Special Populations and SettingsFree Access

Community Outreach in Breast Imaging: What Radiologists Can Do to Close the Gap for the Uninsured Population

Published Online:https://doi.org/10.1148/rg.230011

Abstract

After implementation of the Affordable Care Act in 2010, the uninsured population of the United States decreased significantly. As of 2022, there were approximately 26.4 million uninsured individuals in the United States. The lack of coverage and access to services disproportionally affect minority groups in the country, reflecting the influence of the social determinants of health in their uninsured status. Use of screening mammography, an effective modality that results in early detection of and decreased mortality from breast cancer, was delayed or postponed by women of all races due to lockdowns and fear during the COVID-19 pandemic. Since then, the return to mammographic screening has lagged among minorities, further increasing their disproportionate screening gap. Radiologists—and more specifically breast imagers—must recognize these issues, as people who are uninsured and part of minority groups are diagnosed with breast cancer at later stages and have higher mortality rates, less continuity of care, and overall lower survival. The purpose of this article is to familiarize radiologists with the uninsured population, explain how they are disproportionally affected by breast cancer, and propose strategies that breast imagers can pursue to improve screening access and decrease compliance gaps for this patient population.

©RSNA, 2023

See the invited commentary by Nguyen in this issue.

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Introduction

After the implementation of screening mammography in the 1980s, mortality from breast cancer decreased by 41% (1). Currently, breast cancer is the second leading cause of cancer deaths in women in the United States (2). Screening mammography is necessary for decreasing breast cancer mortality, but access to it is limited in women without health insurance coverage. Lack of coverage and limited access to health care continue to disproportionally affect distinct populations in the United States (3).

Minorities are disproportionally uninsured, with American Indians and Alaska Natives (AIANs) and people of Hispanic origin having the highest uninsured rates, potentially limiting their access to preventive services, including screening mammography (4). The lack of insurance and mammographic screening may additionally cause negative consequences in groups who are known to have an increased incidence of biologically aggressive triple-negative breast cancer, such as Black women and women of Hispanic origin (2). Additional factors, such as geographic location, socioeconomic status, and health literacy, may also affect access to quality care.

Underrepresentation of uninsured patients in clinical studies is a significant issue that limits our understanding of health disparities and impedes efforts to improve access to health care. The purpose of this article is to familiarize radiologists with breast imaging challenges faced by the uninsured population in the United States and to provide an overview of potential strategies to decrease the disproportionate screening gap affecting this patient population.

Characteristics of the Uninsured Population

According to data from the Office of Health Policy, there were approximately 26.4 million uninsured individuals in the United States as of 2022 (5). This number represents an all-time low rate of 8%, with up to 5.2 million people gaining health insurance coverage compared with the total in 2020, likely due to administrative efforts to improve access to health insurance through the Affordable Care Act and the American Rescue Plan (5). Despite this overall increased health coverage in recent years, health care disparities are still notable.

The uninsured population in the United States is primarily composed of individuals from different overlapping population groups, including racial and ethnic minorities, immigrants, individuals of low socioeconomic status, people who reside in rural geographic regions or non–Medicaid expansion states, and people with limited health literacy. These social determinants of health are interconnected and continuously aggravate each other, and in combination may affect access to screening mammography (Fig 1) (6).

Variables that affect access to screening mammography.

Figure 1. Variables that affect access to screening mammography.

Race and Ethnicity

It is important to recognize the heterogeneity of racial and ethnic groups and how available data may often obscure nuances. For example, populations defined as Asian include individuals with origins in various countries or regions (East Asia, Southeast Asia, South Asia, and the Pacific Islands). Similar observations can be made about people of Hispanic origin. Detail and granularity are often lacking in data sources for uninsured populations, limiting outcomes analyses.

Despite these limitations, it is worth noting that although an increase in insurance rates was noted across all races in 2022, AIANs, Native Hawaiians and Other Pacific Islanders, Black women, and women of Hispanic origin were disproportionately affected by a lack of insurance compared with individuals of White or Asian race (3). Uninsured rates for these groups ranged from 9.6% to 18.8%, with the highest percentages affecting AIANs and women of Hispanic origin. In contrast, White and Asian women had insurance rates of 5.7% and 5.8%, respectively (Fig 2) (3).

Uninsured population in the United States by race. Data from the U.S. Census Bureau show disparities within the underserved population in the United States. The uninsured rate is disproportionally higher in people of color, with the difference most noticeable in AIANs and people of Hispanic origin (3).

Figure 2. Uninsured population in the United States by race. Data from the U.S. Census Bureau show disparities within the underserved population in the United States. The uninsured rate is disproportionally higher in people of color, with the difference most noticeable in AIANs and people of Hispanic origin (3).

