Changes in the availability of screening mammography, 2000-2010

Social Determinants of Health in Imaging-based Cancer Screening: A Case-based Primer with Strategies for Care Improvement

Health disparities, preventable differences in the burden of disease and disease outcomes often experienced by socially disadvantaged populations, can be found in nearly all areas of radiology, including emergency radiology, neuroradiology, nuclear medicine, image-guided interventions, and imaging-based cancer screening. Disparities in imaging-based cancer screening are especially noteworthy given the far-reaching population health impact. The social determinants of health (SDoH) play an important role in disparities in cancer screening and outcomes. Through improved understanding of how SDoH can drive differences in health outcomes in radiology, radiologists can effectively provide patient-centered, high-quality, and equitable care. Radiologists and radiology practices can become active partners in efforts to assist patients along their imaging journey and overcome existing barriers to equitable cancer screening care for traditionally marginalized populations. As radiology exists at the intersection of diagnostic imaging, image-guided diagnostic intervention, and image-guided treatment, radiologists are uniquely positioned to design these strategies. Cost-effective and socially conscious strategies that address barriers to equitable care can improve both public health and equitable health outcomes. Potential strategies include championing supportive health policy, reducing out-of-pocket costs, increasing price transparency, improving education and outreach efforts, ensuring that appropriate language translation services are available, providing individualized assistance with appointment scheduling, and offering transportation assistance and childcare. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Changes in geographic accessibility to mammography by state and rural-urban status, United States, 2006-2022

Although mammography is widely available in the United States, differences in accessibility in rural and urban areas and changes over time are not well described. In this study, we estimated the number and proportion of women aged 45-84 years who had limited travel time-based geographic accessibility to mammography by urban-rural status and state in the contiguous United States in 2006 and 2022. The proportion of women aged 45-84 years with limited accessibility to mammography did not substantially change from 2006 (12.7%; representing 7.5 million women) to 2022 (12.2%; 8.2 million women). Accessibility to mammography varied by state, but in 10 states, more than 26% of the statewide female population aged 45-84 years had limited accessibility in 2022. This proportion was substantially higher in rural areas (50.6% overall; ≥50% in 28 states in 2022) than in urban areas (3.0% overall). Increasing accessibility to mammography could increase utilization of breast cancer screening and, potentially, improve breast cancer survival.

Coverage determinants of breast cancer screening in Flanders: an evaluation of the past decade

Background

Breast cancer (BC) is the most common cancer in women in the developed world. In order to find developing cancers in an early stage, BC screening is commonly used. In Flanders, screening is performed in and outside an organized breast cancer screening program (BCSP). However, the determinants of BC screening coverage for both screening strategies are yet unknown.

Objective

To assess the determinants of BC screening coverage in Flanders.

Methods

Reimbursement data were used to attribute a screening status to each woman in the target population for the years 2008–2016. Yearly coverage data were categorized as screening inside or outside BCSP or no screening. Data were clustered by municipality level. A generalized linear equation model was used to assess the determinants of screening type.

Results

Over all years and municipalities, the median screening coverage rate inside and outside BCSP was 48.40% (IQR: 41.50–54.40%) and 14.10% (IQR: 9.80–19.80%) respectively. A higher coverage rate outside BSCP was statistically significantly (P < 0.001) associated with more crowded households (OR: 3.797, 95% CI: 3.199–4.508), younger age, higher population densities (OR: 2.528, 95% CI: 2.455–2.606), a lower proportion of unemployed job seekers (OR: 0.641, 95% CI: 0.624–0.658) and lower use of dental care (OR: 0.969, 95% CI: 0.967–0.972).

Conclusion

Coverage rate of BC screening is not optimal in Flanders. Women with low SES that are characterized by younger age, living in a high population density area, living in crowded households, or having low dental care are less likely to be screened for BC in Flanders. If screened, they are more likely to be screened outside the BCSP.

The Effect of Digital Breast Tomosynthesis Adoption on Facility-Level Breast Cancer Screening Volume

OBJECTIVE

The purpose of this study was to determine whether digital breast tomosynthesis (DBT) adoption was associated with a decrease in screening mammography capacity across Breast Cancer Screening Consortium facilities, given concerns about increasing imaging and interpretation times associated with DBT.

