Since its inception in 1991, the mission of the National Breast and Cervical Cancer Early Detection Program's (NBCCEDP) mission is to improve access to mammography. This program has demonstrated evidence showing that it has improved breast cancer screening rates for women who are uninsured and underinsured. However, the literature has shown that NBCCEDP screenings are decreasing, and only reach a portion of eligible women. Reliable estimates at the sub-county level are needed to identify and reach eligible women. Our work builds upon previous estimates by integrating uninsured and insurance status into spatially adaptive filters. We use spatially adaptive filters to create small area estimates of standardized incidence ratios describing the utilization rate of NBCCEDP services in Minnesota. We integrate the American Community Survey (2010-2014) insurance status data to account for the percentage that an individual is uninsured. We test five models that integrate insurance status by age, sex, and race/ethnicity. Our composite model, which adjusts for age, sex, and race/ethnicity insurance statuses, reduces 95% of the estimation error. We estimate that there approximately 49,913.7 women eligible to receive services for Minnesota. We also create small geography (i.e., county and sub-county) estimates for Minnesota. The integration of the insurance data improved our utilization estimate. The development of these methods will allow state programs to more efficiently use their resources and understand their reach.
Keywords: Health geography; Mammography services; Prevention; Small area estimates.
© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.