Patients in minority groups are most likely to report a lack of consistent medical providers, with as many as 42% of women of Hispanic origin reporting a lack of preventive care, as shown in an analysis performed by the Kaiser Family Foundation (KFF) (4). Lack of a primary care provider negatively affects the rate of screening mammography and diagnosis of breast cancer in early stages (7). The analysis by the KFF also revealed that 31% of AIAN women and 28% of Asian women reported not undergoing screening mammography in the past 2 years in comparison with other races and ethnicities, ranging from 15% in Black women to 22% in White women (Fig 3) (4,8).

Age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years. Chart based on 2020 data shows the age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years by race and ethnicity, with the highest rate documented in the AIAN population. Results might be affected by the impact of COVID-19 on screening mammography (4).

Figure 3. Age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years. Chart based on 2020 data shows the age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years by race and ethnicity, with the highest rate documented in the AIAN population. Results might be affected by the impact of COVID-19 on screening mammography (4).

Additionally, breast cancer mortality rates in AIAN and Asian women are increasing, which contrasts with the decreasing mortality rates in other races and ethnicities (Fig 4) (8,9). Importantly, health care programs for these groups may not specifically cover breast preventive services. For example, federally recognized tribes in the AIAN population are eligible for free health care at Indian Health Service (IHS) facilities. However, the IHS has no funding for mammography machines, and these women often receive screening services from other facilities that may be at greater distances, compromising their access and likely influencing their mortality rates (9).

Age-adjusted rate of death from breast cancer by race and ethnicity, 2013–2018. Chart shows that the rate of death from breast cancer remains the highest in black women. When compared with data from 2013, the mortality rate has increased in the AIAN population as well as in the Asian, Native Hawaiian and Pacific Islander population (8).

Figure 4. Age-adjusted rate of death from breast cancer by race and ethnicity, 2013–2018. Chart shows that the rate of death from breast cancer remains the highest in black women. When compared with data from 2013, the mortality rate has increased in the AIAN population as well as in the Asian, Native Hawaiian and Pacific Islander population (8).

Immigration Status

Although the majority of the uninsured are U.S. citizens, undocumented immigrants have a higher uninsured rate. Undocumented immigrants—including those who are foreign born and reside in the United States without authorization or those who entered the United States legally but stayed after their legal status expired—represent up to 10.5 million people (based on 2017 data) (10). Undocumented immigrants and lawfully present immigrants (with visas or green cards) have uninsured rates of 45% and 23%, respectively, compared with 8% for citizens (10).

This difference in uninsured rates between immigrants and citizens is likely secondary to limited coverage options in the undocumented population, as they often lack access to employer-sponsored insurance and may not qualify for federal health insurance programs (10). In terms of screening mammography, immigrant women are less likely than those born in the United States to report having undergone recent mammography and have a lower probability of undergoing regular mammographic screening (11).

Income Level

The Department of Health and Human Services measures income levels on a yearly basis to determine eligibility for health care benefits. These measurements are known as the Federal Poverty Level (FPL). For example, for a family of four in the year 2022, the FPL was $27 750 (12). Uninsured patients are usually of low income, below 200% of the FPL, with approximately 83% belonging to families with an income below 400% of the FPL (12). Up to 72% of uninsured patients attribute their status to unavailability of affordable coverage (4).

Research indicates that lower-income women in the United States have lower rates of mammography use than their higher-income counterparts, even after controlling for factors such as race, ethnicity, and insurance status. This disparity may be attributed to a higher likelihood of uninsured status among low-income women (13). However, a low income affects multiple additional factors besides the substandard access to quality care and lower rates of screening mammography; these patients also demonstrate additional interconnected determinants of health, such as lower patient literacy and lack of knowledge about cancer prevention and manifestation (14).

Geographic Location and Transportation Barriers

Medicaid is a program funded by the states and the federal government that provides health insurance to low-income Americans. Under the Affordable Care Act, states can opt to expand eligibility to include all individuals with incomes up to 138% of the FPL. States where Medicaid expansion was not implemented demonstrate higher uninsured rates (15). The 11 nonexpansion states have uninsured rates of 16.7%, compared with 9.0% in states with expanded Medicaid eligibility (Figs 57) (8,1618).

Medicaid expansion decisions by status of state action. Map shows the states that have or have not adopted Medicaid expansion. Medicaid expansion in South Dakota has been approved and was implemented in June 2023 (16).

Figure 5. Medicaid expansion decisions by status of state action. Map shows the states that have or have not adopted Medicaid expansion. Medicaid expansion in South Dakota has been approved and was implemented in June 2023 (16).

