By Beth Godsey
Vizient Senior Vice President, Data Science and Methodology
Back in the 1980s, there was a game show called Classic Concentration in which contestants were shown small portions of an image and endeavored to guess what the larger picture might be. Sometimes their assumptions were right, oftentimes not. No one knew for sure until the pieces converged.
Most indices being considered for health equity purposes operate in a similarly fragmented way. The data sets allow for educated guesses about life expectancy and more, but there's not enough breadth or specificity to say with near absolute certainty that the picture is a full one.
Unlike Classic Concentration, health equity is far from a game, and the extrapolations based on these indices can impact everything from community funding to availability of life-saving resources. Calculating the increasingly complex equation of ensuring everyone can attain their highest level of health requires an index with the kind of robust data integration that allows health inequities to be examined from every conceivable angle.
That's exactly what the patent-pending Vizient Vulnerability Index™ does. Launched in winter 2021, the index integrates data from various sources to provide deeper insights regarding community needs, including American Community Survey 2020 (U.S. Census) five-year estimates averaging 2016-2020 survey data; the USDA "food desert" measure of low-income populations beyond a half mile (urban) or one mile (rural) from a grocery store; HUD "severe housing cost" measure of housing cost burden over 50% of income; and provider shortages, broadband availability, opioid dispensing, crime rates, and EPA data on air and water pollution and chemical and waste hazards.
The Vizient Vulnerability Index — which will be publicly available later this summer — identifies nine social needs domains that become even more insightful when combined with Vizient's Clinical Data Base (CDB), a repository of patient outcomes data from over 1,100 Vizient member hospitals that includes more than 135 million distinct patients of all ages and payer groups.
How does the Vizient Vulnerability Index work — and what sets it apart?
When thinking about the social determinants of health that exist within communities, it's certainly true that economic challenges weigh heavily on social needs. But there are additional access barriers that play an equally critical role — challenges that many indices simply do not account for. For example, neither the Area Deprivation Index (ADI), Social Deprivation Index, Social Vulnerability Index nor Community Resilience Estimates include access to healthcare, physical environment or public safety as social determinant of health domains. The Vizient Vulnerability Index, on the other hand, includes those three domains along with income and wealth, employment, education, housing, transportation and social environment.
Intent also is key. The ADI was originally developed to inform mortality risks and is now a ranking of neighborhoods by socioeconomic disadvantage to inform health delivery and policy whereas the Vizient Vulnerability Index describes how social determinants of health drive life expectancy in communities — and can be applied to several different health-focused outcomes, particularly related to chronic disease incidence and management, readmission rates, ED utilization and maternal well-being.
The Vizient Vulnerability Index also excels in its measurement focus. Let's examine the measurement focuses of the four previously mentioned indices on the topic of life expectancy across all census tracts in the U.S. (Note that in the Vizient analysis below "r2" is a correlational coefficient that expresses the relationship between an index's components and what is being measured, in this case life expectancy):
- The ADI includes 17 components (i.e., measures or data points) with income and housing accounting for almost all of the variation. The index's fit to life expectancy is r2 0.40, meaning only 40% of the variation in life expectancy is explained by its components.
- The Social Deprivation Index has nine components, including race (Black), gender and age (women 15-44), with a fit to life expectancy of r2 0.31.
- The Social Vulnerability Index has 14 components in four domains, with income and education accounting for nearly all variation. Since the index is intended for disaster management planning, its fit to life expectancy is only r2 0.20.
- Community Resilience Estimates includes seven household risk factors and three individual risk factors, including age (>64). Populations with greater than or equal to three risk factors have a fit to life expectancy of r2 0.19.
Conversely, the Vizient Vulnerability Index includes 43 components allocated across nine domains. Its identification of the variation in life expectancy has been quite significant, with a 75% correlation between life expectancy and the impact of social factors.
Another of the Vizient Vulnerability Index's key differentiators is its ability to provide insights at the local census tract level — and, importantly, it doesn't assume that communities are impacted by different drivers of health to the same degree. Explaining life expectancy will vary in the south side of Chicago, in rural Indiana, on a Native American reservation or in Alaska. The Vizient Vulnerability Index provides specific, quantifiable insights for the social needs of individual communities whereas other indices apply a single index algorithm to the entire United States.
So, what does this mean for bettering health outcomes?
