Patient Navigation Can Improve Breast Cancer Outcomes among African American Women in Chicago: Insights from a Modeling Study View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2022-08-08

AUTHORS

Aditya S. Khanna, Bryan Brickman, Michael Cronin, Nyahne Q. Bergeron, John R. Scheel, Joseph Hibdon, Elizabeth A. Calhoun, Karriem S. Watson, Shaila M. Strayhorn, Yamilé Molina

ABSTRACT

African American (AA) women experience much greater mortality due to breast cancer (BC) than non-Latino Whites (NLW). Clinical patient navigation is an evidence-based strategy used by healthcare institutions to improve AA women’s breast cancer outcomes. While empirical research has demonstrated the potential effect of navigation interventions for individuals, the population-level impact of navigation on screening, diagnostic completion, and stage at diagnosis has not been assessed. An agent-based model (ABM), representing 50–74-year-old AA women and parameterized with locally sourced data from Chicago, is developed to simulate screening mammography, diagnostic resolution, and stage at diagnosis of cancer. The ABM simulated three counterfactual scenarios: (1) a control setting without any navigation that represents the “standard of care”; (2) a clinical navigation scenario, where agents receive navigation from hospital-affiliated staff; and (3) a setting with network navigation, where agents receive clinical navigation and/or social network navigation (i.e., receiving support from clinically navigated agents for breast cancer care). In the control setting, the mean population-level screening mammography rate was 46.3% (95% CI: 46.2%, 46.4%), the diagnostic completion rate was 80.2% (95% CI: 79.9%, 80.5%), and the mean early cancer diagnosis rate was 65.9% (95% CI: 65.1%, 66.7%). Simulation results suggest that network navigation may lead up to a 13% increase in screening completion rate, 7.8% increase in diagnostic resolution rate, and a 4.9% increase in early-stage diagnoses at the population-level. Results suggest that systems science methods can be useful in the adoption of clinical and network navigation policies to reduce breast cancer disparities. More... »

PAGES

813-828

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11524-022-00669-9

DOI

http://dx.doi.org/10.1007/s11524-022-00669-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1150071706

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/35941401


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