Percentage of population without health insurance coverage by state—2021. Map shows the percentage of the population without health insurance coverage by state in 2021, based on U.S. Census Bureau data (8).

Figure 6. Percentage of population without health insurance coverage by state—2021. Map shows the percentage of the population without health insurance coverage by state in 2021, based on U.S. Census Bureau data (8).

Age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years. Map based on 2020 Centers for Disease Control and Prevention (CDC) data shows the age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years by state. Results might be affected by the impact of COVID-19 on screening mammography (17).

Figure 7. Age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years. Map based on 2020 Centers for Disease Control and Prevention (CDC) data shows the age-adjusted prevalence in women aged 50–74 years who did not undergo mammography within the past 2 years by state. Results might be affected by the impact of COVID-19 on screening mammography (17).

As of 2021, the states with the highest uninsured rates included Texas, Oklahoma, Georgia, Wyoming, and Florida, all of which are nonexpansion states (19). Most states have had a decrease in percentage of uninsured patients in 2021 compared with in 2019. However, the District of Columbia, Rhode Island, Maryland, North Dakota, Arkansas, Alabama, and Nevada had interval increases in the percentage of patients without health insurance coverage (Table 1) (8).

Table 1: Percentage of Population without Health Insurance Coverage by State: 2019, 2021, and Interval Difference

Table 1:

In a 2018 study by Heller et al (20), the authors investigated the uptake of screening mammography in Medicare enrollees with the Atlas of Rural and Small-Town America of the U.S. Department of Agriculture. This study revealed that rates of mammographic screening were lower in rural counties and urban counties with a population of less than 20 000. Other studies have noted that travel times to breast imaging facilities are disparately longer for AIANs compared with those for other racial and ethnic groups and for rural women compared with urban women, highlighting their geographic access barriers (21).

Low rates of screening mammography can also be seen in patients in urban underserved areas or in safety-net hospitals within cities (14,22). A large proportion of women who lack adequate insurance coverage tend to use health care services provided by safety-net hospitals, which primarily serve minority patient populations. However, these health care facilities commonly encounter resource constraints, resulting in lower quality of care and higher mortality rates for uninsured and Medicaid patients (14). Kim et al (22) demonstrated that large city-level disparities in screening mammography use exist in the United States, with higher rates in coastal regions. Census division, Pap test adherence, Asian race, and private insurance were the top predictors of mammography use, accounting for 68% of the variation.

Geographic variations in use of screening mammography and outcomes from breast cancer can also be assessed based on the Area Deprivation Index (ADI). The ADI measures the social determinants of health at a neighborhood level by analyzing multiple socioeconomic variables and ranking them in comparison with the national deprivation levels (23). This measure can then be used for targeted interventions to address specific geographic challenges. For example, Anderson et al (24) noticed a strong association between breast cancer screening and area deprivation in the Appalachian region, which contributed to disparities in late-stage breast cancer diagnoses.

Patient Health Literacy, Culture, and Beliefs

Health literacy is the patient’s capacity to make proper health decisions by obtaining and understanding health information (25). Low health literacy is associated with decreased use of screening mammography, mostly due to misconceptions about mammography as well as lack of understanding of the meaning of screening and how it affects breast cancer (25).

Women who are uninsured or underinsured—in addition to being older, from lower socioeconomic backgrounds, racial or ethnic minorities, or lacking a regular source of health care—are the least likely to receive appropriate screening for breast cancer (26). Moreover, factors related to structural, interpersonal, and cultural aspects have been found to impact adherence to breast cancer screening. The lack of knowledge and cultural beliefs often increase misconceptions and concerns about the safety of mammography, causing fear, anxiety, and doubts about the efficacy of mammography (2628). Additionally, embarrassment and mistrust of doctors and the health care system may put certain groups at risk for lower compliance with screening mammography recommendations (26).

Language

Language diversity in the United States has tripled since 1980, with almost 67.8 million people speaking a language other than English in their households (29). Lack of English proficiency may limit communication between patients and their providers. A language barrier may impede navigation of the U.S. health care system; this has been shown to have a negative impact on access to treatment, patient satisfaction, and patient safety (27,30). Data have demonstrated that limited English proficiency (LEP) negatively impacts screening mammography.

Jacobs et al (31) demonstrated that non–English-speaking or LEP women of the same race or ethnicity are less likely to undergo screening mammography. The disparities observed were not explained by other factors such as sociodemographic factors, medical contact, U.S. nativity, or residency length in the United States. Similarly, a study by Cataneo et al (32) revealed that women with LEP have a lower probability of undergoing screening mammography, while also noting that Spanish-speaking LEP women are a particularly vulnerable subgroup.

