An analysis of multilevel factor contributions to breast cancer screening inequities in an academic health system

Background Breast 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...

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Bibliographic Details
Published in:Cancer Vol. 131; no. 3; pp. e35734 - n/a
Main Authors: Marcotte, Leah M., Khor, Sara, Reddy, Ashok, Morenz, Anna, Nelson, Karin, Akinsoto, Nkem, Lee, E. Sally, Onstad, Susan, Wong, Edwin S.
Format: Journal Article
Language:English
Published: United States Wiley Subscription Services, Inc 01.02.2025
Subjects:
Academic Medical Centers
Adult
Aged
Black or African American - statistics & numerical data
Breast cancer
breast cancer screening
Breast Neoplasms - diagnosis
Breast Neoplasms - ethnology
Cancer screening
Confidence intervals
Cross-Sectional Studies
Data analysis
Decomposition
Early Detection of Cancer - statistics & numerical data
Female
health equity
Healthcare Disparities - ethnology
Healthcare Disparities - statistics & numerical data
Humans
Logistic Models
Medical screening
Middle Aged
primary care
Regression analysis
Regression models
Statistical analysis
Web portals
White - statistics & numerical data
health equity
primary care
breast cancer screening
ISSN:0008-543X, 1097-0142, 1097-0142
Online Access:Get full text
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Summary:Background Breast 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. Methods The 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. Results BCS 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). Conclusion Racialized 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. Among individual‐, provider‐, and clinic‐level factors evaluated using health system data, differences in patient portal use had the greatest estimated contribution to breast cancer screening inequities between Black and White racialized groups.
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ISSN:0008-543X
1097-0142
1097-0142
DOI:10.1002/cncr.35734