SUBJECTS AND METHODS

Facility characteristics and examination volume data were collected prospectively from Breast Cancer Screening Consortium facilities that adopted DBT between 2011 and 2014. Interrupted time series analyses using Poisson regression models in which facility was considered a random effect were used to evaluate differences between monthly screening volumes during the 12-month preadoption period and the 12-month postadoption period (with the two periods separated by a 3-month lag) and to test for changes in month-to-month facility-level screening volume during the preadoption and postadoption periods.

RESULTS

Across five regional breast imaging registries, 15 of 83 facilities (18.1%) adopted DBT for screening between 2011 and 2014. Most had no academic affiliation (73.3% [11/15]), were nonprofit (80.0% [12/15]), and were general radiology practices (66.7% [10/15]). Facility-level monthly screening volumes were slightly higher during the postadoption versus preadoption periods (relative risk [RR], 1.09; 95% CI, 1.06-1.11). Monthly screening volumes remained relatively stable within the preadoption period (RR, 1.00 per month; 95% CI 1.00-1.01 per month) and the postadoption period (RR, 1.00; 95% CI, 1.00-1.01 per month).

CONCLUSION

In a cohort of facilities with varied characteristics, monthly screening examination volumes did not decrease after DBT adoption.

Geographic access to mammography facilities and frequency of mammography screening

PURPOSE

To assess the association between geographic access to mammography facilities and women's mammography utilization frequency.

METHODS

Using data from the population-based 1995-2007 Wisconsin Women's Health study, we used proportional odds and logistic regression to test whether driving times to mammography facilities and the number of mammography facilities within 10 km of women's homes were associated with mammography frequency among women aged 50-74 years and whether associations differed between Rural-Urban Commuting Areas and income and education groups.

RESULTS

We found evidence for nonlinear relationships between geographic access and mammography utilization (nonlinear effects of driving times and facility density, P-values .01 and .005, respectively). Having at least one nearby mammography facility was associated with greater mammography frequency among urban women (1 vs. 0 facilities, odds ratio 1.26, 95% confidence interval, 1.09-1.47), with similar effects among rural women. Adding more facilities had decreasing marginal effects. Long driving times tended to be associated with lower mammography frequency. We found no effect modification by income, education, or urbanicity. In rural settings, mammography nonuse was higher, facility density smaller, and driving times to facilities were longer.

CONCLUSIONS

Having at least one mammography facility near one's home may increase mammography utilization, with decreasing effects per each additional facility.

Effect of Population Socioeconomic and Health System Factors on Medical Care of Childhood Cancer Survivors: A Report from the Childhood Cancer Survivor Study

PURPOSE

To determine the independent contribution of population socioeconomic and health system factors on childhood cancer survivors' medical care and screening.

METHODS

7899 childhood cancer survivors in the United States and Canada enrolled in the Childhood Cancer Survivor Study (CCSS). Population-level factors were derived from U.S. Area Health Resource File or 201 Canadian Census. Health service utilization and individual-level factors were self-reported. Multivariable logistic regression was used to calculate the effect of population factors on medical care (any care vs. no care; risk-based care vs. general care) and indicated echocardiogram or mammogram, adjusting for individual sociodemographic and health status.

RESULTS

After adjusting for individual factors, population factors had a nominal impact on childhood cancer survivors' medical care and screening. Higher population median income was associated with risk-based survivor-focused care versus general care (odds ratio [OR] 1.05, 95% confidence interval [CI], 1.01-1.09) among all participants, but not among U.S. residents only (OR 1.03, 95% CI, 0.99-1.07). For U.S. residents, the number of CCSS centers within the geographic area was associated with greater odds of receiving risk-based survivor-focused medical care (OR 1.12, 95% CI, 1.04-1.20). Areas with higher median income had higher rates of echocardiogram screening among survivors at risk of cardiomyopathy (for every $10,000 increase in median income, there is a 12% increase in odds of echocardiogram screening; 95% CI 1.05-1.20). A positive relationship was identified between greater number of physicians and surgeons in the county of residence and recommended echocardiogram (for every additional 1000 physicians and surgeons: OR 1.12, 95% CI, 1.01-1.23). We found no association between population-level factors and mammography screening.

CONCLUSIONS

Population socioeconomic disparities moderately affect childhood cancer survivors' risk-based medical care and screening after accounting for individual sociodemographic and health factors.

The impact of Medicare eligibility on cancer screening behaviors

INTRODUCTION

Lack of health insurance limits access to preventive services, including cancer screening. We examined the effects of Medicare eligibility on the appropriate use of cancer screening services in the United States.

