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. 2020 Dec 1;3(12):e2031640.
doi: 10.1001/jamanetworkopen.2020.31640.

Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic

Lauren A Eberly  1   2   3   4 , Michael J Kallan  5 , Howard M Julien  1   3 , Norrisa Haynes  1   3 , Sameed Ahmed M Khatana  1   2   4 , Ashwin S Nathan  1   2   4 , Christopher Snider  5 , Neel P Chokshi  1   6 , Nwamaka D Eneanya  4   5   7 , Samuel U Takvorian  8 , Rebecca Anastos-Wallen  9 , Krisda Chaiyachati  9   10 , Marietta Ambrose  1   3 , Rupal O'Quinn  1 , Matthew Seigerman  1 , Lee R Goldberg  1 , Damien Leri  10 , Katherine Choi  10 , Yevginiy Gitelman  9   10 , Daniel M Kolansky  1 , Thomas P Cappola  1   3 , Victor A Ferrari  1 , C William Hanson  11 , Mary Elizabeth Deleener  11 , Srinath Adusumalli  1   2   3   4   10   11
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Patient Characteristics Associated With Telemedicine Access for Primary and Specialty Ambulatory Care During the COVID-19 Pandemic

Lauren A Eberly et al. JAMA Netw Open. .

Erratum in

  • Error in Abstract.
    [No authors listed] [No authors listed] JAMA Netw Open. 2021 Feb 1;4(2):e211913. doi: 10.1001/jamanetworkopen.2021.1913. JAMA Netw Open. 2021. PMID: 33606029 Free PMC article. No abstract available.

Abstract

Importance: The coronavirus disease 2019 (COVID-19) pandemic has required a shift in health care delivery platforms, necessitating a new reliance on telemedicine.

Objective: To evaluate whether inequities are present in telemedicine use and video visit use for telemedicine visits during the COVID-19 pandemic.

Design, setting, and participants: In this cohort study, a retrospective medical record review was conducted from March 16 to May 11, 2020, of all patients scheduled for telemedicine visits in primary care and specialty ambulatory clinics at a large academic health system. Age, race/ethnicity, sex, language, median household income, and insurance type were all identified from the electronic medical record.

Main outcomes and measures: A successfully completed telemedicine visit and video (vs telephone) visit for a telemedicine encounter. Multivariable models were used to assess the association between sociodemographic factors, including sex, race/ethnicity, socioeconomic status, and language, and the use of telemedicine visits, as well as video use specifically.

Results: A total of 148 402 unique patients (86 055 women [58.0%]; mean [SD] age, 56.5 [17.7] years) had scheduled telemedicine visits during the study period; 80 780 patients (54.4%) completed visits. Of 78 539 patients with completed visits in which visit modality was specified, 35 824 (45.6%) were conducted via video, whereas 24 025 (56.9%) had a telephone visit. In multivariable models, older age (adjusted odds ratio [aOR], 0.85 [95% CI, 0.83-0.88] for those aged 55-64 years; aOR, 0.75 [95% CI, 0.72-0.78] for those aged 65-74 years; aOR, 0.67 [95% CI, 0.64-0.70] for those aged ≥75 years), Asian race (aOR, 0.69 [95% CI, 0.66-0.73]), non-English language as the patient's preferred language (aOR, 0.84 [95% CI, 0.78-0.90]), and Medicaid insurance (aOR, 0.93 [95% CI, 0.89-0.97]) were independently associated with fewer completed telemedicine visits. Older age (aOR, 0.79 [95% CI, 0.76-0.82] for those aged 55-64 years; aOR, 0.78 [95% CI, 0.74-0.83] for those aged 65-74 years; aOR, 0.49 [95% CI, 0.46-0.53] for those aged ≥75 years), female sex (aOR, 0.92 [95% CI, 0.90-0.95]), Black race (aOR, 0.65 [95% CI, 0.62-0.68]), Latinx ethnicity (aOR, 0.90 [95% CI, 0.83-0.97]), and lower household income (aOR, 0.57 [95% CI, 0.54-0.60] for income <$50 000; aOR, 0.89 [95% CI, 0.85-0.92], for $50 000-$100 000) were associated with less video use for telemedicine visits. These results were similar across medical specialties.

Conclusions and relevance: In this cohort study of patients scheduled for primary care and medical specialty ambulatory telemedicine visits at a large academic health system during the early phase of the COVID-19 pandemic, older patients, Asian patients, and non-English-speaking patients had lower rates of telemedicine use, while older patients, female patients, Black, Latinx, and poorer patients had less video use. Inequities in accessing telemedicine care are present, which warrant further attention.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Eneanya reported receiving personal fees from Somatus outside the submitted work. Dr Chaiyachati reported receiving grants from Agency for Healthcare Research & Quality and Patient-Centered Outcomes Research Institute, and personal fees from Roundtrip Inc outside the submitted work. Dr Goldberg reported receiving grants from Respircaridia, and personal fees from Respircardia and Abbott outside the submitted work. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Forest Plots Showing Adjusted Odds Ratios for Telemedicine Visit Completion
Figure 2.
Figure 2.. Forest Plots Showing Adjusted Odds Ratios for Video Use for Telemedicine Visit
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