Evidence map›Paper›PMID 37293106›Full record

ArticleResearch square2023

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

David Haynes, Kelly D Hughes, Maria Borerro, McKenna Haas, Lauren Roach, Anne Blaes

Abstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

David HaynesUniversity of Minnesota.
Kelly D HughesMinnesota Department of Health.
Maria BorerroUniversity of Minnesota.
McKenna HaasUniversity of Minnesota.
Lauren RoachUniversity of Minnesota.
Anne BlaesUniversity of Minnesota.

Funding

Adaptive Interventions for Smoking Cessation in Lung Cancer Screening ProgramsR01CA196873 · NCI · UNIVERSITY OF MINNESOTA · PI JOSEPH, ANNE · 2015 to 2019
$3.4M
NCI NIH HHS R01 CA196873
6 · The paper itself

Abstract

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.

Identifiers

PMID37293106
PMCPMC10246289

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.