Here's where I'll argue that Vizient is a trailblazer in this space due to the Vizient Vulnerability Index's ability to fully quantify and prioritize the inequities that communities are experiencing. In one geographic area, the most critical issue might be food deserts — in another, it could be environmental conditions like living next to a Superfund site, or perhaps it's public safety or housing or access to care.
Whatever the issue, clearcut data enables health systems to more effectively focus their interventions to mitigate these challenges. For example, if a community's primary pain point is access to care, the health system can focus on increasing availability of primary care visits, as well as obstetric and behavioral health services.
Of course, many social determinants that impact communities extend beyond the hospital's walls, whether it's lack of housing, transportation or public safety. But by knowing exactly what issues are affecting local residents, it gives health systems perspective on possible resources or partnerships necessary to better support their patient population. Ultimately, the Vizient Vulnerability Index provides a multitude of different touchpoints for healthcare organizations to understand their community and where gaps exist. Other indices simply don't allow for that same level of specificity.
What are the consequences of not seeing the full picture?
Many of these indices are used to identify a community's social needs and allocate funding or incentives for greater access to resources, including healthcare. However, in the context of health equity, if the index used is not calibrated to the specific local community, and does not adequately account for the many social determinants of health, then it's likely to result in an inappropriate amount of funding — whether too much or too little — because of overgeneralization.
This very problem is playing out in real time as the Centers for Medicare and Medicaid Services (CMS) implements policies and programs that use the ADI to help address health inequities (e.g., ACO REACH and Medicare Shared Savings Program).
Politico Pro recently highlighted that the CMS payment model, though well intended, likely inadvertently penalizes low-income people and communities of color. According to the article, "in parts of the country where extreme wealth and poverty live side-by-side, the metric can produce distorted results because home values tend to be higher in urban areas, even in places rife with poverty and poor health outcomes."
Similarly, a recent Health Affairs article noted that even though most census tracts within southeastern Washington, D.C., have life expectancies in the lowest quintile nationally, no neighborhood in D.C. would be considered disadvantaged when using the ADI. As a result, patients in these communities continue to be excluded from policies and programs that aim to enhance care through additional funding or incentives.
This is not a disparagement of the ADI, which has been effectively used in numerous research efforts, but is instead an acknowledgement of the limitations many of these indices have when it comes to identification of social needs at the local level — which is precisely what the Vizient Vulnerability Index aims to rectify.
For example, the ADI shows greater social needs in Plains states as compared to the Vizient Vulnerability Index, which means communities in Plains states are effectively prioritized in disbursement of limited resources. In Appalachian areas — where there are numerous challenges including little access to transportation, housing and healthcare — the Vizient Vulnerability Index indicates more social need compared to the ADI. In fact, when using the Vizient Vulnerability Index, considering the MSSP advance investment payment (AIP) policy, providers serving patients living in Appalachian areas would receive a 20% higher AIP than when the ADI is used.
To put it simply: If you're not measuring the specificity of what's happening at a local level, you're not allocating the right resources.
What are the implications moving forward?
Health systems and the communities they serve historically have found it difficult to make sense out of various data sources to identify community-level challenges and implement the right programs in response.
Among other uses, the Vizient Vulnerability Index supports and quantifies improvement over time. For instance, if a health system sees that the access to care domain has become less of a challenge, the index can help them measure the impact of their interventions. In order to say, "This approach is working," the proof is in the data — and more specifically, in the holistic picture that the Vizient Vulnerability Index creates.
For more information about the Vizient Vulnerability Index, email HealthEquity@vizientinc.com.
About the author
Beth Godsey oversees analytical modeling, metric development and the hospital ranking/scoring methodology and framework for Vizient members. Additionally, she supports member scenario and impact analysis regarding changes to the national landscape, including, CMS Pay for Performance Program methods and publicly reported measures and methodology. Prior to coming to Vizient, Godsey worked in the Center of Clinical Effectiveness at BJC HealthCare in St. Louis. Godsey has 15 years of experience in statistical analysis and modeling and some of her key accomplishments and experience include providing advanced analytical support for major hospital strategic initiatives and providing systemwide analytical support. Godsey has masters degrees in predictive analytics from Northwestern University and business administration from Webster University in St. Louis. She earned her Bachelor of Science in statistics from the University of Tennessee at Knoxville and is a Six Sigma Black Belt.