Future efforts should focus on developing interventions and policies that target rural residents and lower SES areas to eliminate disparities in CRC-related outcomes.
Background Patient navigation may reduce cancer disparities associated with socioeconomic status (SES) and household factors. We examined whether these factors were associated with delays in diagnostic resolution among patients with cancer screening abnormalities and whether patient navigation ameliorated these delays. Methods We analyzed data from five of ten centers from the NCI Patient Navigation Research Program that collected SES and household data on employment, income, education, housing, marital status, and household composition. The primary outcome was time to diagnostic resolution following a cancer screening abnormality. We fit separate adjusted Cox proportional hazard models for each SES and household factor and included an interaction between that factor and intervention status. Results Among 3777 participants (n=1968 control, n=1809 navigation intervention), 91% were women, with a mean age of 44 years, and 43% were Hispanic, 28% White, and 27% African American. Within the control arm, the unemployed experienced longer time to resolution than the full-time employed (HR=0.85, p=0.02). Renters (HR=0.81, p=0.02) and those with other (i.e., unstable) housing (HR=0.60, p<0.001) had delays compared to homeowners. Never married (HR=0.70, p<0.001) and previously married participants (HR=0.85, p=0.03) had longer time to care than married participants. There were no differences in time to diagnostic resolution by any of these variables within the navigation intervention arm. Conclusions Delays in diagnostic resolution exist by employment, housing type, and marital status. Patient navigation eliminated these disparities in our study sample. Our findings demonstrate the value of providing patient navigation to patients at high risk for delays in cancer care.
Background We evaluated the efficacy of a Chicago-based cancer patient navigation program developed to increase the proportion of patients reaching diagnostic resolution and reduce the time from abnormal screening test to definitive diagnostic resolution. Methods Women with an abnormal breast (n=352) or cervical (n=545) cancer screening test were recruited for the quasi-experimental study. Navigation subjects originated from five federally qualified health center sites and one safety net hospital. Records-based concurrent control subjects were selected from 20 sites. Control sites had similar characteristics to the navigated sites in terms of patient volume, racial/ethnic composition, and payor mix. Mixed-effects logistic regression and Cox proportional hazard regression analyses were conducted to compare navigation and control patients reaching diagnostic resolution by 60 days and time to resolution, adjusting for demographic covariates and site. Results Compared to controls, the breast navigation group had shorter time to diagnostic resolution (aHR=1.65, CI=1.20–2.28) and the cervical navigation group had shorter time to diagnostic resolution for those who resolved after 30 days (aHR= 2.31, CI=1.75–3.06), with no difference before 30 days (aHR= 1.42, CI=0.83–2.43). Variables significantly associated with longer time to resolution for breast cancer screening abnormalities were being older, never partnered, abnormal mammogram and BI-RADS 3, and being younger and Black for cervical abnormalities. Conclusions Patient navigation reduces time from abnormal cancer finding to definitive diagnosis in underserved women. Impact Results support efforts to use patient navigation as a strategy to reduce cancer disparities among socioeconomically disadvantaged women.
Background: Women with breast or cervical cancer abnormalities can experience barriers to timely follow-up care, resulting in delays in cancer diagnosis. Patient navigation programs that identify and remove barriers to ensure timely receipt of care are proliferating nationally. The study used a systematic framework to describe barriers, including differences between African American and Latina women; to determine recurrence of barriers; and to examine factors associated with barriers to follow-up care. Methods: Data originated from 250 women in the intervention arm of the Chicago Patient Navigation Research Program (PNRP). The women had abnormal cancer screening findings and navigator encounters. Women were recruited from a community health center and a publicly owned medical center. After describing proportions of African American and Latina women experiencing particular barriers, logistic regression was used to explore associations between patient characteristics, such as race/ethnicity, and type of barriers. Results: The most frequent barriers occurred at the intrapersonal level (e.g., insurance issues and fear), while institutional-level barriers such as system problems with scheduling care were the most commonly recurring over time (29%). The majority of barriers (58%) were reported in the first navigator encounter. Latinas (81%) reported barriers more often than African American women (19%). Differences in race/ethnicity and employment status were associated with types of barriers. Compared to African American women, Latinas were more likely to report an intrapersonal level barrier. Unemployed women were more likely to report an institutional level barrier. Conclusion: In a sample of highly vulnerable women, there is no single characteristic (e.g., uninsured) that predicts what kinds of barriers a woman is likely to have. Nevertheless, navigators appear able to easily resolve intrapersonal-level barriers, but ongoing navigation is needed to address system-level barriers. Patient navigation programs can adopt the PNRP barriers framework to assist their efforts in assuring timely follow-up care.
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