Variation in telemedicine usage in gynecologic cancer: Are we widening or narrowing disparities?

Anna Jo Bodurtha Smith, Emily G. Gleason,Leslie Andriani, Jonathan Heintz,Emily M. Ko

GYNECOLOGIC ONCOLOGY(2024)

引用 0|浏览3
暂无评分
摘要
Introduction. Telemedicine rapidly increased with the COVID-19 pandemic and could reduce cancer care disparities. Our objective was to evaluate sociodemographic (race, insurance), patient, health system, and cancer factors associated with telemedicine use in gynecologic cancers. Methods. We conducted a retrospective cohort study of patients with endometrial cancer and epithelial ovarian cancer with at least one visit from March 2020 to October 2021, using a real-world electronic health record-derived database, representing approximately 800 sites in US academic (14%) and community practices (86%). We used multivariable Poisson regression modeling to analyze the association of ever using telemedicine with patient, sociodemographic, health system, and cancer factors. Results. Of 3950 patients with ovarian cancer, 1119 (28.3%) had at least one telemedicine visit. Of 2510 patients with endometrial cancer, 720 (28.7%) had at least one telemedicine visit. At community cancer practices, patients who identified as Black were less likely to have a telemedicine visit than patients who identified as white in both ovarian and endometrial cancer (Ovarian: RR 0.62, 95% CI 0.42-0.9; Endometrial: RR 0.56, 95% CI 0.38-0.83). Patients in the Southeast, Midwest, West, and Puerto Rico were less likely to have telemedicine visits than patients in the Northeast. Uninsured patients were less likely, and patients with Medicare were more likely, to have one or more telemedicine visit than patients with private insurance. Conclusions. In this national cohort study, <30% of patients ever used telemedicine, and significant racial and regional disparities existed in utilization. Telemedicine expansion efforts should include programs to improve equity in access to telemedicine.
更多
查看译文
关键词
Telemedicine,Ovarian cancer,Uterine cancer,Health disparities,Health policy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要