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Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program

The mission of the National Breast and Cervical Cancer Early Detection Program’s (NBCCEDP) mission is to improve access to mammography and other health services for underserved women. Since its inception in 1991, this national program has improved breast cancer screening rates for women who are unin...

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Autores principales: Haynes, David, Hughes, Kelly D., Borerro, Maria, Haas, McKenna, Roach, Lauren, Blaes, Anne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246289/
https://www.ncbi.nlm.nih.gov/pubmed/37293106
http://dx.doi.org/10.21203/rs.3.rs-2886477/v1
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author Haynes, David
Hughes, Kelly D.
Borerro, Maria
Haas, McKenna
Roach, Lauren
Blaes, Anne
author_facet Haynes, David
Hughes, Kelly D.
Borerro, Maria
Haas, McKenna
Roach, Lauren
Blaes, Anne
author_sort Haynes, David
collection PubMed
description The mission of the National Breast and Cervical Cancer Early Detection Program’s (NBCCEDP) mission is to improve access to mammography and other health services for underserved women. Since its inception in 1991, this national program 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.
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spelling pubmed-102462892023-06-08 Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program Haynes, David Hughes, Kelly D. Borerro, Maria Haas, McKenna Roach, Lauren Blaes, Anne Res Sq Article The mission of the National Breast and Cervical Cancer Early Detection Program’s (NBCCEDP) mission is to improve access to mammography and other health services for underserved women. Since its inception in 1991, this national program 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. American Journal Experts 2023-05-16 /pmc/articles/PMC10246289/ /pubmed/37293106 http://dx.doi.org/10.21203/rs.3.rs-2886477/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Article
Haynes, David
Hughes, Kelly D.
Borerro, Maria
Haas, McKenna
Roach, Lauren
Blaes, Anne
Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title_full Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title_fullStr Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title_full_unstemmed Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title_short Estimating Uninsured and Underinsured Women Eligible for Minnesota’s Breast Cancer Screening Program
title_sort estimating uninsured and underinsured women eligible for minnesota’s breast cancer screening program
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10246289/
https://www.ncbi.nlm.nih.gov/pubmed/37293106
http://dx.doi.org/10.21203/rs.3.rs-2886477/v1
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