Diagnostic Resolution after Abnormal Mammograms: The Role of Contextual and Individual Factors

Advances in early detection and treatment have resulted in an overall decline in breast cancer mortality rates in the United States (U.S.) (Surveillance, Epidemiology, and End Results Program [SEER], 2015; Berry et al., 2005; American Cancer Society, 2013). Despite these advances, significant socioeconomic and racial breast cancer mortality disparities persist. Survival rates are the lowest for Black women among all racial or ethnic groups in the U.S. (SEER, 2015). Black women are more often diagnosed at a later stage of breast cancer, and as a result, face higher mortality rates relative to their white counterparts (DeSantis, Siegel, Bandi, & Jemal, 2011; DeSantis, Ma, Bryan, & Jemal, 2014). In part, late stage diagnosis in Black women has been attributed to delay in diagnostic follow-up after an abnormal mammogram result (Smith-Bindman et al., 2006; Wujcik & Fair, 2008). Despite the literature documenting diagnostic delay after abnormal mammography, very little is known and few studies have examined the relationship between contextual-level factors, individual-level factors, and timely diagnostic follow-up after abnormal mammograms (Schootman et al., 2007; Wujcik & Fair, 2008). Social work has a long and rich history of valuing and attending to the health of vulnerable populations in order to seek social justice. However, despite the efforts that date back to the 1800s to remedy conditions that lead to poor health in vulnerable populations, social and economic injustices remain determinants of poor health and health disparities (Gehlert et al., 2008). Likewise, health disparities are the result of social, economic, and environmental forces that are fundamental causes of the disparity. Today, health remains vastly different for various segments of the population. Mortality, morbidity, and well-being are determined by far more than genetics or even personal health behavior, moreover social and economic power structures of a population shape health (Marmot & Wilkinson, 2006). Conceptually, the social determinants of health expand the definition of individual health to the conditions that people are conceived and born, live, grow, develop, and age. In order for social work to adequately address health disparities the social determinants of health must be addressed. Given the holistic perspective of the profession, social workers have the expertise and training to provide leadership in addressing health disparities. In addition, social work has a unique and integral role in the U.S. health care system. Social workers contribute to scholarly research and provide services across the health care continuum (NASW, 2005). According to the National Association of Social Workers (2005), social work is committed and has a continuing focus on addressing health disparities. Addressing health disparities is a matter of social justice and social workers have an ethical obligation to contribute to the transdisciplinary efforts in finding solutions to address the ongoing health disparities in vulnerable populations. Informed by two theoretical frameworks, the model for analysis of population health and health disparities (Warnecke et al., 2008) and the Andersen behavioral model of health services use (Andersen, 1995), this study examined the relationship between multiple levels of influence, both contextual and individual, and timely diagnostic follow-up of abnormal mammograms. The study tested two hypotheses: 1) neighborhood poverty, racial residential segregation, and/or distance to mammography clinic will have a significant direct effect on diagnostic resolution; and 2) insurance status, having a usual source of healthcare, age, race/ethnicity, level of education, household income, and/or BI-RADS value (Breast Imaging Reporting and Data System value) will have a significant direct effect on diagnostic resolution. A data analysis was conducted to test the study hypotheses and assess the relationship between contextual factors and individual factors and diagnostic resolution after an abnormal mammogram. The analytic sample was a subset of women in the Patient Navigation in Medically Underserved Areas (PNMUA) a randomized, controlled trial conducted in three hospitals in Chicago, Illinois. The longitudinal data was collected from patient electronic medical records and questionnaires. Data from 690 women were used for the study analyses.  Diagnostic resolution after an abnormal mammogram was operationalized using two dependent variables, diagnostic resolution and time to diagnostic resolution. The first dependent variable, diagnostic resolution, was dichotomized as patient completed or did not complete follow-up within 60 days after an abnormal mammogram. The second dependent variable, time to diagnostic resolution, was operationalized as the number of days between an abnormal screening mammogram or diagnostic mammogram and confirmation of a definitive diagnosis, either benign or malignant, in the electronic medical record. The independent variables were contextual factors (neighborhood poverty, distance to mammography clinic, and racial residential segregation) and individual factors (insurance status, usual source of healthcare, age, race/ethnicity, level of education, BI-RADS value, and household income). The control variables were patient navigation intervention status and the hospital where women received breast care. Two statistical regression methods, binary logistic regression and Cox proportional hazards regression analyses, were used to test the study hypotheses. Results from the multivariate analyses indicated that the hospital where women received breast care, patient navigation, distance to mammography clinic, and age were associated with diagnostic resolution. Women who accessed care at Holy Cross or Roseland had longer time to diagnostic resolution compared to women accessing care at Trinity. Women in the patient navigation intervention group had shorter time to diagnostic resolution compared to women in the standard of care group. Older women also had shorter time to diagnostic resolution. In addition, living farther from the hospital mammography clinic was associated with shorter time to diagnostic resolution. Although there are limitations to the study that must be considered, findings of this study offer several important implications for research about contextual and individual factors related to timely diagnostic resolution after abnormal mammography and it builds on the seminal cancer disparities research that documents how health outcomes are related to social advantage and disadvantage. For social work practice, this study offers the opportunity to inform individual-level interventions that address the contextual environment in which women access early detection breast cancer services. This study contributes to understanding the complex interactions and multiple levels of influence impacting women accessing care in medically underserved areas that may inform policy efforts, future early detection interventions, and future directions for research.