Breast Cancer Screening and Outcomes Disparities Persist for Native American Women

Abstract

Over the past three decades, mortality rates from breast cancer have decreased for multiple racial groups but have remained constant for American Indian and Alaskan Native (AI/AN) women. Additionally, AI/AN women are less likely to receive timely breast cancer screening and are more likely to be diagnosed with advanced stage breast cancer at younger ages than their White counterparts. These disparities can be explained, in part, by the unique barriers to accessing care faced by AI/AN women. The Indian Health Service provides care to many AI/AN patients; however, their scope of practice is limited, and the service is chronically underfunded, leaving many women without appropriate and timely care. Additionally, geographic access to care is limited because of the sparsity of clinics and limited transportation resources. American Indian and Alaskan Native patients also harbor a history of mistrust in health care systems, and there is a paucity of culturally sensitive education regarding the importance of screening. There have been some grassroots efforts to address these barriers; however, large-scale coordinated efforts are lacking. In order to provide equitable breast health care, more awareness and widescale initiatives are needed and can be championed by breast radiologists.

Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race

“…This is important for the trustworthy and ethical use of such AI technology, and an important finding in the context of recent concerns that AI may amplify health disparities 37 – 39 . Previous studies have shown disparities in the provision of breast cancer care related to race, ethnicity, and other demographic characteristics 40 – 43 . Here, an automated, objective method for breast density prediction could alleviate some of these disparities, for example, when assessing personalised cancer risk.…”

BC2NetRF: Breast Cancer Classification from Mammogram Images Using Enhanced Deep Learning Features and Equilibrium-Jaya Controlled Regula Falsi-Based Features Selection

“…Compared to other cancer types, breast cancer has the highest probability of being treated (around 90%). Cancer does not produce early pain, so it is not noticed until serious health issues arise [ 6 ]. Age is a factor in both breast cancer mortality and incidence rates.…”

Breast cancer screening attitudes, beliefs, and behaviors of Zuni Pueblo women: identifying cornerstones for building effective mammogram screening intervention programs

“…AI/AN populations are entitled by treaty to receive healthcare free of charge provided by the US federal government, which for most is healthcare provided by the Indian Health Service (IHS). This universal health care coverage does not result in easily accessible health care services in many cases [ 12 ]. Challenges to health care access through the IHS stem from several factors including underfunding, geographic sparsity, and historic trauma leading to current mistrust [ 12 ].…”

“…This universal health care coverage does not result in easily accessible health care services in many cases [ 12 ]. Challenges to health care access through the IHS stem from several factors including underfunding, geographic sparsity, and historic trauma leading to current mistrust [ 12 ]. While AI/AN populations are entitled to healthcare, the federal funding is insufficient for addressing comprehensive healthcare needs.…”

“…An additional challenge for the AI/AN population in accessing care is geography. While there are over 300 IHS primary health clinics, there are only 46 IHS hospitals, and not all hospitals provide specialty care services [ 12 ]. This means that in many cases AI/AN patients and caretakers must travel long distances to receive specialty healthcare services, such as mammograms.…”