With greater support from CMS, and COVID-19 widening the health disparity gap, there has never been a greater opportunity for healthcare organizations to develop and implement strategies that directly promote health equity. This comprehensive overview will enable you to prepare for upcoming policy changes, explore the root causes of health disparities, and begin developing an actionable health equity strategy your organization can employ.
Written by Ben Tuck, ClosedLoop
Originally published February 2, 2022. Last updated June 19, 2023. • 15 min read
There has never been a better opportunity for your organization to help advance health equity than now.
In October 2021, the Centers for Medicare and Medicaid Services (CMS) launched a complete strategic refresh through their Innovation Center (CMMI) with the overarching goal of achieving equitable outcomes by providing high-quality, affordable, person-centered care. Their new strategy is centered around five core objectives that will guide alternative payment model design for years to come.
Advancing health equity is one of these initiatives.
ClosedLoop and its partners consider advancing health equity an industry-wide imperative, and we’re committed to proactively embedding equity in every healthcare decision. Persistent disparities drive preventable suffering, produce negative outcomes, and erect barriers to achieving optimal health. We’re working to identify and eliminate these disparities with data, and we encourage you to join us in the pursuit of health equity.
As defined by the CDC, health equity is achieved “when every person has the opportunity to attain their full health potential and no one is disadvantaged from achieving this potential due to their social position or other socially determined circumstances.” This requires coordinated efforts to address pervasive inequalities, discrimination, and disparities.
According to the Healthy People 2020 report, health disparities are “closely linked with social, economic, and/or environmental disadvantage” and “adversely affect groups of people who have systematically experienced greater obstacles to health based on their racial or ethnic group; religion; socioeconomic status; gender; age; mental health; cognitive, sensory, or physical disability; sexual orientation or gender identity; geographic location.”
Health disparities are pervasive and have an immense impact on outcomes. For example, Black women are three to four times more likely to die a pregnancy-related death compared to White women, and they are up to 12 times more likely in some cities. Health disparities also result in avoidable, excess spending. Recent studies of racial equity estimate that $135 billion could be saved annually if racial disparities in health were eliminated, including $93 billion in excess costs of care.
Eliminating disparities and advancing health equity has always been a priority for CMS, but it’s now a major objective that will be measured and considered in every stage of payment model design, testing, participant and program evaluations, and ultimately reimbursement. All new value-based payment models will:
Require participants to collect and report on demographics, and when applicable, social determinants of health (SDoH) data
Include patients from underserved communities and identify opportunities to reduce inequities at the population level
Ensure providers are not disincentivized from participating and potentially introduce new measures to assess impact on equity
CMMI’s new strategic objectives come at a pivotal moment, as the COVID-19 pandemic significantly exacerbated long-standing disparities. Life expectancy for Black people has consistently been lower than for White people, and while the gap shrunk over the past decade, COVID-19 increased it to a difference of six years—the largest gap since 1998. Minorities also had over three times more premature excess deaths per 100,000 than White people in 2020, reflecting increased risk of exposure to COVID-19 due to socioeconomic disparities and barriers to care.
With greater support from CMS, and COVID-19 widening the health disparity gap, there has never been a greater opportunity for healthcare organizations (HCOs) to develop and implement strategies that directly promote health equity. This comprehensive overview will enable you to prepare for upcoming policy changes, explore the root causes of health disparities, and begin developing an actionable health equity strategy your organization can employ. Specifically, we’ll cover:
CMMI’s New Health Equity Objective
How Social Determinants of Health Fuel Health Inequities and What You Can Do About it
How COVID-19 Exacerbated Health Disparities
Developing a Strategy to Prioritize Health Equity
How to Measure and Mitigate Algorithmic Bias in Healthcare
Let’s get started.
Advancing health equity is a core objective of CMMI’s refreshed strategy to dramatically increase the expansion of value-based payment models that reduce costs, ensure quality care, and improve health outcomes for Medicare and Medicaid beneficiaries. Their new strategic objectives will heavily lean on the center’s policy and operational learnings, and advancing health equity draws directly from the number one lesson learned over the past decade: ensuring health equity is embedded in every payment model.
In outlining health equity as a core objective, CMMI detailed the challenges they’ve experienced, their main areas of focus moving forward, and the next steps they’ll take to create a more equitable system for everyone.
