Having health insurance does not eliminate race/ethnicity-associated delays in breast cancer diagnosis in the District of Columbia.
BACKGROUND: Delays in follow-up after breast cancer screening contribute to disparities in breast cancer outcomes. The objective of this research was to determine the impact of race/ethnicity and health insurance on diagnostic time, defined as number of days from suspicious finding to diagnostic resolution. METHODS: This retrospective cohort study of 1538 women examined for breast abnormalities between 1998-2010 at 6 hospitals/clinics in the District of Columbia measured mean diagnostic times between non-Hispanic whites (NHWs), non-Hispanic blacks (NHBs), and Hispanics with private, government, or no health insurance by using a full-factorial ANOVA model. RESULTS: Respective average--geometric mean (95% CI)--diagnostic times (in days) for NHWs, NHBs, and Hispanics were 16 (12, 21), 27 (23, 33), and 51 (35, 76) among privately insured; 12 (7, 19), 39 (32, 48), and 71 (48, 105) among government insured; 45 (17, 120), 60 (39, 92), and 67 (56, 79) among uninsured. Government insured NHWs had significantly shorter diagnostic times than government insured NHBs (P = .0003) and Hispanics (P < .0001). Privately insured NHWs had significantly shorter diagnostic times than privately insured NHBs (P = .03) and Hispanics (P < .0001). Privately insured NHBs had significantly shorter diagnostic times than uninsured NHBs (P = .03). CONCLUSIONS: Insured minorities waited >2 times longer to reach their diagnostic resolution than insured NHWs. Having private health insurance increased the speed of diagnostic resolution in NHBs; however, their diagnostic time remained significantly longer than for privately insured NHWs. These results suggest diagnostic delays in minorities are more likely caused by other barriers associated with race/ethnicity than by insurance status.
Hoffman, HJ; LaVerda, NL; Levine, PH; Young, HA; Alexander, LM; Patierno, SR; District of Columbia Citywide Patient Navigator Research Program Research Group,
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