Telemedicine use among patients with metastatic breast cancer during the COVID-19 pandemic: Differences by race, age, and region

Telemedicine impact on patient disparities and physician practice patterns in cancer rehabilitation: A multicenter retrospective study

OBJECTIVE

To examine the impact of telemedicine on demographic and practice patterns between outpatients receiving virtual versus in-person cancer rehabilitation physiatry care.

DESIGN

Multicenter retrospective study.

SETTING

Outpatient cancer rehabilitation physiatry clinics at four academic medical centers in the United States.

PATIENTS

Patients with cancer diagnoses or history of cancer diagnosis.

INTERVENTIONS

Cancer rehabilitation physiatry encounters.

MAIN OUTCOME MEASURES

Visit mode (in-person, telemedicine); disparities variables (age, race, and gender) by visit mode, and practice interventions (imaging, medications, procedures, other orders, and orders of any type) by visit mode.

RESULTS

Among a total of 7004 encounters, 2687 unique patients were found. In-person participants were significantly older than the average telemedicine participant (mean 62.9 vs. 60.7 years; p < .001). A race effect was seen (p = .037) with individuals reporting as Asian or other being more likely to have telemedicine encounters. No gender disparities were seen. Using a random visit analysis model to compare populations receiving in-person versus telemedicine care, a slight majority (53%) of follow-up visits were via telemedicine, versus 40% of new patient visits (p < .001). No significant differences were seen in medication prescribing frequency (38.9% telemedicine vs. 36.7% in-person, adjusted relative risk [RR]: 0.988, confidence interval [CI]: 0.73-1.34; p = .988) or imaging frequency (2.4% telemedicine vs. 7.6%; adjusted RR: 0.784, CI: 0.44-1.39; p = .408) between telemedicine versus in-person visit types. Other orders were significantly less likely to be placed during telemedicine than in-person visits (19.9% telemedicine vs. 28.6% in-person; adjusted RR: 0.623, CI: 0.45-0.86, p = .004). Order(s) of any type were placed in 54% of visits (52% telemedicine vs. 56% in-person; adjusted RR: 0.92 for telemedicine, CI: 0.83-1.01, p = .082).

CONCLUSIONS

Telemedicine has been integrated into cancer rehabilitation physiatry practices and appears to be conducive for placing many types of orders, especially medications. Age was found to be the only major demographic difference between in-person and telehealth patients.

Rural, Regional, Racial Disparities in Telemedicine Use During the COVID-19 Pandemic Among US Adults: 2021 National Health Interview Survey (NHIS)

Objective

The primary objective of this study is to conduct a comparative analysis of telemedicine utilization patterns among adult populations residing in both rural and urban areas and evaluate the probability of telemedicine adoption among adults dwelling in both rural and urban areas amid the backdrop of the COVID-19 pandemic.

Methods

Our study has attained sample populations (n = 279,260, National Weighted Estimates = 2,391,188,373) through the secondary analysis of the National Health Interview Survey (NHIS) for the year 2021. We examined the relationship between the rural, regional, and racial variables using chi-square tests and binary logistic regression associated with telemedicine use in our multivariable analysis.

Results

Telemedicine use by population decreased with decreasing urbanization level, from 40.2% among adults living in large central metropolitan to 29.7% among adults living in rural area (p<0.0001). Regarding household income, adults with 400% or more of the federal poverty level (FPL) were significantly more likely to use telemedicine than adults with less than 100% of the FPL. Females were more likely than males to utilize telemedicine. In terms of region, adults living in the West were 1.25 times more likely to use telemedicine than adults living in the Northeast, and minority race/ethnicity groups (eg, Non-Hispanic Black, Hispanic, and other) are less likely to use the telemedicine rather than Non-Hispanic White.

Conclusion

Health equity is attained when all demographic groups enjoy uniform access to healthcare services, but disparities emerge when there are discernible variations in access to treatment. Considering this study's findings, it becomes evident that the distinctions in poverty rates, median income levels, and healthcare utilization patterns across racial and regional lines may serve as indicators of potential health equity concerns.

Sociodemographic Inequities in Telemedicine Use Among US Patients Initiating Treatment in Community Cancer Centers During the Ongoing COVID-19 Pandemic, 2020-2022

PURPOSE

Although telemedicine was seen as a way to improve cancer care during the coronavirus disease (COVID-19) pandemic, there is limited information regarding inequities in its uptake. This study assessed sociodemographic factors associated with telemedicine use among patients initiating treatment for 20 common cancers.

METHODS

This retrospective cohort study used deidentified electronic health record-derived patient data from a nationwide network of community cancer practices, linked to area-level Census information. We included adults (age 18 years and older) who initiated first-line systemic cancer treatment between March 2020 and December 2022 (follow-up through March 2023). Exposures include race/ethnicity, insurance status, and area-level social determinants of health (eg, block group socioeconomic status [SES]). The outcome was telemedicine use within 90 days after treatment initiation. Associations were examined using logistic regression models adjusted for age, sex, performance status, stage, and cancer type.

RESULTS

This study included 36,993 patients (48.6% women; median age, 69 years), of whom 15.1% used telemedicine services. Black (12.2%; odds ratio [OR], 0.78 [95% CI, 0.70 to 0.88]) and uninsured (9.2%; OR, 0.59 [95% CI, 0.48 to 0.73]) patients were less likely to use telemedicine services than their White and well-insured counterparts (14.5% and 15.0%, respectively). Patients in rural (9.7%; OR, 0.54 [95% CI, 0.46 to 0.57]), suburban (11.8%; OR, 0.67 [95% CI, 0.61 to 0.74]), and low SES areas (9.9%; OR, 0.39 [95% CI, 0.35 to 0.43]) were less also likely to use telemedicine than their counterparts in urban (16.6%) or high SES (21.6%) areas.

CONCLUSION

Nearly one sixth of patients initiating cancer treatment during the pandemic used telemedicine, but there were substantial inequities. The proliferation of telemedicine may perpetuate cancer care inequities if marginalized populations do not have equitable access.