Historic Challenges to Ensuring Health Equity
Over the past decade, the center has experienced difficulties thoroughly integrating equity in payment model design and reaching their desired level of impact. To incorporate equity in every facet of model creation and implementation, CMMI conducted extensive reviews to identify the following challenges and issues that have historically limited progress:
CMMI’s Four Key Efforts to Advance Health Equity
CMMI is focusing their efforts around four key areas to address and overcome the challenges they’ve experienced. These actions will broaden the reach of models, provide previously unavailable measures of impact, and help to refine models with new learnings. CMMI will:
CMMI’s Next Steps
CMMI also detailed their next steps, providing a closer look at their key efforts and how exactly they plan to achieve this objective. In the near future, CMMI will:
Address barriers to participation. Some aspects of model design and the application process have historically limited engagement from rural and safety net providers, and CMMI will ensure they are not disincentivized from participating.
Create new data collection requirements. These new requirements will necessitate beneficiary-level demographic data and track model impact for underserved beneficiaries. This may also include financially incentivizing and supporting data collection needs when appropriate.
Collect and leverage social needs data. CMMI will screen for social needs, coordinate with community-based organizations, and collect social needs data in standardized formats.
Analyze and learnfrom program data. The characteristics of participating providers and beneficiaries will be evaluated and used to help ensure equitable reach of models.
Create new quality measures. These measures will incentivize the reduction of health disparities and measure model and provider performance.
Provide support for equity education. Model participants caring for underserved populations will receive training and technical support as appropriate, and CMMI will share best practices for partnering with community-based organizations.
CMMI’s new models will directly incentivize advancing health equity. CMMI has announced that they’re considering upfront payments, social risk adjustment, and payment incentives for reducing disparities. This will enable greater engagement from HCOs that care for underserved populations and help to include organizations that have not participated in any of CMMI’s prior payment models.
Social determinants of health (SDoH) profoundly affect a person’s overall health, and addressing them is key to advancing health equity. The World Health Organization (WHO) defines SDoH as “the non-medical factors that influence health outcomes. They are the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.”
SDoH have an immense impact on outcomes and fuel persistent health inequities. Studies suggest that SDoH account for up to 30–55% of health outcomes, and estimate that they make up a far greater contribution to overall population health than medical care or genetics.
There is also an economic imperative to address SDoH. Health disparities cost hundreds of billions of dollars annually in direct medical costs and indirect costs tied to lost productivity. This is especially concerning, as U.S. health spending is projected to reach $6.2 trillion by 2028, but 25% of total healthcare spending is estimated to be wasted. Given the estimated impact of SDoH relative to medical care, proactively addressing the socioeconomic factors propagating health disparities may significantly reduce this excess spending while improving outcomes.
An Example of SDoH: Where You Live Matters
The definition of SDoH is broad and it can be helpful to zoom in on a single subset of social factors to contextualize how significantly they contribute to health. Consider just the environment in which people live. A person’s ZIP code is a stronger predictor of their overall health than other factors, and in some U.S. cities, a child’s life expectancy can vary more than 25 years between neighborhoods that are only a few miles apart. Where someone lives is associated with a variety of social factors that can negatively affect health, including:
Living in a food desert. Significant distance to grocery stores and other sources of food can deprive people of access to affordable options and leave them with insufficient nutrition.
Exposure to violent crime. Communities with higher crime rates and violent incidents are associated with worse health outcomes.
Local environmental factors. Local water and air pollution are detrimental to health, potentially leading to strokes and lung cancer.
Barriers to physical activity. Neighborhoods lacking the infrastructure for regular exercise can significantly contribute to worse health (e.g., greater rates of obesity).
The significance of living space extends far beyond the examples listed above. People may also lack access to broadband internet, health services, educational opportunities, and may live in residences constructed with lead and asbestos.
How Healthcare Organizations Can Address SDoH
Addressing SDoH is critical to achieving health equity and succeeding in value-based care. To this end, HCOs can participate in CMS’s alternative payment models (APMs), which incentivize tackling the root causes of poor health and provide reimbursement for quality of care rather than quantity of services provided. In addition to partnering with CMS, HCOs can collaborate with community-based organizations that systematically link healthcare and social services for people at risk of poor outcomes. Increasingly, these collaborations are forming to specifically address SDoH, and partnerships between clinicians, social service agencies, and health systems are on the rise.
One such collaboration is the Pathways Community HUB (HUB). The HUB acts as a registry for at-risk individuals, pairs them with a coordinator with access to services, enables and monitors service delivery, and ties payments to milestones and improved outcomes.
The Idaho Health Data Exchange (IHDE) is another example, implementing a search and referral platform for its provider users to better understand SDoH and enhance the exchange of data. It also partnered with a social care network to help providers connect their patients with relevant social services and community resources.
