Evidence map›Paper›PMID 34107542›Full record

ArticleApplied clinical informatics2021

Disparities in Telemedicine Access: A Cross-Sectional Study of a Newly Established Infrastructure during the COVID-19 Pandemic.

Vivian Hsiao, Thevaa Chandereng, Robin L Lankton, Jeffrey A Huebner, Jeffrey J Baltus, Grace E Flood, Shannon M Dean, Amye J Tevaarwerk, David F Schneider

Abstract read
In one paragraph

Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

85 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Comparison of buprenorphine treatment by virtual-only vs. traditional clinicians.Journal of substance use and addiction treatment · 2026
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25 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Vivian HsiaoUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.
Thevaa ChanderengColumbia University, Department of Biostatistics, New York City, New York, United States.
Robin L LanktonUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.
Jeffrey A HuebnerUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.
Jeffrey J BaltusUniversity of Wisconsin Hospitals and Clinics, Madison, Wisconsin, United States.
Grace E FloodColumbia University, Department of Biostatistics, New York City, New York, United States.
Shannon M DeanUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.
Amye J TevaarwerkUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.
David F SchneiderUniversity of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, United States.

Funding

UW COMPREHENSIVE CANCER CENTER SUPPORTP30CA014520 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Christian Capitini · 1985 to 2026
$142.6M
University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
University of Wisconsin Voice Research Training Program (T32)T32DC009401 · NIDCD · UNIVERSITY OF WISCONSIN-MADISON · PI Susan Lynn Thibeault · 2009 to 2026
$6.3M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UL1 TR002373NCI NIH HHS P30 CA014520NIDCD NIH HHS T32 DC009401P30 CA014520 NCI Cancer Center SupportT32 DC009401 NIH/NIDCDUL1TR000427 NIH/NCATS
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic led to dramatic increases in telemedicine use to provide outpatient care without in-person contact risks. Telemedicine increases options for health care access, but a "digital divide" of disparate access may prevent certain populations from realizing the benefits of telemedicine.

objectivesThe study aimed to understand telemedicine utilization patterns after a widespread deployment to identify potential disparities exacerbated by expanded telemedicine usage.

methodsWe performed a cross-sectional retrospective analysis of adults who scheduled outpatient visits between June 1, 2020 and August 31, 2020 at a single-integrated academic health system encompassing a broad range of subspecialties and a large geographic region in the Upper Midwest, during a period of time after the initial surge of COVID-19 when most standard clinical services had resumed. At the beginning of this study period, approximately 72% of provider visits were telemedicine visits. The primary study outcome was whether a patient had one or more video-based visits, compared with audio-only (telephone) visits or in-person visits only. The secondary outcome was whether a patient had any telemedicine visits (video-based or audio-only), compared with in-person visits only.

resultsA total of 197,076 individuals were eligible (average age = 46 years, 56% females). Increasing age, rural status, Asian or Black/African American race, Hispanic ethnicity, and self-pay/uninsured status were significantly negatively associated with having a video visit. Digital literacy, measured by patient portal activation status, was significantly positively associated with having a video visit, as were Medicaid or Medicare as payer and American Indian/Alaskan Native race.

conclusionOur findings reinforce previous evidence that older age, rural status, lower socioeconomic status, Asian race, Black/African American race, and Hispanic/Latino ethnicity are associated with lower rates of video-based telemedicine use. Health systems and policies should seek to mitigate such barriers to telemedicine when possible, with efforts such as digital literacy outreach and equitable distribution of telemedicine infrastructure.

Indexed as

AdolescentAdultAgedCOVID-19Cross-Sectional StudiesFemaleHealthcare DisparitiesHealth Services AccessibilityHumansMaleMiddle AgedPandemicsRetrospective StudiesTelemedicineYoung Adult

Identifiers

PMID34107542
PMCPMC8189758

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.