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Disparities in Telemedicine Utilization for Urology Patients During the COVID-19 Pandemic.
Javier-DesLoges, Juan; Meagher, Margaret; Soliman, Shady; Yuan, Julia; Hakimi, Kevin; Ghali, Fady; Nalawade, Vinit; Patel, Devin N; Monga, Manoj; Murphy, James D; Derweesh, Ithaar.
  • Javier-DesLoges J; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Meagher M; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Soliman S; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Yuan J; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Hakimi K; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Ghali F; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Nalawade V; Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA.
  • Patel DN; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Monga M; Department of Urology, UC San Diego School of Medicine, La Jolla, CA.
  • Murphy JD; Department of Radiation Medicine and Applied Sciences, UC San Diego School of Medicine, La Jolla, CA.
  • Derweesh I; Department of Urology, UC San Diego School of Medicine, La Jolla, CA. Electronic address: iderweesh@ucsd.edu.
Urology ; 163: 76-80, 2022 05.
Article in English | MEDLINE | ID: covidwho-1586290
ABSTRACT

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.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Urology / Telemedicine / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Limits: Humans Language: English Journal: Urology Year: 2022 Document Type: Article Affiliation country: J.urology.2021.11.037

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Urology / Telemedicine / COVID-19 Type of study: Cohort study / Observational study / Prognostic study Limits: Humans Language: English Journal: Urology Year: 2022 Document Type: Article Affiliation country: J.urology.2021.11.037