Breast Cancer in the Uninsured Population

Teaching Point Certain racial groups have been shown to have worse outcomes from breast cancer. Despite having a low incidence of breast cancer, Black women, AIAN women, and women of Hispanic origin have higher mortality and lower survival rates than White women
(Figs 812) (8,14,3336). This may be due in part to distinctions in tumor biology.

Incidence and mortality rates of breast cancer by race and ethnicity. Data from the Surveillance, Epidemiology, and End Results (SEER) program show that White women have the highest incidence rates, while Black women have the highest mortality rates. The lowest mortality rates were reported in the Asian and Pacific Islander population (34).

Figure 8. Incidence and mortality rates of breast cancer by race and ethnicity. Data from the Surveillance, Epidemiology, and End Results (SEER) program show that White women have the highest incidence rates, while Black women have the highest mortality rates. The lowest mortality rates were reported in the Asian and Pacific Islander population (34).

Five-year relative survival percentages by race and ethnicity. CDC selected registries data from 2012 to 2018 show the percentage of patients surviving breast cancer 5 years after diagnosis. Asian and Pacific Islander women had the highest 5-year survival percentage of breast cancer (91.6%), followed by White women (91.2%) (8).

Figure 9. Five-year relative survival percentages by race and ethnicity. CDC selected registries data from 2012 to 2018 show the percentage of patients surviving breast cancer 5 years after diagnosis. Asian and Pacific Islander women had the highest 5-year survival percentage of breast cancer (91.6%), followed by White women (91.2%) (8).

Distribution of breast cancer cases by stage at diagnosis and by race, 2015–2019. Chart based on data from the North American Association of Central Cancer Registries (NAACCR) shows the distribution of breast cancer cases by stage at diagnosis and by race. While breast cancer is most often diagnosed in the localized stage for all races, it is diagnosed in the regional and distant stages in a higher proportion of Black women, AIAN women, and women of Hispanic origin than in White women (33).

Figure 10. Distribution of breast cancer cases by stage at diagnosis and by race, 2015–2019. Chart based on data from the North American Association of Central Cancer Registries (NAACCR) shows the distribution of breast cancer cases by stage at diagnosis and by race. While breast cancer is most often diagnosed in the localized stage for all races, it is diagnosed in the regional and distant stages in a higher proportion of Black women, AIAN women, and women of Hispanic origin than in White women (33).

Lack of insurance resulting in late presentation and delayed therapy in a 54-year-old Black woman who presented with a right breast lump for 1 year. She last underwent screening mammography 6 years earlier. (A, B) Spot compression exaggerated craniocaudal lateral (XCCL) (A) and mediolateral oblique (MLO) (B) mammograms show a 1.1-cm, irregular, high-density mass (arrow) in the right breast, anterior depth, within the axillary tail. (C) US image shows a 1.1 × 1 × 0.8-cm, hypoechoic, irregular, antiparallel mass (arrowheads) with an indistinct margin, correlating with the mammographic findings. Owing to the patient’s lack of funding and health insurance, as well as her owing a balance to the hospital, the biopsy was performed 3 months after initial mammography, revealing invasive ductal carcinoma, estrogen receptor (ER) positive, progesterone receptor (PR) positive, human epidermal growth factor receptor 2 (HER2) negative, Ki-67 score = 10%–15%. The patient required repeat diagnostic evaluation with US 8 months later due to delays in surgical intervention secondary to lack of insurance. (D) US image 8 months later shows an increase in size of the mass (arrowheads) to 1.3 cm. (E) Timeline (in months) shows delays in patient care. Note the delay in consultation despite 1 year of symptoms and inconsistent screening in this minority patient. After diagnostic examinations were ordered, more than 3 months were necessary for completion of the required examinations and diagnostic biopsy. Lack of funding and patient inability to pay delayed the scheduled biopsy, which was performed after temporary insurance was obtained. The time of diagnosis (*) was 18 months after the patient’s initial symptom. The patient lost her temporary insurance and was lost to follow-up, further delaying care. After Medicaid and a Gold Card were obtained through patient navigation, surgical treatment was performed 26 months after the initial symptom.

