In Washington, D.C., where I live, an infant born in 2020 had an average life expectancy of 75.3 years. If you jump the border between the nation’s capital and Bethesda, Maryland, a well-heeled suburb just north of the District, life expectancy jumps to 88.3 years.
The trek from Bethesda to the Capitol is less than 10 miles, but if you are lucky enough to be born in the ‘burbs, you will live more than a decade longer, on average. The disparity is even greater when comparing the east and west sides of the capital city, with a difference in life expectancies of as much as 30 years.
Washington, D.C., is not alone. In Chicago; Buffalo, New York; Baltimore; New York City; New Orleans, and Columbus, Ohio there are 20-to-30-year differences in life expectancies between neighborhoods in the same city. This story is repeated across other cities in the U.S. as well.
This isn’t just an urban problem. Significant life expectancy disparities exist across rural regions as well, especially in the Deep South and Appalachia.
How is this possible? And why are we allowing this to happen?
Socio-political determinants contribute to these disparities, but we must dig deeper. It is true that if you are born in some parts of the nation’s capital and rural areas, you are more likely to have to deal with housing instability, food insecurity, transportation gaps, and education and economic disparities. What’s more, lower-income rural and urban communities are less likely to have the number of physicians, particularly specialists, to serve the community adequately.
Bridging the health equity gap will require a shift in incentives in the current healthcare financial system, which has often eroded access, picked winners and losers, and perpetuated biases. Our system is built on disease management instead of disease prevention, often financially rewarding those who manage illness more than those who prevent disease.
The system also bears remnants of a racist, classist, and sexist past, and we must acknowledge that those remnants still influence policy decisions today. We also must address inaccurate and inflammatory political rhetoric, diversify communication channels, and emphasize the importance of private investment. Providers, payers, business leaders, and policymakers must all actively participate in changing the system on both population and individual levels.
A daunting task? Absolutely, but it is a necessary endeavor. Here are three tools that will help us on this journey.
Data
There is a lot of talk about data-driven decision-making in population health and health equity. At the same time, there are differing viewpoints on how to measure impact in this space.
Leveraging data to evaluate outcomes from various interventions, drugs, and devices is, and will be, increasingly important for reimbursement and investment. In my class at the University of North Carolina’s Kenan-Flagler Business School, we discuss using outcomes-based pricing and real-world evidence to determine what gets produced, used, and reimbursed. Understanding population-based outcomes — whether a product or service actually works — is crucial for financial success and the health of a community.
Of course, we must also recognize that data can be biased, so we must “audit” the data.
What does this look like in practice? When Ernst & Young collaborated with a health data startup to improve understanding of chronic kidney disease (CKD), it discovered that Black CKD patients were more likely to be diagnosed in later stages of the disease, primarily because regular care was sporadic or delayed. Healthcare companies can use this model to address similar barriers specific to underserved patient populations and preventable chronic conditions. For life sciences companies, this data can enable more inclusive healthcare experiences and drive commercial excellence.
Communication and Respect
Doctors can be judgmental at times and may not always communicate effectively with patients. We are trained to process information quickly and make decisions, but individuals from marginalized groups may feel judged by their physicians.
When this occurs, they are less likely to seek care.
According to the Urban Institute’s December 2020 Well-Being and Basic Needs Survey, over three-quarters of adults (75.9%) who felt judged by their healthcare providers reported that such treatment disrupted their receipt of healthcare. This includes patients who delayed care, searched for a new provider, did not receive needed care, or did not follow doctor’s orders.
Tools like the CDC’s Health Equity Guiding Principles for Inclusive Communication assist healthcare providers in using language that respects all individuals. Additionally, the Rural Health Information Hub suggests providers:
- Use person-first language
- Avoid gender-specific terms
- Use plain language
- Avoid stereotypes and generalizations
- Be mindful of words or phrases that rank or prioritize certain groups
Private-Sector Partnerships
Expanding government programs like Medicaid is crucial for addressing health equity, as is an increase in private philanthropy and investment.
Besides healthcare corporations, the private sector has a role in improving health. As the World Economic Forum stated, “every company is a healthcare company” and can invest in enhancing health outcomes and life expectancy in their communities. A group of researchers highlighted in Harvard Business Review suggests:
- Utilizing HR teams to help employees comprehend their healthcare plans and benefits to make informed decisions
- Ensuring employer-sponsored health plans cover costs that are prohibitive for low-income families but proven to reduce health disparities
- Investing in non-traditional benefits like nutrition programs that contribute to better health outcomes
- Expanding primary care and mental health access through virtual care and community partnerships
The road to health equity is a challenging one, requiring a fundamental shift in how we structure, incentivize, and implement our healthcare system. With strong leadership, however, we can begin dismantling the entrenched disparities that can significantly impact a person’s life expectancy based on their zip code.
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