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Socioeconomic Disparities in Patient Use of Telehealth During the Coronavirus Disease 2019 Surge

Educational Objective
To identify the key insights or developments described in this article
1 Credit CME
Key Points

Question  What demographic and socioeconomic factors were associated with patient participation in telehealth during the coronavirus disease 2019 (COVID-19) pandemic surge?

Findings  In a cohort study of 1162 patients at a large, urban tertiary care center in the Midwest, age, sex, median household income, insurance status, and marital status were associated with patient participation in telehealth during the COVID-19 pandemic surge.

Meaning  Similar characteristics that are associated with inequitable access to in-person medical care are also associated with inequitable access to telehealth; a focus on vulnerable patient populations in a changing landscape is necessary to provide timely and essential medical care.

Abstract

Importance  The coronavirus disease 2019 (COVID-19) pandemic required the rapid transition to telehealth with the aim of providing patients with medical access and supporting clinicians while abiding by the stay-at-home orders.

Objective  To assess demographic and socioeconomic factors associated with patient participation in telehealth during the COVID-19 pandemic.

Design, Setting, and Participants  This cohort study included all pediatric and adult patient encounters at the Department of Otolaryngology–Head & Neck Surgery in a tertiary care, academic, multisubspecialty, multisite practice located in an early hot spot for the COVID-19 pandemic from March 17 to May 1, 2020. Encounters included completed synchronous virtual, telephone, and in-person visits as well as visit no-shows.

Main Outcomes and Measures  Patient demographic characteristics, insurance status, and 2010 Census block level data as a proxy for socioeconomic status were extracted. Univariate and multivariate logistic regression models were created for patient-level comparisons.

Results  Of the 1162 patients (604 females [52.0%]; median age, 55 [range, 0-97] years) included, 990 completed visits; of these, 437 (44.1%) completed a virtual visit. After multivariate adjustment, females (odds ratio [OR], 1.71; 95% CI, 1.11-2.63) and patients with preferred provider organization insurance (OR, 2.70; 95% CI, 1.40-5.20) were more likely to complete a virtual visit compared with a telephone visit. Increasing age (OR per year, 0.98; 95% CI, 0.98-0.99) and being in the lowest median household income quartile (OR, 0.60; 95% CI, 0.42-0.86) were associated with lower odds of completing a virtual visit overall. Those patients within the second (OR, 0.53; 95% CI, 0.28-0.99) and lowest (OR, 0.33; 95% CI, 0.17-0.62) quartiles of median household income by census block and those with Medicaid, no insurance, or other public insurance (OR, 0.47; 95% CI, 0.23-0.94) were more likely to complete a telephone visit. Finally, being within the lower 2 quartiles of proportion being married (OR for third quartile, 0.49 [95% CI, 0.29-0.86]; OR for lowest quartile, 0.39 [95% CI, 0.23-0.67]) was associated with higher likelihood of a no-show visit.

Conclusions and Relevance  These findings suggest that age, sex, median household income, insurance status, and marital status are associated with patient participation in telehealth. These findings identify vulnerable patient populations who may not engage with telehealth, yet still require medical care in a changing health care delivery landscape.

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Article Information

Accepted for Publication: November 16, 2020.

Published Online: January 14, 2021. doi:10.1001/jamaoto.2020.5161

Corresponding Author: Ilaaf Darrat, MD, MBA, Department of Otolaryngology–Head & Neck Surgery, Henry Ford Hospital, 2799 W Grand Blvd, Detroit, MI 48202 (idarrat1@hfhs.org).

Author Contributions: Drs Darrat and Tam had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Darrat, Tam, Williams.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: Darrat, Tam, Williams.

Statistical analysis: Darrat, Tam, Boulis.

Administrative, technical, or material support: Williams.

Supervision: Darrat, Williams.

Conflict of Interest Disclosures: None reported.

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