Figure 11. Lack of insurance resulting in late presentation and delayed therapy in a 54-year-old Black woman who presented with a right breast lump for 1 year. She last underwent screening mammography 6 years earlier. (A, B) Spot compression exaggerated craniocaudal lateral (XCCL) (A) and mediolateral oblique (MLO) (B) mammograms show a 1.1-cm, irregular, high-density mass (arrow) in the right breast, anterior depth, within the axillary tail. (C) US image shows a 1.1 × 1 × 0.8-cm, hypoechoic, irregular, antiparallel mass (arrowheads) with an indistinct margin, correlating with the mammographic findings. Owing to the patient’s lack of funding and health insurance, as well as her owing a balance to the hospital, the biopsy was performed 3 months after initial mammography, revealing invasive ductal carcinoma, estrogen receptor (ER) positive, progesterone receptor (PR) positive, human epidermal growth factor receptor 2 (HER2) negative, Ki-67 score = 10%–15%. The patient required repeat diagnostic evaluation with US 8 months later due to delays in surgical intervention secondary to lack of insurance. (D) US image 8 months later shows an increase in size of the mass (arrowheads) to 1.3 cm. (E) Timeline (in months) shows delays in patient care. Note the delay in consultation despite 1 year of symptoms and inconsistent screening in this minority patient. After diagnostic examinations were ordered, more than 3 months were necessary for completion of the required examinations and diagnostic biopsy. Lack of funding and patient inability to pay delayed the scheduled biopsy, which was performed after temporary insurance was obtained. The time of diagnosis (*) was 18 months after the patient’s initial symptom. The patient lost her temporary insurance and was lost to follow-up, further delaying care. After Medicaid and a Gold Card were obtained through patient navigation, surgical treatment was performed 26 months after the initial symptom.

Multiple variables affecting timely diagnosis and treatment in a 42-year-old Black woman with a history of HIV infection receiving highly active antiretroviral therapy (HAART) without regular medical care and without any prior mammography. She presented to the emergency department (ED) with a right breast mass, bloody nipple discharge, and nipple inversion for 1 month. Note the patient’s comorbidities and advanced symptoms. (A) Image from a US study performed in the ED shows an irregular hypoechoic mass (arrow) with an angular margin and hyperechoic rind in the right breast at the 6-o’clock position, concerning for malignancy. Breast US studies performed in the ED are challenging and often suboptimal. The patient left the ED against medical advice before the study was reported to pick up her children at the bus stop. Although an appointment was made in the breast imaging department on the following day, she missed her appointment due to lack of transportation. She was rescheduled four additional times over 2 months due to lack of transportation and lack of a support system. (B, C) Craniocaudal (B) and MLO (C) mammograms of the right breast show a conglomerate of multiple irregular masses with an obscured and spiculated margin (arrows) and associated fine heterogeneous calcifications in a segmental distribution in the area of palpable concern in the right breast. Note the trabecular thickening affecting the region (★). Prominent right axillary lymph nodes (arrowhead in C) are also noted. (D–F) US images show the mammographic masses (arrowheads in D), which are more extensive than in the original US study from the ED, as well as axillary (E) and supraclavicular (F) lymphadenopathy (★). Biopsy scheduled for the following week was delayed due to the patient returning to the ED before the biopsy with nausea and vomiting that required treatment. Biopsy was performed 4 months after the original presentation, demonstrating grade 3 invasive ductal carcinoma, ER positive, PR positive, and HER2 negative, and a right axillary node positive for metastatic disease. (G–I) Axial images from further workup with CT show osseous (G), pulmonary (H), and liver (I) metastases (arrows). (J) Images from bone scan show osseous metastatic involvement of the left clavicle, right hemipelvis and acetabulum, thoracolumbar spine, ribs, and right temporal bone. (K) Checklist highlights the multiple variables that affected this patient and her poor outcome.

Figure 12. Multiple variables affecting timely diagnosis and treatment in a 42-year-old Black woman with a history of HIV infection receiving highly active antiretroviral therapy (HAART) without regular medical care and without any prior mammography. She presented to the emergency department (ED) with a right breast mass, bloody nipple discharge, and nipple inversion for 1 month. Note the patient’s comorbidities and advanced symptoms. (A) Image from a US study performed in the ED shows an irregular hypoechoic mass (arrow) with an angular margin and hyperechoic rind in the right breast at the 6-o’clock position, concerning for malignancy. Breast US studies performed in the ED are challenging and often suboptimal. The patient left the ED against medical advice before the study was reported to pick up her children at the bus stop. Although an appointment was made in the breast imaging department on the following day, she missed her appointment due to lack of transportation. She was rescheduled four additional times over 2 months due to lack of transportation and lack of a support system. (B, C) Craniocaudal (B) and MLO (C) mammograms of the right breast show a conglomerate of multiple irregular masses with an obscured and spiculated margin (arrows) and associated fine heterogeneous calcifications in a segmental distribution in the area of palpable concern in the right breast. Note the trabecular thickening affecting the region (★). Prominent right axillary lymph nodes (arrowhead in C) are also noted. (D–F) US images show the mammographic masses (arrowheads in D), which are more extensive than in the original US study from the ED, as well as axillary (E) and supraclavicular (F) lymphadenopathy (★). Biopsy scheduled for the following week was delayed due to the patient returning to the ED before the biopsy with nausea and vomiting that required treatment. Biopsy was performed 4 months after the original presentation, demonstrating grade 3 invasive ductal carcinoma, ER positive, PR positive, and HER2 negative, and a right axillary node positive for metastatic disease. (G–I) Axial images from further workup with CT show osseous (G), pulmonary (H), and liver (I) metastases (arrows). (J) Images from bone scan show osseous metastatic involvement of the left clavicle, right hemipelvis and acetabulum, thoracolumbar spine, ribs, and right temporal bone. (K) Checklist highlights the multiple variables that affected this patient and her poor outcome.

