Abstract

Black women face a 38% higher breast cancer mortality rate despite lower overall incidence. This research investigates clinical informatics as a mediator of this disparity. Analyzing 1,034 TCGA-BRCA patients, a Large Language Model (Gemini-Flash-2.0) was utilized to increase phenotypic data density from 18.5% to 50.4%. Using Inverse Probability of Treatment Weighting (IPTW), the study identifies a “Biological Trap”: 54% of patients reside in a structural “Documentation Gap,” while aggressive subtypes—prevalent in Black women—are 22 times more likely to generate discordant diagnostic data. Institutional informatics fidelity, driven by hospital site, is a primary mediator of health equity; documentation failure results in a nearly two-fold increased risk of death (OR: 1.69).

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