Differences in Telemedicine Use for Patients With Diabetes in an Academic Versus Safety Net Health System: Retrospective Cohort Study.

BACKGROUND

The COVID-19 public health emergency catalyzed widespread adoption of both video- and audio-only telemedicine visits. This proliferation highlighted inequities in use by age, race and ethnicity, and preferred language. Few studies have investigated how differences in health system telemedicine implementation affected these inequities.

OBJECTIVE

This study aims to describe patients who used telemedicine during the public health emergency and identify predictors of telemedicine use across 2 health systems with different telemedicine implementations.

METHODS

This retrospective cohort study included adults with diabetes receiving primary care between July 2020 and March 2021 at 2 independent health systems in San Francisco, California. Participant sociodemographic characteristics, health information, and telemedicine utilization were acquired from electronic health records. The primary outcome was visit type (any audio or video telemedicine vs in-person only) during the study period. We used multivariable logistic regression to assess the association between visit type and key predictors associated with digital exclusion (age, race and ethnicity, preferred language, and neighborhood socioeconomic status), adjusting for baseline health. We included an interaction term to evaluate health system impact on each predictor and then stratified by health system (academic, which prioritized video-enabled visits, vs safety net, which prioritized audio-only visits).

RESULTS

Among 10,201 patients, we found higher odds of telemedicine use in the safety net system compared with the academic system (adjusted odds ratio [aOR] 2.94, 95% CI 2.48-3.48). Patients with younger age (18-34 years: aOR 2.55, 95% CI 1.63-3.97; 35-49 years: aOR 1.39, 95% CI 1.12-1.73 vs 75+ years) and Chinese-language preference (aOR 2.04, 95% CI 1.66-2.5 vs English) had higher odds of having a telemedicine visit. Non-Hispanic Asian (aOR 0.67, 95% CI 0.56-0.79), non-Hispanic Black (aOR 0.83, 95% CI 0.68-1), and Hispanic or Latine (aOR 0.76, 95% CI 0.61-0.95) patients had lower odds of having a telemedicine visit than non-Hispanic White patients. We found significant interactions between health system and age, race and ethnicity, and preferred language (P<.05). After stratifying by health system, several differences persisted in the academic system: non-Hispanic Asian (aOR 0.57, 95% CI 0.46-0.70) and Latine (aOR 0.67, 95% CI 0.50-0.91) patients had lower odds of a telemedicine visit, and younger age groups had higher odds (18-34 years: aOR 3.97, 95% CI 1.99-7.93; 35-49 years: aOR 1.86, 95% CI 1.36-2.56). In the safety net system, Chinese-speaking patients had higher odds of having a telemedicine visit (aOR 2.52, 95% CI 1.85-3.42).

CONCLUSIONS

We found disparities in telemedicine utilization by age, race and ethnicity, and preferred language, primarily in the health system that used more video visits. While telemedicine expanded rapidly recently, certain populations remain at risk for digital exclusion. These findings suggest that system-level factors influence telemedicine adoption and implementation decisions impact accessibility for populations at risk for digital exclusion.