Black women have a higher incidence of triple-negative breast cancer, higher incidence of breast cancer before the age of 50 years, and lower incidence of hormone receptor–positive tumors (37). Uninsured Black women who are diagnosed with breast cancer are more likely to die of the disease than those with insurance (38). Similarly, women of Hispanic origin often present with higher histologic grade cancers, higher stages at diagnosis, and human epidermal growth factor receptor 2 (HER2)–positive cancer types (14).

Teaching Point In addition, uninsured women are more likely to present with advanced breast cancer stages at diagnosis and have higher mortality rates, less continuity of care, and overall lower survival rates
(14).

In AIAN women, incidence rates of breast cancer vary significantly by location compared with those in White women in Alaska and the Southern plains (Kansas, Oklahoma, and Texas) (Fig 13) (8). The differences in rates for AIAN women across regions cannot be fully accounted for by variations in established breast cancer risk factors and may be explained by differences in access to health care and health behaviors (39). Additionally, in comparison with non-Hispanic White women, AIAN women are more likely to have advanced-stage disease, highlighting the necessity for investigating underlying risk factors (39).

Incidence rates in AIAN women compared with those in white women. CDC data show breast cancer incidence disparities between AIAN women and White women in each registered Indian Health Service (IHS) region. The incidence rate of breast cancer in the AIAN population is higher in certain IHS regions such as Alaska and the Southern Plains. States that have at least one Purchase/Referred Care Delivery Area (PRCDA)–designated county, grouped by IHS region, are Alaska (Alaska), Pacific Coast (California, Idaho, Oregon, and Washington), Southwest (Arizona, Colorado, Nevada, New Mexico, and Utah), Northern Plains (Indiana, Iowa, Michigan, Minnesota, Montana, Nebraska, North Dakota, South Dakota, Wisconsin, and Wyoming), Southern Plains (Kansas, Oklahoma, and Texas), and East (Alabama, Connecticut, Florida, Louisiana, Maine, Massachusetts, Mississippi, New York, North Carolina, Pennsylvania, Rhode Island, South Carolina, and Virginia) (8).

Figure 13. Incidence rates in AIAN women compared with those in white women. CDC data show breast cancer incidence disparities between AIAN women and White women in each registered Indian Health Service (IHS) region. The incidence rate of breast cancer in the AIAN population is higher in certain IHS regions such as Alaska and the Southern Plains. States that have at least one Purchase/Referred Care Delivery Area (PRCDA)–designated county, grouped by IHS region, are Alaska (Alaska), Pacific Coast (California, Idaho, Oregon, and Washington), Southwest (Arizona, Colorado, Nevada, New Mexico, and Utah), Northern Plains (Indiana, Iowa, Michigan, Minnesota, Montana, Nebraska, North Dakota, South Dakota, Wisconsin, and Wyoming), Southern Plains (Kansas, Oklahoma, and Texas), and East (Alabama, Connecticut, Florida, Louisiana, Maine, Massachusetts, Mississippi, New York, North Carolina, Pennsylvania, Rhode Island, South Carolina, and Virginia) (8).

Interventions

There are multiple evidence-bases strategies that may improve care among the uninsured.

Radiologist-Patient Interaction

Effective physician-patient communication increases rates of screening mammography (40). Breast imagers can provide value by having active conversations with patients (41). The vast majority of breast imagers have multiple occasions to communicate directly with patients while delivering test results and performing real-time US evaluations and image-guided procedures, which provide opportunities for building rapport (41,42).

This is the core concept of the Imaging 3.0 initiative of the American College of Radiology (ACR), which promotes achieving increased value in radiology while providing patient-centered care (43). Sharing health-related information with their families and communities through word-of-mouth communication is a recognized factor in patients’ health care decision-making process (44). As such, incorporating information about breast cancer screening and diagnosis during patient interaction can make a difference to the individual patient, their family, and their surrounding network (Table 2) (44).

