.
As Team VIVE puts it, “Integrating health equity considerations into technology and data practices—or techquity—is increasingly important to reducing outcomes disparities and systemic inequities.”
The HLTH Foundation has convened the Techquity for Health Coalition, a group of health technology innovators, health systems, associations and others committed to addressing health equity and good data practices.
Last year, the HLTH Foundation collaborated with Ipsos on a survey about techquity, asserting that “healthtech has potentially unintentionally exacerbated mistrust and fear in marginalized, vulnerable and underserved communities … use of (these) algorithms, which are often developed based on homogenous and macro-population-level data sets, have been shown to have unintended consequences.”
The study report, The Path to Techquity, concluded that, “Achieving techquity will require strong leadership, long-term investment, organizational transformation, collaboration, inclusivity, transparency, and perhaps most importantly, the will to change.”
And to be sure, really good, inclusive data sets.
As Michael put it, “Accountability is, above all, a social construct. Data to improve only leads to improvement if you believe in it and use it.”
Next Steps for Payers
- Read our blog post about why health equity matters.
- Download our free white paper, “Addressing Social Determinants of Health: A Practical Road Map” to explore how to factor SDOH into the way you engage and support the populations you serve.
- Subscribe to the Medecision blog for more healthcare trends and strategies like this.