METHODS

We performed a cross-sectional analysis of the 2012 Behavioral Risk Factor and Surveillance System (analyzed in 2014). Univariable and logistic regression analyses were performed for participants aged 60-64 and 66-70 to examine the effects of Medicare eligibility on prevalence of self-reported screening for colorectal, breast, and prostate cancers. Sub-analyses were performed among low-income (<$25,000 annual/household) individuals.

RESULTS

Medicare-eligible individuals were significantly more likely to undergo all examined preventive services (colorectal cancer OR: 1.90; 95% CI 1.79-2.04; prostate cancer OR: 1.29; 95% CI 1.17-1.43; breast cancer OR: 1.23; 95% CI 1.10-1.37) and the effect was most pronounced among low-income individuals (colorectal cancer OR: 2.04; 95% CI 1.8-2.32; prostate cancer OR: 1.39; 95% CI 1.12-1.72; breast cancer OR: 1.42, 95% CI 1.20-1.67). Access to a healthcare provider was the strongest independent predictor of undergoing appropriate screening, ranging from OR 2.73 (95% CI 2.20-3.39) for colorectal cancer screening in the low-income population to OR 4.79 (95% CI 3.95-5.81) for breast cancer screening in the overall cohort. The difference in screening prevalence was most pronounced when comparing Medicare-eligible participants to uninsured Medicare-ineligible participants (+33.2%).

CONCLUSIONS

Medicare eligibility impacts the prevalence of cancer screening, likely as a result of increased access to primary care. Low-income individuals benefit most from Medicare eligibility. Expanded public insurance coverage to these individuals may improve access to preventive services.

Travel by public transit to mammography facilities in 6 US urban areas

We examined lack of private vehicle access and 30 minutes or longer public transportation travel time to mammography facilities for women 40 years of age or older in the urban areas of Boston, Philadelphia, San Antonio, San Diego, Denver, and Seattle to identify transit marginalized populations - women for whom these travel characteristics may jointly present a barrier to clinic access. This ecological study used sex and race/ethnicity data from the 2010 US Census and household vehicle availability data from the American Community Survey 2008-2012, all at Census tract level. Using the public transportation option on Google Trip Planner we obtained the travel time from the centroid of each census tract to all local mammography facilities to determine the nearest mammography facility in each urban area. Median travel times by public transportation to the nearest facility for women with no household access to a private vehicle were obtained by ranking travel time by population group across all U.S. census tracts in each urban area and across the entire study area. The overall median travel times for each urban area for women without household access to a private vehicle ranged from a low of 15 minutes in Boston and Philadelphia to 27 minutes in San Diego. The numbers and percentages of transit marginalized women were then calculated for all urban areas by population group. While black women were less likely to have private vehicle access, and both Hispanic and black women were more likely to be transit marginalized, this outcome varied by urban area. White women constituted the largest number of transit marginalized. Our results indicate that mammography facilities are favorably located for the large majority of women, although there are still substantial numbers for whom travel may likely present a barrier to mammography facility access.

The Urban/Rural Dichotomy in the Distribution of Breast Cancer across Pennsylvania

Breast cancer rates clearly differ across the United States. This is due to a variety of factors, but at least one determinant is the population density. Breast cancer detection rates and treatment paradigms may differ in rural areas when compared with more urban ones. As the population becomes more mobile and diffuse, this may or may not be a worsening problem. The current analysis was undertaken to examine the breast cancer incidence and outcomes in a single state in an attempt to plan for resource allocation in the future. A retrospective analysis was performed using data available from the Pennsylvania Department of Health regarding breast cancer rates by county, the distribution of cases with regard to degree of rurality, death rates by county as a function of rurality, and the age distribution of all presenting cases. Data from 1999 were compared with those of 2009. The United States Census Bureau definition of rurality was used, which specifies that a county be classified as rural if the population density is less than 284 persons/square mile. Between 1999 and 2009, the population of Pennsylvania increased by approximately 3.4 per cent (421,325 people). The urban population increased by 3.9 per cent, whereas the rural population increased by only 2.2 per cent. During that same period, the number of cancer cases/100,000 population remained about the same: 391.41 in 1999; 390.7 in 2009. However, the distribution of cases shifted during that time toward more rural areas of the state: in 1999, there were 372.3 breast cancer cases/100,000 population compared with 2009 when the rate was 384.4/100,000 population. The number of cancer deaths/100,000 population actually dropped overall during the decade: 98.5 in 1999 versus 82.3 in 2009. Though this was true in both urban and rural counties, the decrease was much less pronounced in the rural areas. In urban counties, the death rate dropped from 100.5 to 81.5/100,000 population, whereas in rural counties, the drop was only from 93.3 to 84.3. The greater increase in cases diagnosed in rural areas of Pennsylvania is only partially explained by the relatively greater increase in rural population. There are undoubtedly other issues at work in rural areas: environmental factors, diffusion of resources, less access to surveillance programs. In addition, though the death rate has dropped in both rural and urban areas, this is much less pronounced in rural counties. Coupled with the increase in prevalence in those areas, this suggests that breast cancer care may be lagging in rural areas. There is a need to examine allocation of resources and surveillance programs.