Table 2: Interventions to Positively Influence Screening Mammography during Patient Visits

Table 2:

Radiologists should familiarize themselves with objective communication methods, such as the Standardized Kalamazoo Communication Skills Assessment Tool for Radiologists (KalRad). This tool, developed by Brown et al (45), is a modification of the Standardized Kalamazoo Communication Skills Assessment Tool tailored toward radiologists. Their study demonstrated moderate interrater reliability during the assessment of communication skills through enacted conversations about bad news, radiation risks, and diagnostic errors, which supports an objective assessment and provides guidance for communication skills training in residency and fellowship (40,45).

Educating patients with limited English proficiency (LEP) in their native language is ideal but not always possible. Trained medical interpreters are offered at no cost in federally funded clinics thanks to federal mandates (29). However, facilities without federal funding often rely on less costly alternatives, such as bilingual providers and staff, digital translators, and lay interpreters (29). Medical conversation language skills training for bilingual staff and volunteers in these facilities is a safe and cost-effective solution (29,46). Google Translate and MediBabble, accessible online translation tools, are possible solutions at no cost, but awareness of the possibility of inaccurate translations that may result in safety risks is necessary (29,30).

Teaching Point Radiologists should strive to have diversity and minority representation in their groups to help lessen some of the disparities, as patients are most likely to relate to the language and cultural beliefs of their physicians. This representation will also help alleviate unconscious bias of radiologists that negatively affects this patient population
(47,48).

Radiologist–Referring Physician Interaction

Communication between radiologists and referring physicians is challenged by the fragmentation of care of uninsured patients: imaging, diagnosis, and treatment are usually performed at separate facilities and/or local neighborhood clinics (14). By educating referring physicians, radiologists can aid in the shared decision making between these practitioners and their patients, which is especially important for patients with limited health literacy.

Understanding how uninsured patients navigate the health care system is necessary to tailor the implementation of interaction strategies between radiologists and referring physicians. Federally Qualified Health Centers (FQHCs) are federally funded clinics oriented toward the underserved communities and represent an important component of the primary care safety net in the United States (49,50). Similarly, the safety-net hospital setting is a key source of high-quality care for uninsured and underserved communities (51). Outreach and patient education strategies can be tailored toward FQHCs and safety-net hospitals with the aid of patient navigators to provide mammography education and ensure continuity of care (52). Additionally, multidisciplinary meetings in the safety-net hospital setting provide an excellent opportunity to collaborate with referring physicians and other medical specialties, improving the quality of care for these patients (48,53).

Radiologist-Community Interaction

Breast imagers can use their communication skills to reach larger populations. By understanding the needs of target audiences—in this case, the uninsured population—strategic goals, interventions, and necessary resources can be defined and set to increase the likelihood of success of community interactions (26). Partnerships with government-funded programs, hospitals, breast cancer support groups, and other organized groups can augment scope and resources, resulting in stronger outreach (26,36).

Community events are opportunities that are often available and can influence a greater number of women. By participating in local community events, such as health fairs, fundraisers, and women’s health symposiums, radiologists can educate and increase engagement of patients to be more active in their health care (48). For example, health fairs provide an opportunity for interactions outside the medical setting, where patients usually feel less anxious and open to ask important questions about their care (48). Highly religious communities may benefit from church-based health interventions, which result in an important reach (54). For example, educational church-based interventions in Black women have been shown to increase rates of screening mammography when compared with those of control groups (28).

Current contact information and previously prepared flyers during community events are necessary to ensure that potential patients have the necessary information to contact, create appointments with, and reach services during and immediately after these events. Supporting patient interest with pertinent information during these interactions is key, as education can raise awareness, but it is useless without access to services.

The Media

Health information gaps disparately affect uninsured people, and this information deprivation negatively affects health outcomes. Use of mass media in this population differs from that in the insured, as uninsured patients are more likely to use entertainment-based television than information-based media (55,56). Thus, creating strategies to appropriately reach these communities is necessary.

Television continues to be an important source of information for these patients, specifically when ethnically targeted (55). Entertainment-based education can be particularly valuable in some Hispanic communities through modeling health behaviors to those with limited health care knowledge and access (57). Narrative interventions in television programing, in which the viewers can see how others enact health behaviors, increase their health knowledge and attitudes toward such interventions. A study by Borrayo et al (58), in which a group of women of Hispanic origin were exposed to a narrative intervention versus two nonnarrative interventions (educational video and written educational material), demonstrated that although all modalities increased their understanding of breast cancer, the participants were able to identify themselves with the story character, resulting in higher motivation to engage in screening mammography.

Cancer prevention and detection activities in entertainment programs (eg, soap operas and sitcoms) can disseminate health information in a more culturally relevant manner (58,59). Radiologists should be open and prepared for media interactions and appearances, ideally if they involve television and channels tailored to these communities. Media training can provide skills and comfort during the different types of media communications, allowing the information to be delivered clearly and effectively.

