Disparities in time to start of definitive radiation treatment for patients with locally advanced cervical cancer.

BACKGROUND: Chemoradiation or radiation therapy alone are curative standards for patients with locally advanced cervical cancer. OBJECTIVE: To investigate factors that influence time to initiation of chemoradiation or radiation and the subsequent impact of time to treatment on recurrence and survival outcomes. METHODS: Patients with locally advanced cervical cancer treated with definitive chemoradiation or radiation at our institution between November 2015 and August 2020 were retrospectively identified. Time to treatment initiation was defined as the number of days from date of diagnosis (via biopsy) to the start date of radiation. The cohort was stratified by the median time to treatment into early (<75 days) and delayed (≥75 days) cohorts. Multivariable logistic regression was conducted to examine factors associated with delayed time to treatment. RESULTS: We identified 143 patients with locally advanced cervical cancer who underwent definitive chemoradiation or radiation. Median follow-up time was 18 months (range 2-62). A total of 71 (49.7%) patients had time to treatment <75 days and 72 (50.3%) patients had time to treatment ≥75 days. The delayed cohort had a higher proportion of Hispanic patients (51.4% vs 31.0%, p=0.04). In multivariable modeling, Hispanic women were 2.71 times more likely (p=0.04) to undergo delayed time to treatment than non-Hispanic white women. Additionally, patients with stage >IIB disease were less likely to undergo delayed time to treatment (OR 0.26, p=0.02) than patients with stage

Disparities in telemedicine during COVID-19.

BACKGROUND: Oncology rapidly shifted to telemedicine in response to the COVID-19 pandemic. Telemedicine can increase access to healthcare, but recent research has shown disparities exist with telemedicine use during the pandemic. This study evaluated health disparities associated with telemedicine uptake during the COVID-19 pandemic among cancer patients in a tertiary care academic medical center. METHODS: This retrospective cohort study evaluated telemedicine use among adult cancer patients who received outpatient medical oncology care within a tertiary care academic healthcare system between January and September 2020. We used multivariable mixed-effects logistic regression models to determine how telemedicine use varied by patient race/ethnicity, primary language, insurance status, and income level. We assessed geospatial links between zip-code level COVID-19 infection rates and telemedicine use. RESULTS: Among 29,421 patient encounters over the study period, 8,541 (29%) were delivered via telemedicine. Several groups of patients were less likely to use telemedicine, including Hispanic (adjusted odds ratio [aOR] 0.86, p = 0.03), Asian (aOR 0.79, p = 0.002), Spanish-speaking (aOR 0.71, p = 0.0006), low-income (aOR 0.67, p < 0.0001), and those with Medicaid (aOR 0.66, p < 0.0001). Lower rates of telemedicine use were found in zip codes with higher rates of COVID-19 infection. Each 10% increase in COVID-19 infection rates was associated with an 8.3% decrease in telemedicine use (p = 0.002). CONCLUSIONS: This study demonstrates racial/ethnic, language, and income-level disparities with telemedicine use, which ultimately led patients with the highest risk of COVID-19 infection to use telemedicine the least. Additional research to better understand actionable barriers will help improve telemedicine access among our underserved populations.

Disparities in Telemedicine Utilization for Urology Patients During the COVID-19 Pandemic.

OBJECTIVE: To determine the odds of accessing telemedicine either by phone or by video during the COVID-19 pandemic. METHODS: We performed a retrospective study of patients who were seen at a single academic institution for a urologic condition between March 15, 2020 and September 30, 2020. The primary outcome was to determine characteristics associated with participating in a telemedicine appointment (video or telephone) using logistic regression multivariable analysis. We used a backward model selection and variables that were least significant were removed. We adjusted for reason for visit, patient characteristics such as age, sex, ethnicity, race, reason for visit, preferred language, and insurance. Variables that were not significant that were removed from our final model included median income estimated by zip code, clinic location, provider age, provider sex, and provider training. RESULTS: We reviewed 4234 visits: 1567 (37%) were telemedicine in the form of video 1402 (33.1%) or telephone 164 (3.8%). The cohort consisted of 2516 patients, Non-Hispanic White (n = 1789, 71.1%) and Hispanic (n = 417, 16.6%). We performed multivariable logistic regression analysis and demonstrated that patients who were Hispanic, older, or had Medicaid insurance were significantly less likely to access telemedicine during the pandemic. We did not identify differences in telemedicine utilization when stratifying providers by their age, sex, or training type (physician or advanced practice provider). CONCLUSION: We conclude that there are differences in the use of telemedicine and that this difference may compound existing disparities in care. Additionally, we identified that these differences were not associated with provider attributes. Further study is needed to overcome barriers in access to telemedicine.