Advanced Breast Imaging Availability by Screening Facility Characteristics

RATIONALE AND OBJECTIVES

To determine the relationship between screening mammography facility characteristics and on-site availability of advanced breast imaging services required for supplemental screening and the diagnostic evaluation of abnormal screening findings.

MATERIALS AND METHODS

We analyzed data from all active imaging facilities across six regional registries of the National Cancer Institute-funded Breast Cancer Surveillance Consortium offering screening mammography in calendar years 2011-2012 (n = 105). We used generalized estimating equations regression models to identify associations between facility characteristics (eg, academic affiliation, practice type) and availability of on-site advanced breast imaging (eg, ultrasound [US], magnetic resonance imaging [MRI]) and image-guided biopsy services.

RESULTS

Breast MRI was not available at any nonradiology or breast imaging-only facilities. A combination of breast US, breast MRI, and imaging-guided breast biopsy services was available at 76.0% of multispecialty breast centers compared to 22.2% of full diagnostic radiology practices (P = .0047) and 75.0% of facilities with academic affiliations compared to 29.0% of those without academic affiliations (P = .04). Both supplemental screening breast US and screening breast MRI were available at 28.0% of multispecialty breast centers compared to 4.7% of full diagnostic radiology practices (P < .01) and 25.0% of academic facilities compared to 8.5% of nonacademic facilities (P = .02).

CONCLUSIONS

Screening facility characteristics are strongly associated with the availability of on-site advanced breast imaging and image-guided biopsy service. Therefore, the type of imaging facility a woman attends for screening may have important implications on her timely access to supplemental screening and diagnostic breast imaging services.

Regional variation in mammography use among insured women 40-49 years old: impact of a USPSTF guideline change

PURPOSE

The impact of the US Preventive Services Task Force (USPSTF) recommendation that 40-49 year old women should no longer routinely receive screening mammography in November 2009 in different regions of the US is unknown.

METHODS

We conducted a retrospective cohort study using medical claims from administrative health records from privately insured 40-59 year old women enrolled between 2005 and 2012 to evaluate biennial screening trends.

RESULTS

There was a slight decrease in mammography usage among 40-49 year old US women after the 2008-2009 biennial period (p<0.001). There were some regional differences in mammography trends, with the West showing the greatest difference in odds of 40-49 year olds receiving a mammography in 2011-2012 compared to 2008-2009 (OR: 0.93; 95% CI: 0.91-0.94). Although trends for 50-59 year olds mirrored that of 40-49 year olds, the younger age group had a stronger decline in 2009-2010 and 2010-2011.

CONCLUSIONS

These findings show that USPSTF guideline changes made some differences in mammography usage among 40-49 year olds, but adherence was uneven across regions.

Continuum of mammography use among US women: classification tree analysis

OBJECTIVES

To identify women with low mammography utilization.

METHODS

We used Classification Tree Analysis among women aged 42-80 from the 2008 Behavioral Risk Factor Surveillance System (N = 169,427) to identify sub-groups along a continuum of screening.

RESULTS

Women with neither a primary care provider nor health insurance had the lowest utilization (33.9%) and were 2.8% of the sample. Non-smoking women aged 55-80, with a primary care provider, health insurance, and income of $75,000 or more had the highest utilization (90.7%) and comprised 5% of the sample.

CONCLUSION

As access to primary care providers and health insurance increases with the Affordable Care act, classification tree analyses may help to identify women of high priority for intervention.