Observational studyCancer2025
An analysis of multilevel factor contributions to breast cancer screening inequities in an academic health system.
Observational study in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- How and Under What Conditions Do Patient Portals Improve Cancer Screening Completion: A Scoping Review.AJPM focus · 2026Review
- A randomized factorial experiment to optimize the design of a culturally tailored breast cancer screening outreach chatbot intervention.Frontiers in digital health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundBreast cancer screening (BCS) inequities are evident at national and local levels, and many health systems want to address these inequities, but may lack data about contributing factors. The objective of this study was to inform health system interventions through an exploratory analysis of potential multilevel contributors to BCS inequities using health system data.
methodsThe authors conducted a cross-sectional analysis within a large academic health system including 19,774 individuals who identified as Black (n = 1445) or White (n = 18,329) race and were eligible for BCS. They evaluated individual-level, provider-level, and clinic-level factors. They conducted logistic regression and Blinder-Oaxaca (BO) decomposition analyses to quantitatively estimate the contribution of factors to the mean difference in BCS outcomes between the two racialized groups. They calculated average marginal effects (AME) for the logistic regression models representing the estimated additive probability of receiving BCS in the Black versus White group.
resultsBCS was completed in 63.7% of Black and 71.7% of White individuals (AME, -0.08; 95% confidence interval (CI), -0.10 to -0.04; p < .001). In the BO decomposition, observed factors explained 13.3% difference in BCS. Lower patient portal use among Black versus White patients had the greatest estimated contribution to the BCS inequity (4.6 percentage points; 95% CI, 3.0-6.2).
conclusionRacialized group differences in patient portal use had the greatest estimated contribution to the explained difference in BCS between Black and White individuals. Patient portal use promotion could be considered as a part of multifaceted health system efforts to address BCS inequities.
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What OpenQuestion holds
Registered trials
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.