Breast screening attendance of Aboriginal and Torres Strait Islander women in the Northern Territory of Australia

Objective: To compare breast screening attendances of Indigenous and non-Indigenous women. Methods: A total of 4,093 BreastScreen cases were used including 857 self-identified Indigenous women. Chi-squared analysis compared data between Indigenous and non-Indigenous women. Logistic regression was used for groupings based on visits-to-screening frequency. Odds ratios and 95% confidence intervals were calculated for associations with low attendance. Results: Indigenous women were younger and had fewer visits to screening compared with non-Indigenous women. Non-English speaking was mainly associated with fewer visits for Indigenous women only (OR 1.9, 95%CI 1.3-2.9). Living remotely was associated with fewer visits for non-Indigenous women only (OR 1.3, 95%CI 1.1-1.5). Shared predictors were younger age (OR 12.3, 95%CI 8.1-18.8; and OR 11.5, 95%CI 9.6-13.7, respectively) and having no family history of breast cancer (OR 2.1, 95%CI 1.3-3.3; and OR 1.8, 95%CI 1.5-2.1, respectively). Conclusions: Factors associated with fewer visits to screening were similar for both groups of women, except for language which was significant only for Indigenous women, and remoteness which was significant only for non-Indigenous women. Implications for public health: Health communication in Indigenous languages may be key in encouraging participation and retaining Indigenous women in BreastScreen; improving access for remote-living non-Indigenous women should also be addressed

Mammographic densities of Aboriginal and non-Aboriginal women living in Australia's Northern Territory

Objectives: To compare the mammographic densities and other characteristics of Aboriginal and non-Aboriginal women screened in Australia. Methods: Population screening programme data of Aboriginal (n = 857) and non-Aboriginal women (n = 3236) were used. Mann–Whitney U test compared ages at screening and Chi-square tests compared personal and clinical information. Logistic regression analysis was used for density groupings. OR and 95% CI were calculated for multivariate association for density. Results: Mammographic density was lower amongst Aboriginal women (P < 0.001). For non-Aboriginal women, higher density was associated with younger age (OR 2.4, 95% CI 2.1–2.8), recall to assessment (OR 2.2, 95% CI 1.6–3.0), family history of breast cancer (OR 1.4, 95% CI 1.2–1.6), English-speaking background (OR 1.4, 95% CI 1.2–1.6), and residence in remote areas (OR 1.2, 95% CI 1.1–1.4). For Aboriginal women, density was associated with younger age (OR 2.7, 95% CI 2.0–3.5; P < 0.001), and recall to assessment (OR 2.3, 95% CI 1.4–3.9; P < 0.05). Conclusions: Significant differences between Aboriginal and non-Aboriginal women were found. There were more significant associations for dense breasts for non-Aboriginal women than for Aboriginal women

“From the technology came the idea”: safe implementation and operation of a high quality teleradiology model increasing access to timely breast cancer assessment services for women in rural Australia

Abstract: Breast cancer is the most commonly diagnosed cancer in Australian women. Providing timely diagnostic assessment services for screen-detected abnormalities is a core quality indicator of the population-based screening program provided by BreastScreen Australia. However, a shortage of local and locum radiologists with availability and appropriate experience in breast work to attend onsite assessment clinics, limits capacity of services to offer assessment appointments to women in some regional centres. In response to identified need, local service staff developed the remote radiology assessment model for service delivery. This study investigated important factors for establishing the model, the challenges and enablers of successful implementation and operation of the model, and factors important in the provision of a model considered safe and acceptable by service providers. Methods: Semi-structured interviews were conducted with service providers at four assessment services, across three jurisdictions in Australia. Service providers involved in implementation and operation of the model at the service and jurisdictional level were invited to participate. A social constructivist approach informed the analysis. Deductive analysis was initially undertaken, using the interview questions as a classifying framework. Subsequently, inductive thematic analysis was employed by the research team. Together, the coding team aggregated the codes into overarching themes. Results: 55 service providers participated in interviews. Consistently reported enablers for the safe implementation and operation of a remote radiology assessment clinic included: clinical governance support; ability to adapt; strong teamwork, trust and communication; and, adequate technical support and equipment. Challenges mostly related to technology and internet (speed/bandwidth), and maintenance of relationships within the group. Conclusions: Understanding the key factors for supporting innovation, and implementing new and safe models of service delivery that incorporate telemedicine, will become increasingly important as technology evolves and becomes more accessible. It is possible to take proposed telemedicine solutions initiated by frontline workers and operationalise them safely and successfully: (i) through strong collaborative relationships that are inclusive of key experts; (ii) with clear guidance from overarching bodies with some flexibility for adapting to local contexts; (iii) through establishment of robust teamwork, trust and communication; and, (iv) with appropriate equipment and technical support