To take the first step, HCOs can work to identify specific social needs by collecting non-medical, demographic data. This is key to identifying the most actionable areas for improvement and the population subsets at the highest risk for negative outcomes due to specific SDoH factors. To conduct this analysis, HCOs can distribute social needs assessment surveys, collaborate with community-based organizations, and draw on publicly available datasets, such as the Area Deprivation Index, to evaluate where barriers and disparities exist.
Driving new and existing initiatives with SDoH data and using this data to design interventions will help close equity gaps. HCOs can also go a step further by implementing technology solutions to coordinate care, predict risk tied to SDoH on an individual level, and surface the specific SDoH factors that contribute most significantly to increased risk.
COVID-19 simultaneously exacerbated existing health disparities and introduced entirely new ones. The pandemic disproportionately impacted people of color. Due to a combination of persistent health disparities and SDoH factors, they are at higher risk for infection, severe illness, and death.
The Kaiser Family Foundation found that “Black people accounted for more cases and deaths relative to their share of the population in 30 of 49 states reporting cases and 34 of 44 states reporting deaths.” Moreover, they found “the COVID-19 related death rate among Black people was over twice as high as the rate for White people.”
The pandemic is also imposing economic pressure on low-income communities. These populations are more likely to hold jobs that can’t be performed remotely, potentially leading to either unemployment due to pandemic-related shutdowns or increased risk of contracting COVID-19 due to greater exposure.
Survey data reports that approximately 60% of Hispanic households and roughly 50% of Black households lost a job due to the pandemic, compared to just 40% of White households.
The risks and severity associated with COVID-19 are further compounded by structural barriers to care and health resources, existing insurance coverage disparities, and an inability to take time off work without severe financial repercussions and potential loss of employment if infected.
Combating disparities caused or exacerbated by COVID-19 is paramount, but HCOs will only be able to maximize their efforts by collecting data that reflects race, ethnicity, and SDoH. Tackling COVID-19 health disparities begins with identifying them, developing a strategy that directly supports people at the highest risk for negative outcomes, and partnering with community organizations to close the gaps.
Achieving health equity necessitates establishing it as an organizational priority and developing a robust strategy. Critically, efforts will be more likely to succeed if they extend beyond a clinical setting and address SDoH in your local communities. That said, cultivating a culture around health equity and executing on an equity-centered initiative is challenging. Fortunately, The Institute for Healthcare Improvement has outlined five ways to make health equity a core strategy:
Developing a strategy that adheres to these five actions will foster more equitable health outcomes and will help to ensure that the pursuit of equity remains a central focus.
How to Measure and Mitigate Algorithmic Bias in Healthcare
Amidst an ever-growing torrent of available data in healthcare and the shift to value-based care, artificial intelligence (AI) and machine learning (ML) increasingly play a central role. Instead of treating patients as adverse events and complications occur, HCOs are beginning to anticipate the future and working proactively to prevent these events and improve outcomes. AI/ML is essential to preemptively surface high-risk patients, predict exactly what they’re at risk of and why (e.g., an unplanned admission due to COPD exacerbation), and help care teams target interventions efficiently.
AI/ML helps HCOs identify and combat disparities, advancing health equity with more efficient resource allocation, reduced spending, and improved outcomes. However, if algorithms are biased, the AI solutions designed to improve care and equity can end up making things worse.
High-profile cases of algorithmic bias have directly propagated racial health disparities. Optum’s algorithm managed 70 million lives and did not account for race—ultimately disadvantaging and producing worse outcomes for Black members while prioritizing White members for care and special programs, despite being less sick than Black members on average.
Ensuring Unbiased, Fair AI
Fortunately, algorithmic bias in healthcare is by no means inevitable, and organizations are taking major steps to ensure AI is unbiased, fair, and explainable. The University of Chicago Booth School of Business has developed a playbook to guide HCOs and policy leaders on defining, measuring, and mitigating bias. HCOs should strive to:
If you’re interested in eliminating health disparities, excelling in CMS’s alternative payment models that prioritize health equity, and tackling SDoH gaps with unbiased AI, we’re here to help.
ClosedLoop provides an end-to-end, healthcare-specific machine learning platform and pre-built content library that enables HCOs to quickly produce predictive models customized to their specific populations and available data sources. By accurately predicting which people are at highest risk of potentially preventable negative outcomes, ClosedLoop can help you target care management or other human-led interventions more efficiently and effectively, potentially reducing disparities and leading to better, more equitable outcomes at lower costs.