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Claude Louis-Charles
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AI Impact on Health and Data Equity in Underserved Communities Overview of Social Determinants of Health (SDOH) and Health Related Social Needs (HRSN) and its Challenges
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Publishdrive
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9781972752371
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1
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CHF 7.40
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325
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DRM
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PC/MAC/eReader/Tablet
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ePUB
AI Impact on Health and Data Equity in Underserved Communities is a timely and essential exploration of how artificial intelligence is reshaping health outcomes, data access, and social equity for America's most vulnerable populations. As the book notes,'AI is considered a double-edged sword,' capable of both widening and narrowing the gaps in health and opportunity. This comprehensive guide helps readers understand that duality-and shows how AI can be used responsibly to uplift communities that have historically been overlooked.
Drawing from national statistics, public health research, and real-world case studies, the book uncovers the true landscape of poverty and disadvantage in the United States. It challenges common assumptions about who the underserved really are, revealing that many of the most disadvantaged communities are rural, geographically isolated, and often white, despite public narratives that focus primarily on urban minority populations. Through detailed analysis of Social Determinants of Health (SDOH) and Health-Related Social Needs (HRSN), the book explains how structural, systemic, and social forces shape health disparities long before a patient enters a clinic.
The book also examines how AI can either reinforce or reduce inequities depending on how it is designed, trained, and deployed. Readers will learn how data inequality, biased algorithms, and limited digital access can worsen health outcomes-but also how AI-driven tools, when responsibly implemented, can improve care coordination, enhance early detection, support mental health interventions, and strengthen community-based health strategies. Special attention is given to Microsoft AI and cloud technologies that can help close gaps in data quality, access, and representation.
From metabesity and mental health disparities to precision health, community partnerships, and ethical AI governance, this book provides a holistic roadmap for using technology to advance equity rather than deepen divides. Whether you are a healthcare leader, policymaker, technologist, or community advocate, this book offers the insight and clarity needed to ensure AI becomes a force for fairness, dignity, and improved health outcomes for all.
Chapter 2 The Truth about Poverty in America
Although the definition of underserved communities has not been contested in many statistical references and comprises most racial and gender minorities, a closer and thorough investigation reveals that these people are not always the obvious people of color in the urban inner cities. Defining underserved communities is challenging because it varies depending on contextual factors, even though the underlying conception still prevails. For instance, the Federal Emergency Management Agency (FEMA) defines underserved populations as those who lack access to resources or are otherwise disenfranchised. Federal Emergency Management Agency definition includes socio-economically disadvantaged, ethnic and national origin minorities, people who experience geographical isolation, cannot speak and/or understand English, women and children, people with disabilities, and older adults. The US Housing and Urban Development (HUD) Office considers underserved communities as individuals who are denied the opportunity to participate in economic, social, and civic life. The analysis of the statistics on the levels of disenfranchisement across these disparate groups paints a picture that deviates from the assumptions about who underserved communities are and where they are. According to the US Office of Personnel Management (OPM) 2022 Census statistics, poverty in America can be assessed using the overall poverty rate and its prevalence across racial, ethnic, age, gender, and disability demarcations. This paper will leverage these statistical figures and maps to demonstrate that the truly underserved communities are actually white (non-Hispanic) individuals living in the Southern Sunbelt.
Who are They? The outward signs of underserved communities are illusions because individuals often simultaneously belong to more than one disenfranchised group, meaning the need to assess the statistical figures to uncover the truly underserved people. When determining who the underserved people are, one must assess the characteristics, numbers, and percentages of people in poverty (which is a determinant of the levels of disenfranchisement). The characteristics include race and hispanic origin, age, nativity, and disability status.
Race and Hispanic Origin According to the latest census statistics on the rate of poverty in America, white (not Hispanic) people are the most numerically living in poverty, followed by Blacks, Asians, American Indians, Alaska Natives, and Hispanics, respectively (See Figure 3). The census shows that 16.7 million Whites (not Hispanics) live below the poverty line, which is exponentially more than the other races. However, as a percentage of the total population, poverty is more prevalent among American Indians at 25%, even though this comprises about 1 million people (Slagter, 2020). Nevertheless, since most Native Americans are fewer than the other races and live on the reservations, they are not as visible as the 7.1 million African Americans living below the poverty line (Slagter, 2020). The visibility of underserved communities is often associated with the African American and Hispanic races, whereby approximately 17% of their population lives in poverty. Asians had the second lowest number of people living in poverty, representing 8.6% of its population, which makes the race less visible as an underserved community (Slagter, 2020). Therefore, the largest group (by sheer numbers) of disadvantaged is white people living in poverty, and a significant percentage of American Indians are socio-economically disadvantaged; Hispanics and African Americans are the apparent embodiments of underserved communities in America.
Age The American census categorizes poverty into three age groups: children (under 18 years), adults (18 to 64 years), and older adults (65 years and above) to determine different disenfranchisement levels. Although the census statistics show that most adults, 21 million, live in poverty, 15% of children live in poverty. Similarly, 10% of older adults experience significant economic disadvantages, which makes it an underserved community in healthcare because they are more vulnerable and susceptible to medical conditions like heart disease. Although children and older adults are relatively fewer than adults, they are more likely to be considered underserved because poverty exposes them to adverse health outcomes. Therefore, children are more likely to be considered an underserved community because a significant percentage lives below the poverty line.
Nativity Native-born and foreign-born in America is a significant determinant that differentiates people living in poverty because national policies tend to favor their citizens over immigrants and visitors. Although about 31 million native-born residents live in poverty, 14 percent of the 6.9 million foreign-born residents are economically disadvantaged. Of the foreign-born residents, 18.8% of those without