The increased popularity of the internet has opened an important avenue to provide health information to the public. However, disparities in internet access across different groups exist. People of Hispanic origin and Black race have lower access compared with non-Hispanic Whites and Asians (60). Similarly, individuals in rural areas report less internet access compared with those in urban areas (60). However, up to 85% of Americans own a smartphone, and populations with low socioeconomic status—such as the uninsured—are more likely to own one and be smartphone dependent (60,61).

In terms of social networks, higher frequencies of use have been observed in minorities and those with lower education and socioeconomic status (62). This information highlights the importance of social media in the dissemination of health information for underserved communities, with the additional advantage of offering an opportunity for real-time interaction between the communicator and the recipient (62,63). By creating a social media presence, radiologists can provide educational content that can be tailored to this patient population and can also decrease misinformation (64).

Legislation

Teaching Point Physician advocacy is a necessity in the pursuit of diminishing health disparities for the uninsured communities. Radiologists are encouraged to engage in advocacy efforts, viewing it not only as a personal choice, but also as a medical responsibility
(65). By including patient advocacy in the curricula during medical education in academic institutions, the medical community can stress the importance of advocacy and ethical responsibility in future radiologists (66). Other topics—such as social determinants of health, patient-centered care, antibias, and media training—can complement the educational efforts, especially when combined and modeled by a diverse faculty group (48,6770). Breast imagers, as experts in mammography and its latest guidelines, are ideal candidates for advocating not only within their communities and institutions, but also at a political level (64).

Involvement in the radiologic societies within the different states facilitates participation of radiologists in legislative efforts aimed toward the regionally uninsured and underserved (67). Additionally, participation in national and local nonprofit organizations can further influence policymakers and aid in utilization of grants that increase fundraising efforts aimed toward this population (Table 3).

Table 3: Examples of Organized Groups for Advocacy in Breast Imaging

Table 3:

Mobile Mammography

Mobile mammography (MM) is an important method to increase services to uninsured and underserved women (71). MM not only reaches women in remote rural areas but can also address several of the social determinants of health that affect this group, such as low socioeconomic status, lack of transportation, race (women of Black and AIAN race or Hispanic origin are most likely to use these services), and those residing in rural and underserved regions (71). MM programs can be implemented based on different funding options, including grants, charity or philanthropy, and fee for service (71). Radiologists may develop MM services, as they have proved to be an effective method to reach uninsured and underserved women, especially when coupled with education programs and patient navigation (71,72).

Patient Navigation

Patient navigation emerged as a system to improve cancer outcomes by providing timely logistical and educational support to vulnerable populations (46).

Teaching Point Patient navigation services—which act as a bridge between radiologists, referring physicians, and patients—have proved to increase use of screening mammography while overcoming health barriers in the uninsured patient population
(46,73). They facilitate access to the health care system for uninsured and underserved patients by connecting them to appropriate resources based on their needs, including access to Federally Qualified Health Centers (FQHCs), resulting in improved screening compliance and decreased mortality-to-incidence ratio of breast cancer in this population (74,75). Patient navigators experienced in serving diverse populations, with familiarity with other languages besides English and knowledge of existing programs tailored to the uninsured and underserved populations, can better assist these groups (28,46).

Conclusion

Health care disparities disproportionately affect the uninsured population. Multiple interconnected variables—such as race, immigration status, income level, health literacy, culture, and geographic location—continuously influence and aggravate the inequalities affecting these patients. It is important for radiologists to recognize this population group and understand the unique barriers they face, so as to create strategies that aid in closing the disproportional gap in access to and compliance with screening mammography.

Simple daily interventions, including basic patient and referring physician interactions and greater community outreach strategies through public speaking and the media, are important measures to increase patient education. Bridging these interactions with the aid of patient navigators and increasing screening access through MM are necessary to improve screening outcomes for these patients. Radiologists must be aware of the need for diversity and minority representation within their groups to alleviate implicit bias. Additionally, radiologists’ participation in advocacy and policymaking is imperative and a medical responsibility, with potential for favorable impact on screening use and outcomes for the uninsured population.

Disclosures of conflicts of interest.—The authors, editor, and reviewers have disclosed no relevant relationships.

Acknowledgments

Dorothy Gibbons at The Rose, a nonprofit organization that provides breast imaging services to uninsured and underserved patients in Houston, Tex; Angel Su, MD; and Luis Nunez-Rubiano, MD.

Presented as an education exhibit at the 2022 RSNA Annual Meeting.

References

Article History

Received: Jan 23 2023
Revision requested: May 16 2023
Revision received: May 24 2023
Accepted: May 26 2023
Published online: Oct 04 2023